[go: up one dir, main page]

Next Issue
Volume 13, May
Previous Issue
Volume 13, March
 
 

Land, Volume 13, Issue 4 (April 2024) – 162 articles

Cover Story (view full-size image): Many land rights in Kenya are undocumented. Land administration is implemented in a distributed environment, and land data are available in different systems. Thus, there is a need for data sharing. Guidelines are necessary in support for the development of a land data exchange and interoperability framework. With the ISO Framework for Enterprise Interoperability combined with the Land Administration Domain Model profile for Kenya, such an interoperability framework is developed. Four key issues are identified and modeled, and mapping them to the sustainable development goals helps in achieving those goals. Implementing and testing the LADM profile for Kenya is easy using GIS tools. With the LADM compliant database, a complete and accurate workflow is assured. Integration with external databases aids in improving efficiency and eliminating duplication. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
28 pages, 11064 KiB  
Article
Navigating Post-COVID-19 Social–Spatial Inequity: Unravelling the Nexus between Community Conditions, Social Perception, and Spatial Differentiation
by Minjun Zhao, Ning Liu, Jinliu Chen, Danqing Wang, Pengcheng Li, Di Yang and Pu Zhou
Land 2024, 13(4), 563; https://doi.org/10.3390/land13040563 - 22 Apr 2024
Cited by 3 | Viewed by 981
Abstract
The 2023 SDGs report underscores the prolonged disruption of COVID-19 on community living spaces, infrastructure, education, and income equality, exacerbating social and spatial inequality. Against the backdrop of the dual impact of significant events and the emergence of digital technologies, a coherent research [...] Read more.
The 2023 SDGs report underscores the prolonged disruption of COVID-19 on community living spaces, infrastructure, education, and income equality, exacerbating social and spatial inequality. Against the backdrop of the dual impact of significant events and the emergence of digital technologies, a coherent research trajectory is essential for characterizing social–spatial equity and understanding its influential factors within the urban planning discipline. While prior research emphasized spatial dimensions and mitigated spatial differentiation to ensure urban equity, the complexity of these interconnections necessitates a more comprehensive approach. This study adopts a holistic perspective, focusing on the “social–spatial” dynamics, utilizing social perception (sentiment maps) and spatial differentiation (housing prices index) pre- and post-pandemic to elucidate the interconnected and interactive nature of uneven development at the urban scale. It employs a multi-dimensional methodological framework integrating morphology analysis of housing conditions, GIS analysis of urban amenities, sentiment semantic analysis of public opinion, and multiscale geographically weighted regression (MGWR) analysis of correlation influential factors. Using Suzhou, China, as a pilot study, this research demonstrates how these integrated methods complement each other, exploring how community conditions and resource distribution collectively bolster resilience, thereby maintaining social–spatial equity amidst pandemic disruptions. The findings reveal that uneven resource distribution exacerbates post-pandemic social stratification and spatial differentiation. The proximity of well-maintained ecological environments, such as parks or scenic landmarks, generally exhibits consistency and positive effects on “social–spatial” measurement. Simultaneously, various spatial elements influencing housing prices and social perception show geographic heterogeneity, particularly in areas farther from the central regions of Xiangcheng and Wujiang districts. This study uncovers a bilateral mechanism between social perception and spatial differentiation, aiming to delve into the interdependent relationship between social–spatial equity and built environmental factors. Furthermore, it aspires to provide meaningful references and recommendations for urban planning and regeneration policy formulation in the digital era to sustain social–spatial equity. Full article
Show Figures

Figure 1

Figure 1
<p>Research conceptual framework.</p>
Full article ">Figure 2
<p>Suzhou location and the main research area. Source: self-drawn by author; map review number of China: GS (2023) 2767, supervised by the Ministry of Natural Resources.</p>
Full article ">Figure 3
<p>Sentiment analysis diagram and principle based on SnowNLP.</p>
Full article ">Figure 4
<p>Robust tests via Monte-Carlo testing for spatial variability.</p>
Full article ">Figure 5
<p>Word frequency analysis of Weibo check-in data. (<b>a</b>) 2020; (<b>b</b>) 2022.</p>
Full article ">Figure 6
<p>Sentiment analysis results of Weibo check-in data ((<b>left</b>) 2020, (<b>right</b>) 2022).</p>
Full article ">Figure 7
<p>Scatter plot and local clustering of Weibo index differences in 2020 and 2022.</p>
Full article ">Figure 8
<p>MGWR analysis results combined sentiment maps with community conditions.</p>
Full article ">Figure 9
<p>Spatial analysis of housing price data ((<b>left</b>) 2020, (<b>right</b>) 2022).</p>
Full article ">Figure 10
<p>Scatter plot and local clustering of the growth rate of housing prices in 2020 and 2022.</p>
Full article ">Figure 11
<p>Spatial-analysis-results-related housing price index via MGWR; building floors (A4); education quantity (Cl); park distance (B3); bus quantity (C2); floor area ratio (Al); community establishment age (A2); greening rate (A3); subway distance (B2).</p>
Full article ">
18 pages, 6982 KiB  
Article
Unveiling the Impact of Urbanization on Net Primary Productivity: Insights from the Yangtze River Delta Urban Agglomeration
by Jing Gao, Min Liu and Xiaoping Wang
Land 2024, 13(4), 562; https://doi.org/10.3390/land13040562 - 22 Apr 2024
Cited by 1 | Viewed by 852
Abstract
Urbanization has significantly altered the carbon cycle of the terrestrial environment, particularly in relation to net primary productivity (NPP). Gaining a more comprehensive comprehension of how NPP is affected by urbanization is crucial for obtaining fresh perspectives on sustainable urban landscape design and [...] Read more.
Urbanization has significantly altered the carbon cycle of the terrestrial environment, particularly in relation to net primary productivity (NPP). Gaining a more comprehensive comprehension of how NPP is affected by urbanization is crucial for obtaining fresh perspectives on sustainable urban landscape design and decision making. While there is a significant body of research examining the geographical and temporal patterns of NPP supply capacity, there are only a few studies that have investigated the spatial relationships between NPP and urbanization, particularly at the grid scale. This research investigated the temporal and geographical features and patterns of NPP and their impact mechanisms. In order to estimate NPP and the level of urbanization in the Yangtze River Delta Urban Agglomeration (YRDUA), we used a combination of different models and datasets. To evaluate the geographical correlations and dependence between NPP and urbanization, we utilized local bivariate autocorrelation methods and spatial regression models to describe and visualize these relationships. The findings revealed that there was a consistent negative relationship between NPP and urbanization on a global scale from 1990 to 2020. However, when examining the local scale, the geographical correlations could be classified into four distinct categories: areas with both low NPP and low urbanization, areas with high NPP and high urbanization, areas with low NPP and high urbanization, and areas with high NPP and low urbanization. Our analysis showed that spatial regression models are more suitable for quantifying the spatial relationship between NPP and urbanization due to their ability to include the impacts of spatial Moran’s I techniques. Due to the growing urbanization, the highest NPP value was recorded in 2005, followed by 2000, 2020, and 2010. Conversely, the smallest association was observed in 2015. Examining the geographical connection between NPP and urbanization offers theoretical and practical insights for urban planning that prioritizes human needs and promotes sustainable development. It also aids in the development of reasonable methods for organizing ecological functional systems. Full article
(This article belongs to the Special Issue Land-Based Greenhouse Gas Mitigation for Carbon Neutrality)
Show Figures

Figure 1

Figure 1
<p>Map of the study area. <b>Top left</b> panel: the national boundary of China (green area is the location of the YR Economic Belt in China); <b>bottom left</b> panel: the administrative boundary of the YR Economic Belt (green area is the YRDUA in the YR Economic Belt); <b>bottom right</b> panel: the administrative boundary of the YRDUA (administrative districts); and <b>top right</b> panel: a representative city (Shanghai) in the YRDUA.</p>
Full article ">Figure 2
<p>The process for determining the spatial relationship between NPP and urbanization.</p>
Full article ">Figure 3
<p>Spatial pattern of comprehensive urbanization level (CUL) in the YRDUA from 1990 to 2020.</p>
Full article ">Figure 4
<p>Comparison of comprehensive urbanization level (CUL) across the 16 cities in the YRDUA during 1990–2020.</p>
Full article ">Figure 5
<p>Spatial–temporal correlations between NPP and CUL (global bivariate Moran’s I autocorrelation).</p>
Full article ">Figure 6
<p>Spatial–temporal correlations between NPP and CUL (LISA diagram).</p>
Full article ">Figure 7
<p>Regression coefficient and standard residual distribution of CUL from 1990 to 2020.</p>
Full article ">
18 pages, 12403 KiB  
Article
Ecological Risk Assessment of Land Use Change in the Tarim River Basin, Xinjiang, China
by Yaqi Cheng, Xuyang Zhang and Wei Song
Land 2024, 13(4), 561; https://doi.org/10.3390/land13040561 - 22 Apr 2024
Viewed by 956
Abstract
In recent years, global climate change and human alterations to land use have led to a decrease in ecosystem services, making ecosystems more vulnerable. However, unlike the well-established risk assessment frameworks used in natural disaster research, the concept of ecological risks arising from [...] Read more.
In recent years, global climate change and human alterations to land use have led to a decrease in ecosystem services, making ecosystems more vulnerable. However, unlike the well-established risk assessment frameworks used in natural disaster research, the concept of ecological risks arising from changes in land use is still in its early stages, with its nuances and assessment methodologies yet to be clearly defined. This study proposes a new framework for assessing ecological risks resulting from changes in land use in the Tarim River Basin. The framework employs a coupled PLUS and Invest model to evaluate the ecological risks of land use change under three development scenarios projected for the Tarim River Basin in Xinjiang by 2035. The findings indicate that: (1) Between 2000 and 2020, the predominant land use types in the Tarim River Basin in Xinjiang were primarily unused land, followed by grassland and cropland. Conversely, grassland, water, and construction land were relatively less prevalent. During this period, the area of unused land and cultivated land increased, while grassland, forest land, and water exhibited a declining trend. Moving forward, under the three scenarios from 2020 to 2035, land use changes in the study area are characterized by the expansion of cropland and unused land, coupled with a significant decrease in grassland area, while other land categories demonstrate minor fluctuations. (2) From 2020 to 2035, across various scenarios, the total ecosystem service within the study area demonstrates an overall increasing trend in both the northern and southern marginal zones. Specifically, under the baseline scenario, the total amount of ecosystem services in the study area decreased by 15.247% compared to 2020. Similarly, under the economic development scenario, this decrease amounted to 13.358% compared to 2020. Conversely, under the ecological protection scenario, the decrease reached 19.852% compared to 2020. (3) The structure of ecological risk levels from 2020 to 2035, across multiple scenarios, demonstrates a consistent pattern, characterized by a predominant proportion of moderate risk. Conversely, other risk levels occupy relatively smaller proportions of the area. Full article
(This article belongs to the Special Issue Landscape Ecological Risk in Mountain Areas)
Show Figures

Figure 1

Figure 1
<p>Overview of the study area. (<b>a</b>) Location of the Tarim River Basin in China, (<b>b</b>) Tarim River Basin countries, (<b>c</b>) Tarim River Basin DEM.</p>
Full article ">Figure 2
<p>Research framework.</p>
Full article ">Figure 3
<p>Spatial distribution of land use from 2000 to 2020.</p>
Full article ">Figure 4
<p>Distribution of increases and decreases in different land use types.</p>
Full article ">Figure 5
<p>Distribution of multi-scenario land use projections for 2035.</p>
Full article ">Figure 6
<p>Spatial distribution of multi-scenario projections of ecosystem services from 2020 to 2035.</p>
Full article ">Figure 7
<p>Spatial distribution of ecological risks under multiple scenarios in 2035.</p>
Full article ">
20 pages, 3730 KiB  
Article
Spatial Differentiation of Ecotourist Perceptions Based on the Random Forest Model: The Case of the Gansu Section of the Yellow River Basin
by Jing Yuan, Hang Gao, Yanlong Shen and Guoqiang Ma
Land 2024, 13(4), 560; https://doi.org/10.3390/land13040560 - 22 Apr 2024
Cited by 2 | Viewed by 836
Abstract
Ecotourism is vital for coordinating regional ecological protection with socio-economic development. The Gansu section of the Yellow River Basin is a typical ecologically fragile area in China, and it holds a distinctive position in ecological protection and high-quality development. This study explores spatial [...] Read more.
Ecotourism is vital for coordinating regional ecological protection with socio-economic development. The Gansu section of the Yellow River Basin is a typical ecologically fragile area in China, and it holds a distinctive position in ecological protection and high-quality development. This study explores spatial differentiation in ecotourist perceptions and their distinct effects on ecotourist satisfaction, revisitation, and recommendation. It uses four cities (Gannan, Linxia, Lanzhou, and Baiyin) in the Gansu section of the Yellow River (mainstream) as examples, employing a questionnaire survey to collect ecotourists’ perception data and applying a random forest model and one-way ANOVA for analysis. It was found that: (1) rich ecotourism potential exists in the Gansu section of the Yellow River Basin as an ecologically fragile area; (2) there is spatial differentiation in ecotourist perceptions, and among the four regions, Baiyin stands out for its nature and atmosphere perception, and Lanzhou excels in accessibility and service perception; (3) spatial disparities exist in the influencing factors of ecotourist satisfaction, revisitation, and recommendation. Ecotourists in districts with unique natural resources, such as Gannan and Baiyin, prioritize nature perception, whereas districts with abundant natural resources and an established foundation for ecotourism development, such as Linxia and Lanzhou, emphasize service and atmosphere perception. This study constructs a new research framework to explore spatial variations in ecotourists’ perceptions, assisting ecotourism destinations to meet the needs of ecotourists from the supply side, and presents distinctive strategies and recommendations for the development of ecotourism in similar ecologically fragile areas. Full article
Show Figures

Figure 1

Figure 1
<p>Study area. Notes: (<b>a</b>) displays the location of the study area within the Yellow River Basin; (<b>b</b>) illustrates the location of the study area within the Gansu Province; (<b>c</b>) illustrates the distribution of tourist attractions (5A, 4A, 3A, 2A, and A-level) in the Gansu section of the Yellow River Basin. The 5A grade represents the highest level for tourist attractions in China, symbolizing the country’s world-class premium scenic spots; 4A indicates high-quality tourist attractions with excellent amenities and services; 3A denotes good-quality tourist attractions offering enjoyable experiences; 2A represents tourist attractions with moderate facilities and services; A-level indicates basic-level tourist attractions with limited amenities and services. The figure was produced by the authors, and the data on scenic areas are sourced from the “List of A-level Tourist Attractions in Gansu Province” (as of 31 December 2022).</p>
Full article ">Figure 2
<p>Ecotourism resource of study area. Notes: Zhagana, one of the world’s 50 outdoor paradises in Gannan (<b>top left</b>); International Gliding Campsite Scenic Area in Linxia (<b>top right</b>); sheepskin raft drifting in the Yellow River in Lanzhou (<b>bottom left</b>); the Yellow River Stone Forest National Geological Park in Baiyin (<b>bottom right</b>).</p>
Full article ">Figure 3
<p>Random forest model computation flowchart.</p>
Full article ">Figure 4
<p>Ecotourism attractions in study area. Notes: (<b>a</b>) displays the area proportion of ecotourism attractions in municipalities and states within study area; (<b>b</b>) illustrates ecotourism attractions in the Gansu section of the Yellow River Basin; (<b>c</b>) shows the overall area proportion of ecotourism attractions within study area.</p>
Full article ">Figure 5
<p>Word clouds of ecotourism behavior. Notes: <a href="#land-13-00560-f005" class="html-fig">Figure 5</a> illustrates ecotourism behavior perceived by samples of ecotourists in the survey.</p>
Full article ">Figure 6
<p>Perception and variable importance analysis on ecotourist satisfaction, revisitation, and recommendation in different regions. Notes: (<b>a1</b>) and (<b>a2</b>), respectively, illustrate the perception and variable importance analysis on ecotourist satisfaction; (<b>b1</b>) and (<b>b2</b>), respectively, depict the outcomes of perception and variable importance analysis on ecotourist revisitation; (<b>c1</b>) and (<b>c2</b>), respectively, present the results of the perception and variable importance analysis on ecotourist recommendation.</p>
Full article ">
13 pages, 10688 KiB  
Article
Policies and Regulations for Desertification Prevention and Control in Mongolia
by Yuan You, Na Zhou and Yongdong Wang
Land 2024, 13(4), 559; https://doi.org/10.3390/land13040559 - 22 Apr 2024
Viewed by 1189
Abstract
Desertification is a transnational, cross-regional, and global eco-environmental problem that seriously restricts sustainable socioeconomic development. As Mongolia is a typical arid and semi-arid region, the evolution of desertification in the country is closely related to major global issues such as climate change, global [...] Read more.
Desertification is a transnational, cross-regional, and global eco-environmental problem that seriously restricts sustainable socioeconomic development. As Mongolia is a typical arid and semi-arid region, the evolution of desertification in the country is closely related to major global issues such as climate change, global carbon cycling, and biodiversity. In this article, we analyze the background, development process, limitations, and other aspects of Mongolia’s desertification prevention and control policies and regulations and conclude that Mongolia needs to formulate a “Desertification Prevention and Control Law.” In particular, it needs to clarify the responsibility subjects, beneficiaries, interest compensation subjects, and illegal punishment subjects for prevention and control, as well as the responsibilities and obligations of relevant legal subjects. The research results show that it is important to form a solution mechanism in legal research on the joint prevention and control of desertification between Mongolia and China. We propose a concept of best future practice, highlighting the urgent need to establish a framework for the joint prevention and control of desertification via a cooperative mechanism between Mongolia and China and for the two countries to jointly promote global cooperation in combating this important environmental issue. Full article
(This article belongs to the Section Land Environmental and Policy Impact Assessment)
Show Figures

Figure 1

Figure 1
<p>Schematic showing the degree of desertification and climatic zones of Mongolia. Sources: <a href="https://koeppen-geiger.vu-wien.ac.at/present.htm" target="_blank">https://koeppen-geiger.vu-wien.ac.at/present.htm</a> (accessed on 25 March 2024).</p>
Full article ">Figure 2
<p>Cross-level distribution of desertification degree in Mongolia from 1990 to 2020. Notes: (<b>a</b>) 1990–1995; (<b>b</b>) 1995–2000; (<b>c</b>) 2000–2005; (<b>d</b>) 2005–2010; (<b>e</b>) 2010–2015; (<b>f</b>) 2015–2020. In the legend, −1, −2, −3, and −4 indicate the degrees of desertification intensification, and the smaller the value, the greater the degree of desertification intensification. 1, 2, 3, and 4 indicate the degrees of desertification reduction, and the greater the value, the greater the degree of desertification reduction.</p>
Full article ">Figure 3
<p>Changes in livestock numbers in Mongolia.</p>
Full article ">
18 pages, 3426 KiB  
Article
Challenges and Institutional Barriers to Forest and Landscape Restoration in the Chittagong Hill Tracts of Bangladesh
by Oliver Tirtho Sarkar and Sharif A. Mukul
Land 2024, 13(4), 558; https://doi.org/10.3390/land13040558 - 22 Apr 2024
Viewed by 1743
Abstract
Preventing, halting, and reversing ecosystem degradation is now a global priority, partly due to the declaration of the United Nations (UN) Decade on Ecosystem Restoration by the UN General Assembly 2021–2030 on 1 March 2019. Apart from the most recent global target to [...] Read more.
Preventing, halting, and reversing ecosystem degradation is now a global priority, partly due to the declaration of the United Nations (UN) Decade on Ecosystem Restoration by the UN General Assembly 2021–2030 on 1 March 2019. Apart from the most recent global target to protect 30% of the natural planet by 2030 as part of the Kunming-Montreal Global Biodiversity Framework agreed during COP15, there are several other global goals and targets. The Government of Bangladesh (GoB) has also pledged to restore 0.75 million hectares of forests as part of the Bonn Challenge. The Chittagong Hill Tracts (CHT) of Bangladesh contain almost one-third of the country’s state-owned forests and are home to 12 ethnic communities, whose livelihoods are dependent on forests. Although once rich in biodiversity, the majority of the forests in the region are highly degraded due to faulty management, complex institutional arrangements, and land disputes with locals. The CHT, therefore, represent the most promising region for ecosystem restoration through forest and landscape restoration (FLR). Here, using the secondary literature, we examine the current institutional arrangements and drivers of deforestation and forest degradation in the CHT region and potential benefits and modalities to make FLR successful in the region. Based on our study, we suggest that institutional reform is essential for successful FLR in the CHT. We also discuss key interventions that are necessary to halt ecosystem degradation and to secure community participation in natural resources management in the region. Full article
(This article belongs to the Special Issue Institutions in Governance of Land Use: Mitigating Boom and Bust)
Show Figures

Figure 1

Figure 1
<p>Location map of Chittagong Hill Tracts in Bangladesh (<b>left</b>), with major land use/land cover (<b>right</b>). Modified after Ref. [<a href="#B3-land-13-00558" class="html-bibr">3</a>].</p>
Full article ">Figure 2
<p>Article selection process for our literature review.</p>
Full article ">Figure 3
<p>Current institutional arrangements in the CHT. Modified after Ref. [<a href="#B3-land-13-00558" class="html-bibr">3</a>].</p>
Full article ">Figure 4
<p>A <span class="html-italic">Jhum</span> field in the Chittagong Hill Tracts of Bangladesh. (Photo courtesy: Apu Nazrul).</p>
Full article ">Figure 5
<p>Fruit orchard along a newly developed road in the CHT. (Photo credit: Sharif A. Mukul).</p>
Full article ">Figure 6
<p>Potential benefits of FLR in the Chittagong Hill Tracts of Bangladesh.</p>
Full article ">Figure 7
<p>Potential sources of FLR funding for the CHT.</p>
Full article ">
23 pages, 16274 KiB  
Article
Multi-Scenario Land Use Optimization Simulation and Ecosystem Service Value Estimation Based on Fine-Scale Land Survey Data
by Rui Shu, Zhanqi Wang, Na Guo, Ming Wei, Yebin Zou and Kun Hou
Land 2024, 13(4), 557; https://doi.org/10.3390/land13040557 - 22 Apr 2024
Viewed by 973
Abstract
Land optimization simulation and ecosystem service value (ESV) estimation can better serve land managers in decision-making. However, land survey data are seldom used in existing studies, and land optimization constraints fail to fully consider land planning control, and the optimization at the provincial [...] Read more.
Land optimization simulation and ecosystem service value (ESV) estimation can better serve land managers in decision-making. However, land survey data are seldom used in existing studies, and land optimization constraints fail to fully consider land planning control, and the optimization at the provincial scale is not fine enough, which leads to a disconnection between academic research and land management. We coupled ESV, gray multi-objective optimization (GMOP), and patch-generating land use simulation (PLUS) models based on authoritative data on land management to project land use and ESV change under natural development (ND), rapid economic development (RED), ecological land protection (ELP), and sustainable development (SD) scenarios in 2030. The results show that construction land expanded dramatically (by 97.96% from 2000 to 2020), which encroached on grassland and cropland. This trend will continue in the BAU scenario. Construction land, woodland, and cropland are the main types of land used for expansion, while grassland and unused land, which lack strict use control, are the main land outflow categories. From 2000 to 2030, the total amount of ESV increases steadily and slightly. The spatial distribution of ESV is significantly aggregated and the agglomeration is increasing. The policy direction and land planning are important reasons for land use changes. The land use scenarios we set up can play an important role in preventing the uncontrolled expansion of construction land, mitigating the phenomenon of ecological construction, i.e., “governance while destruction”, and promoting food security. This study provides a new approach for provincial large-scale land optimization and ESV estimation based on land survey data and provides technical support for achieving sustainable land development. Full article
Show Figures

Figure 1

Figure 1
<p>Location and basic information of the study area. (<b>a</b>) Location and DEM of Ningxia province; (<b>b</b>) national territory spatial planning (2021–2035).</p>
Full article ">Figure 2
<p>Land use map of Ningxia in (<b>a</b>) 2000, (<b>b</b>) 2010, and (<b>c</b>) 2020.</p>
Full article ">Figure 3
<p>Flow chart of land utilization simulation and ESV evaluation.</p>
Full article ">Figure 4
<p>The spatial driving factors and spatial restrictions of the land use change in this study. (<b>a</b>) Dem; (<b>b</b>) Slope; (<b>c</b>) Aspect; (<b>d</b>) soil type e; (<b>e</b>) Precipitation; (<b>f</b>) Temperature; (<b>g</b>) Evaporation; (<b>h</b>) Dis rural settlements; (<b>i</b>). Dis railroads; (<b>j</b>) Dis national road; (<b>k</b>) Dis provincial road; (<b>l</b>) Dis other road; (<b>m</b>) Dis open economic zone; (<b>n</b>) Dis town; (<b>o</b>) Dis main rivers; (<b>p</b>) Nighttime light intensity; (<b>q</b>) GDP; (<b>r</b>) Population density; (<b>s</b>) Spatial restrictions; (<b>t</b>) RLE.</p>
Full article ">Figure 5
<p>Land use transfer in different periods: (<b>a</b>) 2000–2010; (<b>b</b>) 2010–2020; (<b>c</b>) 2000–2020; (<b>d</b>) 2020–ND; (<b>e</b>) 2020–RED; (<b>f</b>) 2020–ELP; (<b>g</b>) 2020–SD.</p>
Full article ">Figure 6
<p>Comparison of simulation land use structure and the ESV changes in 2030 under different scenarios.</p>
Full article ">Figure 7
<p>The spatial distribution of ESVs: (<b>a</b>) 2000; (<b>b</b>) 2020; (<b>c</b>) ND; (<b>d</b>) RED; (<b>e</b>) ELP; (<b>f</b>) SD.</p>
Full article ">Figure 8
<p>Increases and decreases in ESV due to increased land use.</p>
Full article ">
20 pages, 1282 KiB  
Article
Promoting Green Transformations through Smart Engagement: An Assessment of 100 Citizen-Led Urban Greening Projects
by Eleni Oikonomaki, Ilektra Papadaki and Christina Kakderi
Land 2024, 13(4), 556; https://doi.org/10.3390/land13040556 - 22 Apr 2024
Viewed by 1324
Abstract
In the face of challenges like heatwaves, flooding, other extreme events, as well as increasing pollution and declining quality of life in cities, there is a growing demand for the preservation and expansion of urban green spaces, often driven by citizen-led transformations. This [...] Read more.
In the face of challenges like heatwaves, flooding, other extreme events, as well as increasing pollution and declining quality of life in cities, there is a growing demand for the preservation and expansion of urban green spaces, often driven by citizen-led transformations. This paper examines 100 urban greening projects initiated or supported by citizens globally, categorizing them according to the type of greenery, the stakeholders involved, the mode of implementation, and the use of smart technologies incorporated. We notice variations in green endeavors based on the stakeholders orchestrating them; most of the entirely citizen-led initiatives being aimed at the creation of urban farms and food growing, demonstrating the pressing need to secure food and self-determination in communities. More than half of the assessed initiatives that managed to scale up and multiply had public authorities providing a framework or a type of support for their development or an NGO or other organization providing expertise and mobilizing citizens at various stages. In terms of technological use, we mostly found that websites and social media platforms ease participatory endeavors and knowledge sharing of best practices, accelerating scaling efforts, while there is low integration of more advanced digital technologies, which, if used, could enable real-time monitoring of green spaces, inform evidence-based decision-making, and streamline processes in scaling up green initiatives. Full article
Show Figures

Figure 1

Figure 1
<p>Geographical spread of analyzed initiatives.</p>
Full article ">Figure 2
<p>Functionalities of urban greening web platforms.</p>
Full article ">
19 pages, 11968 KiB  
Article
Validation of Remotely Sensed Land Surface Temperature at Lake Baikal’s Surroundings Using In Situ Observations
by Egor Dyukarev, Nadezhda Voropay, Oksana Vasilenko and Elena Rasputina
Land 2024, 13(4), 555; https://doi.org/10.3390/land13040555 - 21 Apr 2024
Viewed by 713
Abstract
The accuracy of Land Surface Temperature (LST) products retrieved from satellite data in mountainous-coastal areas is not well understood. This study presents an analysis of the spatial and temporal variability of the differences between the LST and in situ observed air and surface [...] Read more.
The accuracy of Land Surface Temperature (LST) products retrieved from satellite data in mountainous-coastal areas is not well understood. This study presents an analysis of the spatial and temporal variability of the differences between the LST and in situ observed air and surface temperatures (ISTs) for the southeastern slope of Lake Baikal’s surroundings. The IST was measured at 12 ground observation sites located on the southeastern macro-slope of the Primorskiy Ridge (Baikal, Russia) within an elevation range of 460–1656 m above sea level from 2009 to 2021. LST was estimated using 617 Landsat (7 and 8) images from 2009–2021, taking into account brightness temperature, surface emissivity and vegetation cover fraction. The comparison of the LST from satellite data and the IST from ground observation showed relatively high differences, which varied depending on the season and site type. A neural network was suggested and calibrated to improve the LST data. The corrected remote-sensed temperature was found to reproduce the IST very well, with mean differences of about 0.03 °C and linear correlation coefficients of 0.98 and 0.95 for the air and surface IST. Full article
(This article belongs to the Special Issue Digital Mapping for Ecological Land)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The study area (red box at top-left panel) and observation sites (black dots (top-right panel); yellow dots (bottom panel)). Observation site numbers correspond to site ID in <a href="#land-13-00555-t001" class="html-table">Table 1</a>.</p>
Full article ">Figure 2
<p>Daily average temperatures from in situ observations at 12 study sites. 1—Air IST, 2—Surface IST. Vertical axis—IST temperature (°C) for observation site, horizontal axis—time.</p>
Full article ">Figure 3
<p>LST derived from Landsat 8 image 13 June 2019. Dots—observation sites 1–12.</p>
Full article ">Figure 4
<p>LST derived from remote data for 12 observation sites. Vertical axis—LST temperature (°C) for observation site, horizontal axis—time.</p>
Full article ">Figure 5
<p>Median difference (MD) between air IST (<b>a</b>) and surface IST (<b>b</b>) or LST during different months in 2009–2021. Boxes—median ± standard deviation, whiskers—1/99 percentile, dots—outliers.</p>
Full article ">Figure 6
<p>Annual course of statistical parameters of validation for air temperature (<b>left</b>) or soil surface temperature (<b>right</b>) from 2009–2021. MD—median difference, MAR—mean absolute residuals, RMSD—root mean squared difference, R—correlation coefficient. 1—all sites, 2—open sites, 3—semi-closed sites, 4—closed sites. Black horizontal line is zero line.</p>
Full article ">Figure 7
<p>Scatter plots for air temperature (<b>left</b>) or soil surface temperature (<b>right</b>) and differences versus LST from 2009–2021. Lines: top panels—1:1 line, bottom panels—zero lines. 1—open sites, 2—semi-closed sites, 3—closed sites.</p>
Full article ">Figure 8
<p>Median difference (MD) between air IST (<b>a</b>) or surface IST (<b>b</b>) and CRT for different months from 2009–2021. Boxes—median ± standard deviation, whiskers—1/99 percentile, dots—outliers.</p>
Full article ">Figure 9
<p>Scatter plots for CRT for air (<b>left</b>) and soil (<b>right</b>) and differences CRT–IST versus IST from 2009–2021. Lines: top panels—1:1 line, bottom panels—zero lines. 1—open sites, 2—semi-closed sites and 3—closed sites.</p>
Full article ">Figure 10
<p>Median and quartile (25, 75%) values of LST, in situ temperatures (TA, TS) and corrected temperatures (CTA, CTS). Whiskers show 1% and 99% percentiles.</p>
Full article ">
28 pages, 12365 KiB  
Article
How to Realize Synergistic Emission Reduction in Future Urban Agglomerations: Spatial Planning Approaches to Reducing Carbon Emissions from Land Use: A Case Study of the Beijing–Tianjin–Hebei Region
by Haoran Li, Yang Liu, Yixiao Li, Xiaoxi Li, Shuyi Yan and Xi Zheng
Land 2024, 13(4), 554; https://doi.org/10.3390/land13040554 - 21 Apr 2024
Cited by 1 | Viewed by 841
Abstract
Land use changes in rapidly urbanizing regions around the world constitute a principal anthropogenic element fueling the surge in carbon emissions. Here, land use patterns within the Beijing–Tianjin–Hebei (BTH) urban agglomeration under low-carbon development (LCD) scenarios were simulated. Additionally, social network analysis was [...] Read more.
Land use changes in rapidly urbanizing regions around the world constitute a principal anthropogenic element fueling the surge in carbon emissions. Here, land use patterns within the Beijing–Tianjin–Hebei (BTH) urban agglomeration under low-carbon development (LCD) scenarios were simulated. Additionally, social network analysis was employed to formulate carbon balance planning guidelines for various administrative regions. (1) In the ecological protection scenario, carbon emissions from land use were 643.42 × 104 tons lower compared to the natural development scenario. Counties with high ecological support coefficients accounted for 22%, making them better suited for predicting outcomes related to low-carbon-oriented land use. (2) The spatial connections of carbon emissions in BTH were closely related, forming the three main carbon emission spatial linkage areas. (3) A carbon balance zoning plan for the BTH in 2035 under the LCD scenario was formulated. Furthermore, key areas for the implementation of carbon peak and carbon neutrality projects were delineated, and targeted measures for carbon reduction and sink increase were proposed. This study provides a new perspective for implementing territorial spatial planning in Chinese urban agglomerations and can aid the government in formulating a reasonable low-carbon-oriented regional planning policy. Full article
(This article belongs to the Section Land Planning and Landscape Architecture)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Geographical location of the study area.</p>
Full article ">Figure 2
<p>Workflow of this study.</p>
Full article ">Figure 3
<p>Land use patterns under the (<b>a</b>) ND scenario and (<b>b</b>) EP scenario in 2035.</p>
Full article ">Figure 4
<p>Spatial distributions of carbon emissions under the (<b>a</b>) ND scenario and (<b>b</b>) EP scenario in 2035.</p>
Full article ">Figure 5
<p>ESC under the (<b>a</b>) ND scenario and (<b>b</b>) EP scenario in 2035.</p>
Full article ">Figure 6
<p>Carbon emission networks under the LCD scenario in the BTH urban agglomeration.</p>
Full article ">Figure 7
<p>Carbon emission network in the BTH urban agglomeration: (<b>a</b>) indegree centrality, (<b>b</b>) outdegree centrality, (<b>c</b>) betweenness centrality, (<b>d</b>) out-closeness centrality, and (<b>e</b>) in-closeness centrality.</p>
Full article ">Figure 8
<p>Flowchart of carbon balance zoning planning.</p>
Full article ">Figure 9
<p>Flowchart of key carbon balance and county planning.</p>
Full article ">Figure 10
<p>Carbon balance zoning and key county planning for the BTH urban agglomeration in 2035 under the LCD scenario.</p>
Full article ">Figure 11
<p>Key regional proposals for emission peak and carbon neutrality engineering for the BTH urban agglomeration in 2035 under the LCD scenario.</p>
Full article ">Figure 12
<p>A low-carbon-oriented urban agglomeration planning framework.</p>
Full article ">
18 pages, 8984 KiB  
Article
Factors Influencing Ephemeral Gullies at the Regional Scale: Formation and Density
by Lei Ma, Chunmei Wang, Yuan Zhong, Guowei Pang, Lei Wang, Yongqing Long, Qinke Yang and Bingzhe Tang
Land 2024, 13(4), 553; https://doi.org/10.3390/land13040553 - 20 Apr 2024
Viewed by 880
Abstract
Ephemeral gully (EG) erosion is an important type of water erosion. Understanding the spatial distribution of EGs and other influencing factors at a regional scale is crucial for developing effective soil and water management strategies. Unfortunately, this area has not been sufficiently studied. [...] Read more.
Ephemeral gully (EG) erosion is an important type of water erosion. Understanding the spatial distribution of EGs and other influencing factors at a regional scale is crucial for developing effective soil and water management strategies. Unfortunately, this area has not been sufficiently studied. The present study visually interpreted the EGs based on Google Earth images in 137 small watersheds uniformly distributed in the Loess Plateau, compared them with measured results, and analyzed the factors influencing EG formation and density using GeoDetector. The results showed that visually interpreting EGs from Google Earth images was suitable for EG regional studies. Out of the 137 small watersheds, 33.6% had EG occurrence with an average density of 3.41 km/km2. Rainfall (R) and slope gradient (S) were the primary factors influencing the formation of EGs, while the area proportion of sloping farmland (APSF) and soil erodibility (K) were the main factors affecting EG density. The interaction of dual factors had a greater influence compared to single factors, with the interaction between S and Normalized Difference Vegetation Index (NDVI) having the greatest impact on EG formation and the interaction between K and NDVI on EG density. Although natural forces significantly influence whether EGs can form in a specific area, human activities greatly affect the density of the gullies that develop. This underscores the importance of proper land management in controlling gully erosion. These findings could provide theoretical support for EG prediction models and a scientific basis for soil and water loss control strategies at the regional scale. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic diagram of the study area. (<b>a</b>) study area; (<b>b</b>) small watershed unit; (<b>c</b>) rectangular unit.</p>
Full article ">Figure 2
<p>Example of ephemeral gully interpretation.</p>
Full article ">Figure 3
<p>Overall methodology flowchart.</p>
Full article ">Figure 4
<p>The frequency of the relative error of ephemeral gully length. (<b>a</b>) Relative error of single EG. (<b>b</b>) Pareto Chart of the Relative Error in EGs Length.</p>
Full article ">Figure 5
<p>Spatial distribution of ephemeral gully density.</p>
Full article ">Figure 6
<p>The formation of EGs is influenced by several main factors. (<b>a</b>) Spatial distribution of EGs with different rainfall. (<b>b</b>) The proportion of EG sample units within the sample units with different rainfall. (<b>c</b>) Spatial distribution of EGs with different slope gradient. (<b>d</b>) The proportion of EG sample units within the sample units with different slope gradient.</p>
Full article ">Figure 7
<p>Results of interaction detection of EGs formation driving factor.</p>
Full article ">Figure 8
<p>The density of EGs is influenced by several main factors. (<b>a</b>) Spatial distribution of EG density with different proportions of sloping farmland. (<b>b</b>) Relationship between the area proportion of slopping farmland and density of EGs. (<b>c</b>) Spatial distribution of EG density with different soil erodibility. (<b>d</b>) Relationship between soil erodibility and density of EGs.</p>
Full article ">Figure 9
<p>Results of interaction detection of EG density driving factor.</p>
Full article ">
16 pages, 4340 KiB  
Article
Measuring Deprivation and Micro-Segregation in Greek Integrated Sustainable Urban Development Strategies: Time to Apply a Common Method?
by Nikos Karadimitriou and Stavros Spyrellis
Land 2024, 13(4), 552; https://doi.org/10.3390/land13040552 - 20 Apr 2024
Cited by 1 | Viewed by 1149
Abstract
During the Programming Period 2014–2020, dozens of Greek cities drafted Integrated Territorial Investment programmes, based on Integrated Sustainable Urban Development Strategies (ITI SUDs). The Strategies justified the selection of intervention and activity areas using socio-economic analysis. The parameters of that analysis, as specified [...] Read more.
During the Programming Period 2014–2020, dozens of Greek cities drafted Integrated Territorial Investment programmes, based on Integrated Sustainable Urban Development Strategies (ITI SUDs). The Strategies justified the selection of intervention and activity areas using socio-economic analysis. The parameters of that analysis, as specified by the National Coordination Authority, reflected the socio-economic and functional parameters highlighted in the relevant EU regulations. This paper uses a recently published methodology in order to estimate and map deprivation in Greek cities with over 100,000 inhabitants, and compares the results with the activity areas identified in the ITI SUDs of those cities. The paper also makes an estimation of the potential for micro-segregation in deprived areas, in an effort to uncover the links between deprivation, built form and social composition at the micro-scale. The analysis shows that deprivation is comparatively more pronounced in Athens and Thessaloniki, and that the use of a common methodology to measuring deprivation, but with customized measurement scales, could support a more targeted allocation of urban policy resources. On the other hand, micro-segregation seems to be a factor worth exploring only in Athens and Thessaloniki, and not in Patra, Larissa, Volos and Heraklion, where the building stock in areas of deprivation is mostly low-rise. Full article
(This article belongs to the Special Issue Urban Micro-Segregation)
Show Figures

Figure 1

Figure 1
<p>The location of the six cities.</p>
Full article ">Figure 2
<p>GDI for Athens (2011), common measurement scale (<b>left</b>) and city measurement scale (<b>right</b>).</p>
Full article ">Figure 3
<p>GDI for Thessaloniki (2011), common measurement scale (<b>left</b>) and city measurement scale (<b>right</b>).</p>
Full article ">Figure 4
<p>GDI for Patra (2011), common measurement scale (<b>left</b>) and city measurement scale (<b>right</b>).</p>
Full article ">Figure 5
<p>GDI for Heraklion (2011), common measurement scale (<b>left</b>) and city measurement scale (<b>right</b>).</p>
Full article ">Figure 6
<p>GDI for Larissa (2011), common measurement scale (<b>left</b>) and city measurement scale (<b>right</b>).</p>
Full article ">Figure 7
<p>GDI for Volos (2011), common measurement scale (<b>left</b>) and city measurement scale (<b>right</b>).</p>
Full article ">
12 pages, 3034 KiB  
Article
Using Automated Machine Learning for Spatial Prediction—The Heshan Soil Subgroups Case Study
by Peng Liang, Cheng-Zhi Qin and A-Xing Zhu
Land 2024, 13(4), 551; https://doi.org/10.3390/land13040551 - 20 Apr 2024
Viewed by 822
Abstract
Recently, numerous spatial prediction methods with diverse characteristics have been developed. Selecting an appropriate spatial prediction method, along with its data preprocessing and parameter settings, presents a challenging task for many users, especially for non-experts. This paper addresses this challenge by exploring the [...] Read more.
Recently, numerous spatial prediction methods with diverse characteristics have been developed. Selecting an appropriate spatial prediction method, along with its data preprocessing and parameter settings, presents a challenging task for many users, especially for non-experts. This paper addresses this challenge by exploring the potential of automated machine learning method proposed in artificial intelligent domain to automatically determine the most suitable method among various machine learning methods. As a case study, the automated machine learning method was applied to predict the spatial distribution of soil subgroups in Heshan farm. A total of 110 soil samples and 10 terrain variables were utilized in the designed experiments. To evaluate the performance, the proposed method was compared to each machine learning method with default parameters values or parameters determined by expert knowledge. The results showed that the proposed method typically achieved higher accuracy scores than the two alternative methods. This suggests that automated machine learning performs effectively in scenarios where numerous machine learning methods are available and offers practical utility in reducing the dependence on users’ expertise in spatial prediction. However, a more robust automated framework should be developed to encompass a broader range of spatial prediction methods, such as spatial statistic methods, rather than only focusing on machine learning methods. Full article
Show Figures

Figure 1

Figure 1
<p>The Heshan study area.</p>
Full article ">Figure 2
<p>Boxplot of accuracy scores for ML methods determined by different approaches.</p>
Full article ">Figure 3
<p>Boxplot of accuracy scores for RF which determined by default, expert and AutoML, respectively.</p>
Full article ">Figure 4
<p>Boxplot of accuracy scores for the determined workflows by AutoML.</p>
Full article ">Figure 5
<p>The proportion of the ML methods selected by AutoML for the single workflows in 3-fold cross-validations with 30 repeats.</p>
Full article ">Figure 6
<p>The proportion of the ML methods selected by AutoML to construct the ensembles in 30 repetitive 3-fold cross-validations.</p>
Full article ">Figure 7
<p>The spatial distribution of soil subgroups generated by AutoML. (<b>a</b>,<b>b</b>) represent the maps with the best and worst evaluation accuracy scores by single workflow, respectively. (<b>c</b>,<b>d</b>) stand for the maps with the best and worst evaluation accuracy scores by the ensemble, respectively.</p>
Full article ">
26 pages, 4060 KiB  
Article
Impacts of Land Use Conversion on Soil Erosion in the Urban Agglomeration on the Northern Slopes of the Tianshan Mountains
by Ziqi Guo, Zhaojin Yan, Rong He, Hui Yang, Hui Ci and Ran Wang
Land 2024, 13(4), 550; https://doi.org/10.3390/land13040550 - 20 Apr 2024
Cited by 3 | Viewed by 1119
Abstract
The serious problem of soil erosion not only has a profound impact on people’s lives but also results in a series of ecological and environmental challenges. To determine the impact of changes in land use type on soil erosion in the urban agglomeration [...] Read more.
The serious problem of soil erosion not only has a profound impact on people’s lives but also results in a series of ecological and environmental challenges. To determine the impact of changes in land use type on soil erosion in the urban agglomeration on the northern slopes of the Tianshan Mountains, this study commences by employing the InVEST-SDR (integrated valuation of ecosystem services and tradeoffs–sediment delivery ratio) model to calculate soil erosion levels spanning from 2000 to 2020. Subsequently, it forecasts land use and land cover (LULC) conditions for the year 2030 under three scenarios: Q1 (natural development), Q2 (ecological protection), and Q3 (economic priority). This projection is accomplished through the integration of a coupled Markov chain and multi-objective planning model (MOP) alongside patch-generating land use simulation (PLUS) models. Ultimately, based on these outcomes, the study predicts soil erosion levels for the year 2030. There has been a consistent decline in soil erosion from 2000 to 2020 with high-intensity erosion concentrated in the Tianshan Mountain region. Grasslands, glaciers, and permafrost are identified as the most erosion-prone land types in the study area, with forests exhibiting the highest capacity for soil retention. Converting from grassland and barren land to forest within the same area results in a substantial reduction in soil erosion, specifically by 27.3% and 46.3%, respectively. Furthermore, the transformation from barren land to grassland also leads to a noteworthy 19% decrease in soil erosion. Over the past two decades, the study area has witnessed a significant decline in the area of grasslands, with a notable shift towards barren and impervious surfaces due to economic development and mining activities. The three predicted scenarios depict significant expansion towards barren land, grassland, and impervious area, respectively. Soil erosion decreases under different shared socio-economic pathway (SSP) scenarios relative to 2020. There is an increase in soil erosion in the Q1 scenario and in the Q3 scenario, whereas the amount of soil erosion in the Q2 scenario exhibits a continued decrease when only the effect of land change on soil erosion is considered. Persistently rapid economic development can exacerbate soil erosion problems, underscoring the need to find a balance between economic growth and ecological conservation. As economic expansion slows down, greater emphasis should be placed on environmental protection to maintain ecological stability. Full article
Show Figures

Figure 1

Figure 1
<p>Panorama of the urban agglomeration on the northern slopes of the Tianshan Mountains, China. The map vector boundary was obtained from the Ministry of Natural Resources: GS(2020)4619 and no modification has been made to the base map boundary.</p>
Full article ">Figure 2
<p>Flowchart of the Methodology.</p>
Full article ">Figure 3
<p>Factors Driving Land Use Expansion Change.</p>
Full article ">Figure 4
<p>Soil erosion map of the urban agglomeration on the northern slopes of the Tianshan Mountains.</p>
Full article ">Figure 5
<p>Rainfall map for 2000–2020.</p>
Full article ">Figure 6
<p>LULC in Urban Agglomerations on the Northern Slopes of Tianshan Mountains.</p>
Full article ">Figure 7
<p>Multi-scenario LULC changes between 2020 and 2030 (in hectares).</p>
Full article ">Figure 8
<p>Predicted soil erosion for each scenario.</p>
Full article ">Figure 9
<p>Predicted precipitation.</p>
Full article ">
22 pages, 3750 KiB  
Review
Research Progress in the Field of Peatlands in 1990–2022: A Systematic Analysis Based on Bibliometrics
by Jianzong Shi, Wenhao Liu, Ren Li, Xiaodong Wu, Tonghua Wu, Lin Zhao, Junjie Ma, Shenning Wang, Yao Xiao, Guojie Hu, Yongliang Jiao, Dong Wang, Xianhua Wei, Peiqing Lou and Yongping Qiao
Land 2024, 13(4), 549; https://doi.org/10.3390/land13040549 - 19 Apr 2024
Viewed by 1302
Abstract
Peatlands are major natural carbon pool in terrestrial ecosystems globally and are essential to a variety of fields, including global ecology, hydrology, and ecosystem services. Under the context of climate change, the management and conservation of peatlands has become a topic of international [...] Read more.
Peatlands are major natural carbon pool in terrestrial ecosystems globally and are essential to a variety of fields, including global ecology, hydrology, and ecosystem services. Under the context of climate change, the management and conservation of peatlands has become a topic of international concern. Nevertheless, few studies have yet systematized the overall international dynamics of existing peatland research. In this study, based on an approach integrating bibliometrics and a literature review, we systematically analyzed peatland research from a literature perspective. Alongside traditional bibliometric analyses (e.g., number of publications, research impact, and hot areas), recent top keywords in peatland research were found, including ‘oil palm’, ‘tropical peatland’, ‘permafrost’, and so on. Furthermore, six hot topics of peatland research were identified: (1) peatland development and the impacts and degradations, (2) the history of peatland development and factors of formation, (3) chemical element contaminants in peatlands, (4) tropical peatlands, (5) peat adsorption and its humic acids, and (6) the influence of peatland conservation on the ecosystem. In addition, this review found that the adverse consequences of peatland degradation in the context of climate change merit greater attention, that peatland-mapping techniques suitable for all regions are lacking, that a unified global assessment of carbon stocks in peatlands urgently needs to be established, spanning all countries, and that a reliable system for assessing peatland-ecosystem services needs to be implemented expeditiously. In this study, we argued that enhanced integration in research will bridge knowledge gaps and facilitate the systematic synthesis of peatlands as complex systems, which is an imperative need. Full article
Show Figures

Figure 1

Figure 1
<p>Research workflow of this study.</p>
Full article ">Figure 2
<p>Total papers per year and publication growth rate from 1990 to 2022.</p>
Full article ">Figure 3
<p>Countries’ network visualization in terms of co-occurrence links. Different colors represent different clusters, and countries of the same color collaborate more closely with each other.</p>
Full article ">Figure 4
<p>Organizations’ network visualization in terms of co-occurrence links. Different colors represent different clusters, and organizations of the same color collaborate more closely with each other.</p>
Full article ">Figure 5
<p>Top 10 research areas of peatland publications.</p>
Full article ">Figure 6
<p>The keyword trends of peatland studies based on the Avg. pub. year.</p>
Full article ">Figure 7
<p>Thematic clustering of keywords including six clusters.</p>
Full article ">
22 pages, 3965 KiB  
Article
Evolution Process of Urban Industrial Land Redevelopment in China: A Perspective of Original Land Users
by Fang He, Yuan Yi and Yuxuan Si
Land 2024, 13(4), 548; https://doi.org/10.3390/land13040548 - 19 Apr 2024
Cited by 1 | Viewed by 787
Abstract
The crucial role of urban industrial land redevelopment in sustainable urban renewal has garnered widespread attention. While some scholars have explored the interest game among stakeholders in industrial land redevelopment, they primarily focus on the government-led model. Moreover, there remains a research gap [...] Read more.
The crucial role of urban industrial land redevelopment in sustainable urban renewal has garnered widespread attention. While some scholars have explored the interest game among stakeholders in industrial land redevelopment, they primarily focus on the government-led model. Moreover, there remains a research gap concerning the impact of government intervention on the redevelopment of industrial land. This article utilizes evolutionary game theory to investigate the interest game between local governments and original land users in the model of urban industrial land redevelopment dominated by original land users. We establish evolutionary game models considering incentives and the combination of incentives and regulations, explore the interest balance strategy, and examine the impact of positive incentives and mandatory regulations on industrial land redevelopment. Furthermore, we employ a numerical simulation to unveil the impact of initial strategies and parameter adjustments on game strategy. The research results are as follows: (1) Under the original land user-led redevelopment model, only two evolutionary stability strategies exist: either the original land users implement industrial land redevelopment with positive responses from local governments, or neither party advances the process. (2) Government intervention is pivotal in facilitating the redevelopment of inefficient industrial land as economic subsidies and punitive measures motivate more participants to adopt proactive strategies. (3) The increase in government support positively correlates with the likelihood of industrial land redevelopment implementation by original land users. (4) The interests and costs of original land users emerge as crucial parameters influencing strategic decisions. This study enriches the understanding of the interests of core participants in industrial land redevelopment and provides valuable insights for sustainable urban renewal. Full article
Show Figures

Figure 1

Figure 1
<p>The dynamic evolution path of equilibrium points in Scenario 2.</p>
Full article ">Figure 2
<p>Numerical simulation of Scenario 2 in the game model considering subsidies.</p>
Full article ">Figure 3
<p>Numerical simulation of Scenario 2 in the game model considering subsidies and penalties.</p>
Full article ">Figure 4
<p>Diagram on the impact of different initial government strategies. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>y</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msub> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>. (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>y</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msub> <mo>=</mo> <mn>0.7</mn> </mrow> </semantics></math>.</p>
Full article ">Figure 5
<p>Impact of changes in <math display="inline"><semantics> <mrow> <mi>R</mi> <mo>′</mo> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>x</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>y</mi> </mrow> </semantics></math>. (<b>a</b>) Impact of changes in <math display="inline"><semantics> <mrow> <msup> <mrow> <mi>R</mi> </mrow> <mrow> <mi mathvariant="normal">′</mi> </mrow> </msup> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>x</mi> </mrow> </semantics></math>. (<b>b</b>) Impact of changes in <math display="inline"><semantics> <mrow> <msup> <mrow> <mi>R</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msup> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>y</mi> </mrow> </semantics></math>.</p>
Full article ">Figure 6
<p>Impact of changes in <math display="inline"><semantics> <mrow> <mi>R</mi> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>x</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>y</mi> </mrow> </semantics></math>. (<b>a</b>) Impact of changes in <math display="inline"><semantics> <mrow> <mi>R</mi> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>x</mi> </mrow> </semantics></math>. (<b>b</b>) Impact of changes in <math display="inline"><semantics> <mrow> <mi>R</mi> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>y</mi> </mrow> </semantics></math>.</p>
Full article ">Figure 7
<p>Impact of changes in <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>C</mi> </mrow> <mrow> <mi mathvariant="normal">E</mi> </mrow> </msub> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>x</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>y</mi> </mrow> </semantics></math>. (<b>a</b>) Impact of changes in <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>C</mi> </mrow> <mrow> <mi mathvariant="normal">E</mi> </mrow> </msub> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>x</mi> </mrow> </semantics></math>. (<b>b</b>) Impact of changes in <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>C</mi> </mrow> <mrow> <mi mathvariant="normal">E</mi> </mrow> </msub> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>y</mi> </mrow> </semantics></math>.</p>
Full article ">Figure 8
<p>Impact of changes in <math display="inline"><semantics> <mrow> <mi>β</mi> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>x</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>y</mi> </mrow> </semantics></math>. (<b>a</b>) Impact of changes in <math display="inline"><semantics> <mrow> <mi>β</mi> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>x</mi> </mrow> </semantics></math>. (<b>b</b>) Impact of changes in <math display="inline"><semantics> <mrow> <mi>β</mi> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>y</mi> </mrow> </semantics></math>.</p>
Full article ">Figure 9
<p>Impact of changes in <math display="inline"><semantics> <mrow> <mi>F</mi> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>x</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>y</mi> </mrow> </semantics></math>. (<b>a</b>) Impact of changes in <math display="inline"><semantics> <mrow> <mi>F</mi> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>x</mi> </mrow> </semantics></math>. (<b>b</b>) Impact of changes in <math display="inline"><semantics> <mrow> <mi>F</mi> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>y</mi> </mrow> </semantics></math>.</p>
Full article ">
22 pages, 26163 KiB  
Article
Spatiotemporal Analysis of Soil Quality Degradation and Emissions in the State of Iowa (USA)
by Elena A. Mikhailova, Hamdi A. Zurqani, Lili Lin, Zhenbang Hao, Christopher J. Post, Mark A. Schlautman and Gregory C. Post
Land 2024, 13(4), 547; https://doi.org/10.3390/land13040547 - 19 Apr 2024
Viewed by 1074
Abstract
The concept of soil quality (SQ) is defined as the soil's capacity to function, which is commonly assessed at the field scale. Soil quality is composed of inherent (soil suitability) and dynamic (soil health, SH) SQ, which can also be analyzed using geospatial [...] Read more.
The concept of soil quality (SQ) is defined as the soil's capacity to function, which is commonly assessed at the field scale. Soil quality is composed of inherent (soil suitability) and dynamic (soil health, SH) SQ, which can also be analyzed using geospatial tools as a SQ continuum (SQC). This study proposes an innovative spatiotemporal analysis of SQ degradation and emissions from land developments using the state of Iowa (IA) in the United States of America (USA) as a case study. The SQ degradation was linked to anthropogenic soil (SD) and land degradation (LD) in the state. More than 88% of land in IA experienced anthropogenic LD primarily due to agriculture (93%). All six soil orders were subject to various degrees of anthropogenic LD: Entisols (75%), Inceptisols (94%), Histosols (59%), Alfisols (79%), Mollisols (93%), and Vertisols (98%). Soil and LD have primarily increased between 2001 and 2016. In addition to agricultural LD, there was also SD/LD caused by an increase in developments often through urbanization. All land developments in IA can be linked to damages to SQ, with 8385.9 km2 of developed area, causing midpoint total soil carbon (TSC) losses of 1.7 × 1011 kg of C and an associated midpoint of social cost of carbon dioxide emissions (SC-CO2) of $28.8B (where B = billion = 109, USD). More recently developed land area (398.5 km2) between 2001 and 2016 likely caused the midpoint loss of 8.0 × 109 kg of C and a corresponding midpoint of $1.3B in SC-CO2. New developments are often located near urban areas, for example, near the capital city of Des Moines, and other cities (Sioux City, Dubuque). Results of this study reveal several different kinds of SQ damage from developments: loss of potential for future C sequestration in soils, soil C loss, and “realized” soil C social costs (SC-CO2). The state of IA has very limited potential land (2.0% of the total state area) for nature-based solutions (NBS) to compensate for SD and LD. The results of this study can be used to support pending soil health-related legislation in IA and monitoring towards achieving the Sustainable Development Goals (SDGs) developed by the United Nations (UN) by providing a landscape-level perspective on LD to focus field-level initiatives to reduce soil loss and improve SQ. Future technological innovations will provide higher spatial and temporal remote sensing data that can be fused with field-level direct sensing to track SH and SQ changes. Full article
Show Figures

Figure 1

Figure 1
<p>Soil quality is composed of inherent and dynamic soil quality (adapted from De la Rosa and Sobral, 2008 [<a href="#B5-land-13-00547" class="html-bibr">5</a>]).</p>
Full article ">Figure 2
<p>Soil map for the state of Iowa (IA), USA, (40° 36′ N to 43° 30′ N and 89° 5′ W to 96° 31′ W) developed using the SSURGO spatial soils database [<a href="#B14-land-13-00547" class="html-bibr">14</a>] and ecoregions [<a href="#B15-land-13-00547" class="html-bibr">15</a>]. It shows the spatial distribution of soil orders with different inherent soil qualities (soil suitability). The inherent soil quality of IA is dominated by soil orders of Mollisols (60.9%) and Alfisols (23.9%), which are often inherently high-fertility soils important for agriculture.</p>
Full article ">Figure 3
<p>Soil quality is concisely defined as the soil’s capacity to function [<a href="#B5-land-13-00547" class="html-bibr">5</a>], which can be understood as the intersection of land cover and/or land use/land cover (LULC) change and soil type and over scale and time (adapted from Karlen et al., 2019 [<a href="#B25-land-13-00547" class="html-bibr">25</a>]). The SQ continuum is a series of values that differ with LULC and soil type.</p>
Full article ">Figure 4
<p>Concept of soil quality trends with time (adapted from Seybold et al., 1998 [<a href="#B26-land-13-00547" class="html-bibr">26</a>]).</p>
Full article ">Figure 5
<p>State of Iowa (IA) (USA) 2016 land cover map (40° 36′ N to 43° 30′ N and 89° 5′ W to 96° 31′ W) (using data from MRLC [<a href="#B31-land-13-00547" class="html-bibr">31</a>]) showing dynamic soil quality (soil health).</p>
Full article ">Figure 6
<p>Anthropogenically degraded land proportion (%) by county in the state of Iowa (IA) (USA) in 2016. The proportion of land subject to anthropogenic degradation was calculated as a sum of developed land (developed, open space; developed, high intensity; developed, medium intensity; developed, low intensity), agriculture (cultivated crops, and hay/pasture), and barren land.</p>
Full article ">Figure 7
<p>Relationship between the average carbon index (CI) of mineral soils for each county in Iowa [<a href="#B36-land-13-00547" class="html-bibr">36</a>] and the proportion of land degradation (%) in that county (determined in this study).</p>
Full article ">Figure 8
<p>Soil quality (SQ) damage from soil carbon (C) loss with emissions associated with past land developments (through 2016) in Iowa (IA) (USA). Note: B = billion = 10<sup>9</sup>.</p>
Full article ">Figure 9
<p>Damages to soil quality (SQ) from the loss of land for potential soil carbon (C) sequestration from past developments (through 2016) in Iowa (IA) (USA).</p>
Full article ">Figure 10
<p>Damage to soil quality (SQ) from emissions can be measured as “realized” social costs of soil carbon (C) (SC-CO<sub>2</sub>) from past developments (prior and through 2016) in the state of Iowa (IA) (USA). Note: M = million = 10<sup>6</sup>; B = billion = 10<sup>9</sup>.</p>
Full article ">Figure 11
<p>Dallas County, Iowa (IA), USA. Areas that changed land cover between 2001 and 2016 indicate potential damage to soil quality, notably in the area adjacent to the city of Des Moines.</p>
Full article ">
15 pages, 4533 KiB  
Article
Temporal Variation in Soil Resistance to Rill Erosion in Cropland of the Dry—Hot Valley Region, Southwest China
by Yi Wang, Xiaosong Qin, Yaping Kong, Dongdong Hou and Ping Ren
Land 2024, 13(4), 546; https://doi.org/10.3390/land13040546 - 19 Apr 2024
Cited by 1 | Viewed by 816
Abstract
In croplands, soil erosion resistance varies with both natural processes and human disturbances. To clarify the temporal variation in soil erosion resistance, nine cropland plots with three treatments (continuous fallow, fallow after tillage and tillage with corn) were established in the dry–hot valley [...] Read more.
In croplands, soil erosion resistance varies with both natural processes and human disturbances. To clarify the temporal variation in soil erosion resistance, nine cropland plots with three treatments (continuous fallow, fallow after tillage and tillage with corn) were established in the dry–hot valley region of China. A total of 144 field runoff simulation experiments were conducted from May to October to measure the soil detachment rate (Dc), rill erodibility (Kr) and critical shear stress (τc). The results revealed that the natural dry—wet alternation had little influence on the continuous-fallowed soil erosion resistance. On the other hand, the tillage disturbance that occurred in May sharply increased the Dc and Kr to 2.24 and 3 times that of the continuous-fallow treatment, respectively. Then, the erosion resistance could be enhanced with surface consolidation for the fallow-after-tillage treatment. However, after three months of fallow, the Kr was still 89.5% of the fresh tilled soil. In contrast, crop growth could significantly improve aggregate stability and reduce the Kr to 38.2% in August and even further to 23.7% in October compared to the fresh tilled soil. It could be concluded that crop growth is more efficient in enhancing erosion resistance than the mechanical effect. The above results would benefit from the accurate modeling of cropland soil erosion dynamics and guide agricultural management in dry–hot climate regions. Full article
(This article belongs to the Section Soil-Sediment-Water Systems)
Show Figures

Figure 1

Figure 1
<p>Study area and the experimental design. (<b>a</b>) the location of the study area, (<b>b</b>) field plots in Google Maps satellite image, (<b>c</b>) field plots of three different treatments, (<b>d</b>) the design of the runoff simulation experiment.</p>
Full article ">Figure 2
<p>The average monthly temperature and precipitation in the study area.</p>
Full article ">Figure 3
<p>Temporal variation in soil detachment rates of the different treatments.</p>
Full article ">Figure 4
<p>Average soil detachment rates summarized for different slope gradients. Different letters indicate significant differences within the three treatments at the <span class="html-italic">p</span> &lt; 0.05 level.</p>
Full article ">Figure 5
<p>Soil detachment rate dynamics during the experimental process.</p>
Full article ">
20 pages, 3859 KiB  
Article
Insights from 30 Years of Land Use/Land Cover Transitions in Jakarta, Indonesia, via Intensity Analysis
by Faizal Rachman, Jinliang Huang, Xiongzhi Xue and Muh Aris Marfai
Land 2024, 13(4), 545; https://doi.org/10.3390/land13040545 - 19 Apr 2024
Cited by 1 | Viewed by 1021
Abstract
Here, we assess land use/land cover (LULC) transitions over the last 30 years in Jakarta, Indonesia. Land cover maps were prepared for 1990, 1995, 2000, 2005, 2010, 2015, and 2020 using seven categories of Landsat satellite image: bare land, built-up, cropland, green area, [...] Read more.
Here, we assess land use/land cover (LULC) transitions over the last 30 years in Jakarta, Indonesia. Land cover maps were prepared for 1990, 1995, 2000, 2005, 2010, 2015, and 2020 using seven categories of Landsat satellite image: bare land, built-up, cropland, green area, mangrove, water body, and pond. LULC changes were assessed through intensity analyses at the interval and transition levels. LULC changes were initially rapid (1990–1995) and then more gradual (1995–2000, 2000–2005, and 2005–2010). Unlike in previous intervals, annual changes were uniformly distributed over time in 2010–2015 and 2015–2020. Driven by high population and economic growth, built-up land was identified as an active gainer in all intervals except 2010–2015. Alongside built-up areas, cropland was the main supplier of other categories, including bare land, pond, built-up, and green areas. The largest transition area occurred in pond and green areas during 2005–2010 and in built-up land during 2015–2020. High demand for built-up land was observed in land changes driven by high population growth triggered by economic necessity. Economic and population growth exhibited a positive correlation (R2 = 0.78, t = 9.996). This study elucidates spatiotemporal LULC transition patterns over 30 years in a rapidly growing city. Full article
Show Figures

Figure 1

Figure 1
<p>Maps showing the study area of Jakarta Special Province, Indonesia.</p>
Full article ">Figure 2
<p>Overall process of the study.</p>
Full article ">Figure 3
<p>Thorough procedure of land use classification in this study.</p>
Full article ">Figure 4
<p>Structure of the transition pattern used in this study [<a href="#B30-land-13-00545" class="html-bibr">30</a>].</p>
Full article ">Figure 5
<p>Maps of (<b>a</b>) LULC categories, (<b>b</b>) losses, and (<b>c</b>) gains in Jakarta over different time intervals.</p>
Full article ">Figure 6
<p>Rates of LULC changes in different interval levels and annual changes in the study area.</p>
Full article ">Figure 7
<p>(<b>a</b>). Transition pattern of year 1990–1995; (<b>b</b>). Transition pattern of year 1995–2000; (<b>c</b>). Transition pattern of year 2000–2005; (<b>d</b>). Transition pattern of year 2005–2010; (<b>e</b>). Transition pattern of year 2010–2015; (<b>f</b>). Transition pattern of year 2015–2020. Transition pattern for six time interval of LULC changes in Jakarta from 1990 to 2020. Readers should look at the gradient color to have an understanding of the deviation between transition intensity with the transition intensity uniform column, where the red is targeting, and blue is avoiding.</p>
Full article ">Figure 8
<p>Gross domestic product and population growth of Jakarta during 1990–2020 [<a href="#B58-land-13-00545" class="html-bibr">58</a>].</p>
Full article ">
3 pages, 149 KiB  
Editorial
Public Spaces: Socioeconomic Challenges
by Teresa de Noronha
Land 2024, 13(4), 544; https://doi.org/10.3390/land13040544 - 19 Apr 2024
Viewed by 616
Abstract
This Special Issue, entitled ‘Public Spaces: Socioeconomic Challenges’ considers the concept of general well-being from the point of view of collective achievements and/or external conditions that can favorably impact the individual when implemented within an urban structure [...] Full article
(This article belongs to the Special Issue Public Spaces: Socioeconomic Challenges)
21 pages, 9048 KiB  
Article
Trends, Drivers, and Land Use Strategies for Facility Agricultural Land during the Agricultural Modernization Process: Evidence from Huzhou City, China
by Yun Chen, Zhifeng Wang, Kaijiang You, Congmou Zhu, Ke Wang, Muye Gan and Jing Zhang
Land 2024, 13(4), 543; https://doi.org/10.3390/land13040543 - 18 Apr 2024
Viewed by 1202
Abstract
Facility agriculture is an important initiative to adopt an all-encompassing approach to food and build a diversified food supply system. Understanding the evolution of facility agricultural land and the factors that drive it can contribute to the development of scientifically strategic agricultural planning [...] Read more.
Facility agriculture is an important initiative to adopt an all-encompassing approach to food and build a diversified food supply system. Understanding the evolution of facility agricultural land and the factors that drive it can contribute to the development of scientifically strategic agricultural planning and agricultural modernization. Therefore, this paper constructs a “situation-structure-behavior-value” theoretical framework; quantifies the relevant driving factors (physical, proximal, and socioeconomic) and their impacts on the development and layout of facility agriculture land by using a multivariate logistic regression model; and provides a strategy for optimizing land use. The results showed that the area of facility agriculture in Huzhou is rapidly expanding. Regarding drivers, facility agricultural land tends to be located in areas with higher slopes according to plot selection. Facility agriculture is more likely to develop in plots with convenient transportation and closer proximity to markets. At the economic level, economic efficiency, agricultural resource superiority, and policies significantly impact facility agriculture expansion. Finally, we propose three land use policy options to facilitate the sustainable development of facility agriculture. This study elucidates the underlying factors driving different types of facility agricultural land and offers methodological guidance for policy support, planning, control, and optimization strategies for facility agriculture. Full article
Show Figures

Figure 1

Figure 1
<p>Evolution of land use policy for facility agriculture in China since 2007.</p>
Full article ">Figure 2
<p>The theoretical framework of value optimization for facility agricultural land.</p>
Full article ">Figure 3
<p>Location of Huzhou City (China), with transportation routes, rivers, and lake within it.</p>
Full article ">Figure 4
<p>Temporal trends (<b>a</b>) and quantity change of plots (<b>b</b>) of land for facility agriculture from 2007–2021 in Huzhou City, China.</p>
Full article ">Figure 5
<p>Spatial patterns and remote sensing image samples of different types of facility agriculture in Huzhou City, China, from 2007 to 2021.</p>
Full article ">Figure 6
<p>Center of gravity migration and kernel density for different types of facility agriculture, 2007–2021.</p>
Full article ">Figure 7
<p>Spatial hotspot map of different types of facility agricultural land.</p>
Full article ">Figure 8
<p>Facility agricultural land use transfer matrix in Huzhou City: (<b>a</b>) transfer in, (<b>b</b>) transfer out.</p>
Full article ">Figure 9
<p>The land use optimization zoning of facility agriculture in Huzhou City.</p>
Full article ">
16 pages, 1091 KiB  
Article
Drinking Poison to Quench Thirst: Local Government Land Financial Dependence and Urban Innovation Quality
by Shiying Xu, Fuqiang Yang, Qian Yang, Binbin Chang and Kun Wang
Land 2024, 13(4), 542; https://doi.org/10.3390/land13040542 - 18 Apr 2024
Viewed by 938
Abstract
Many emerging markets rely on land financing, whereby land grants are used to raise funds for the government. In the short term, land financing eases the government’s fiscal deficit and boosts regional economic development. However, the long-term implications of such behaviour have not [...] Read more.
Many emerging markets rely on land financing, whereby land grants are used to raise funds for the government. In the short term, land financing eases the government’s fiscal deficit and boosts regional economic development. However, the long-term implications of such behaviour have not been adequately discussed. This study focuses on the relationship between local government land finance dependence (LGLFD) and urban innovation quality (UIQ). We find that LGLFD significantly inhibits the improvement of UIQ, and this inhibition occurs through three main channels: changing government spending preferences, reducing financial efficiency, and deteriorating the institutional environment. Our empirical study analyses 3662 samples from 264 Chinese cities from 2003 to 2016, confirming our research hypothesis. Further research finds that there is significant heterogeneity in the effect of LGLFD on UIQ. Based on these conclusions, some policy implications are proposed. Full article
Show Figures

Figure 1

Figure 1
<p>Research pathway map.</p>
Full article ">Figure 2
<p>Placebo testing.</p>
Full article ">Figure 3
<p>Spatial distribution of cities.</p>
Full article ">
13 pages, 2405 KiB  
Article
Importance of Soil Health for Coffea spp. Cultivation from a Cooperative Society in Puebla, Mexico
by Carol Meritxell Molina-Monteleón, Amparo Mauricio-Gutiérrez, Rosalía Castelán-Vega and José Victor Tamariz-Flores
Land 2024, 13(4), 541; https://doi.org/10.3390/land13040541 - 18 Apr 2024
Viewed by 1464
Abstract
The cultivation systems of Coffea spp. in a cooperative society in Puebla, Mexico, include Rustic, Traditional Polyculture, Commercial Polyculture, Unshaded Monoculture and Shaded Monoculture. In this work, the properties of the soil were analyzed through physical, chemical and biological analyses to determine its [...] Read more.
The cultivation systems of Coffea spp. in a cooperative society in Puebla, Mexico, include Rustic, Traditional Polyculture, Commercial Polyculture, Unshaded Monoculture and Shaded Monoculture. In this work, the properties of the soil were analyzed through physical, chemical and biological analyses to determine its nutritional status. Composite sample analyses were conducted to determine physical, chemical and microbiological parameters (fungi, actinomycetes, mesophilic bacteria, nitrifying and denitrifying bacteria). Leaf nutrients were determined. Rustic was the cropping system with the highest amount of K in the soil and nutrient assimilation in the leaf (N, P, K and Fe) (p = 0.001); in addition, it had high populations of mesophilic bacteria, fungi and actinomycetes and very low nitrification and denitrification rates. The principal component analyses (PCA) (>3.25%) indicated that actinomycetes and K in soil favor the assimilation of Fe, K and P. This Coffea spp. cultivation system generated a lower impact on soil health than the rest of the systems and favored forest ecosystem conservation. Full article
(This article belongs to the Special Issue Soil Management for Soil Health)
Show Figures

Figure 1

Figure 1
<p>Sampling sites in the cooperative society, Puebla, Mexico. Cultivation methods: Unshaded Monoculture, Shaded Monoculture, Commercial Polyculture, Traditional Polyculture, and Rustic.</p>
Full article ">Figure 2
<p>Nitrification and denitrification rates by cropping system in <span class="html-italic">Coffea</span> spp. Different letters indicate significant statistical differences between cultivation systems according to the Tukey test (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 3
<p>Principal component analyses (PCA) for the five <span class="html-italic">Coffea</span> spp. cultivation systems.</p>
Full article ">Figure 4
<p>Principal component analyses (PCA) for leaf nutrients and physical, chemical and biological properties of soil. <b><sup>§</sup></b>: Nutrients in <span class="html-italic">Coffea</span> spp. leaf. CEC: Cation exchange capacity.</p>
Full article ">
25 pages, 8912 KiB  
Article
Urban Green–Blue Space Utilization and Public Perceptions Amid the COVID-19 Pandemic: Insights from Northwest China
by Yuliang Wang, Feifei Li, Dan Liu and Zilong Zhang
Land 2024, 13(4), 540; https://doi.org/10.3390/land13040540 - 18 Apr 2024
Viewed by 964
Abstract
The COVID-19 pandemic has reshaped our daily lives and the way we interact with urban green–blue spaces (UGBS), particularly in the economically challenged regions of Northwest China. Our study, utilizing surveys and social media, delves into the pandemic’s impact on UGBS engagement in [...] Read more.
The COVID-19 pandemic has reshaped our daily lives and the way we interact with urban green–blue spaces (UGBS), particularly in the economically challenged regions of Northwest China. Our study, utilizing surveys and social media, delves into the pandemic’s impact on UGBS engagement in this area, offering critical insights for urban planning amidst a global health crisis. We found a gender-balanced but preference-specific engagement in UGBS, with women and married couples in the Chengguan District of Lanzhou city showing affinity. Moreover, educational levels and proximity to academic institutions emerged as key factors influencing UGBS use, pointing to the importance of educational attainment in engagement diversity. Enhancing safety, creating child-friendly and leisure facilities for families, and designing vibrant spaces for socializing are vital, and placing UGBS near educational districts could also promote environmental awareness and scientific learning. Furthermore, the pandemic has reshaped public priorities, elevating the value of accessible, safe UGBS. This shift is evidenced by varied motivations for UGBS visits, with an emphasis on health, nature connectivity, and leisure. Women, older adults, and families, each with their distinct reasons, were drawn to UGBS for activities ranging from recreation to relaxation. Our findings advocate for the creation of multifunctional UGBS that cater to these varied interests, incorporating features such as air-purifying plants, scenic pathways, and zones for family activities, all underpinned by enhanced safety and accessibility. The study also highlights distinct transportation preferences among residents of Chengguan’s northern and southern parts, suggesting a tailored approach to urban infrastructure that accommodates pedestrian access and public transit use. To prevent overcrowding, adjusting facility hours and event timings based on peak visitation times is recommended. Moreover, improving walkways and public transport connectivity is essential not just for convenience but also for ensuring that these green spaces are equitable and financially accessible, fostering inclusive access to these essential urban areas. During the pandemic, social media revealed a growing search for spiritual fulfillment within UGBS, highlighting their importance in societal well-being and coping mechanisms. In response, there’s a compelling opportunity for UGBS to evolve by incorporating designated areas for spiritual relaxation, along with mental health support services. By actively monitoring social media feedback and trends, these spaces can adapt and refine their offerings, ensuring that they meet the community’s changing needs more effectively. Our study highlights the importance of tailoring UGBS to meet diverse community needs, especially during crises. It emphasizes creating multifunctional, accessible UGBS that reflect demographic trends, transportation habits, and public preferences, aiming to boost community resilience and well-being. Drawing from research conducted amidst a worldwide crisis, our study provides key recommendations for the future evolution of UGBS, urging the creation of inclusive environments that bolster the health and well-being of urban populations. Full article
Show Figures

Figure 1

Figure 1
<p>The distribution of three UGBS (parks) in Chenguan District, Lanzhou City.</p>
Full article ">Figure 2
<p>Public perceptions regarding the functions of UGBS during the pandemic. (Important: Imp; somewhat important: SomImp; neutral: Neu; somewhat unimportant: SomUnimp; unimportant: Unimp).</p>
Full article ">Figure 3
<p>Public perceptions regarding the conditions of UGBS during the pandemic.</p>
Full article ">Figure 4
<p>Demographic distribution of UGBS visitors: (<b>a</b>) gender, (<b>b</b>) marital status, (<b>c</b>) education level, (<b>d</b>) occupation, (<b>e</b>) income, and (<b>f</b>) residency length.</p>
Full article ">Figure 5
<p>UGBS accessibility and transportation preferences. (subfigure (<b>a</b>)—visitors’ commuting methods, (<b>b</b>)—types of destinations visited, (<b>c</b>–<b>e</b>)—park service areas accessible by walking, bicycling, and driving).</p>
Full article ">Figure 6
<p>Graphical analysis of population accessibility: (<b>a</b>–<b>c</b>) transport preferences across service areas (walking, bicycling, and driving time); (<b>d</b>–<b>f</b>) commuting time across service areas (walking, bicycling, and driving time); (<b>g</b>–<b>i</b>) staying time across service areas (walking, bicycling, and driving time); (<b>j</b>) population accessibility within service areas by different transport distances; (<b>k</b>–<b>m</b>) transport choices, commute time, and staying time within each service area, respectively.</p>
Full article ">Figure 7
<p>Temporal dynamics of CES tag networks: relationships between parks and tags during the pandemic ((<b>top left</b>) for YTP, (<b>top right</b>) for WWE, (<b>bottom left</b>) for TWP, and (<b>bottom right</b>) combines data for all three parks). Depiction of CES-related labels and study sites, with size and color signifying frequency and tag category. Colors: blue for aesthetic services; purple for historical services; orange for scientific and educational services; red for recreational services; green for spiritual services.</p>
Full article ">
21 pages, 7307 KiB  
Article
Local Perspectives on Agrosilvofishery in Peatlands: A Case Study of Perigi Village, South Sumatra, Indonesia
by Eunho Choi, Jaehui Jeong, Yustina Artati, Hyunyoung Yang, Dessy Adriani and A-Ram Yang
Land 2024, 13(4), 539; https://doi.org/10.3390/land13040539 - 18 Apr 2024
Viewed by 768
Abstract
As the need for sustainable use peatlands increases, the aim of this study is to identify ways to increase the application of agrosilvofishery as an alternative to the traditional sonor system. Herein, the researchers investigate the perception of peatland degradation and the willingness [...] Read more.
As the need for sustainable use peatlands increases, the aim of this study is to identify ways to increase the application of agrosilvofishery as an alternative to the traditional sonor system. Herein, the researchers investigate the perception of peatland degradation and the willingness to participate in agrosilvofishery among peatland residents. The researchers interviewed 228 households in Perigi Village, South Sumatra, Indonesia, and surveyed 137 peatland owners. Logistic regression analysis revealed a positive correlation between the willingness to participate in agrosilvofishery and household expenses, plans to improve peatland productivity, and knowledge regarding mixed farming in farmer and non-farmer groups. Willingness to provide labor for agrosilvofishery was positively correlated with household expenses and experience with farmer organizations. For both groups, the willingness to participate had a more substantial impact on the willingness to contribute to the agrosilvofishery financially than on the willingness to provide labor. It is imperative to consider various educational, institutional, research, and cultural factors that enable peatland agrosilvofisheries to contribute to the income and livelihood of the residents of Perigi Village. Institutional arrangements should be established, including initial capital support for restoration projects and a system involving the entire village community. This study can contribute to offering guidance for implementing agrosilvofisheries and enhance the practicality of field applications for peatland restoration. Full article
(This article belongs to the Special Issue Restoration of Tropical Peatlands: Science Policy and Practice)
Show Figures

Figure 1

Figure 1
<p>The study site for the agrosilvofishery survey in Perigi Village.</p>
Full article ">Figure 2
<p>Logistic regression study model.</p>
Full article ">
24 pages, 10653 KiB  
Article
Leveraging Reed Bed Burnings as Indicators of Wetland Conversion in Modern Greece
by Cleo Maria Gaganis, Andreas Y. Troumbis and Themistoklis Kontos
Land 2024, 13(4), 538; https://doi.org/10.3390/land13040538 - 18 Apr 2024
Viewed by 1166
Abstract
This study explores the historical occurrence of wetland ecosystems in Greece by using recurring Phragmites australis (common reed) burnings as an indicator. Phragmites australis, a plant closely associated with wetlands, provides excellent insights into wetland distribution. We establish a substantial association between [...] Read more.
This study explores the historical occurrence of wetland ecosystems in Greece by using recurring Phragmites australis (common reed) burnings as an indicator. Phragmites australis, a plant closely associated with wetlands, provides excellent insights into wetland distribution. We establish a substantial association between reed fires and historical wetland existence in Greece using geographical and statistical analysis, with these fires exhibiting remarkable constancy across time. Using Corine land-cover (CLC) data, we extend our analysis into land-use dynamics, demonstrating that places with the highest reed-bed-fire rates were originally wetlands, particularly those converted into permanent irrigated land and areas with complex agriculture patterns. We find spatial commonalities between reed fires and past wetland existence by analyzing fire occurrence across three main categories: reed fires, agricultural land fires, and grassland fires. Historical records of wetland conversion into agricultural land (or land reclamation works) in locations such as Yianitsa and Kopaida give context to our findings. Visualizations confirm the clustering of reed fires around these converted agricultural regions. In summary, our study offers a unique indicator based on Phragmites australis burnings that can be used to identify previous wetland-type ecosystems, with Mediterranean-wide implications. Despite data constraints, this study adds to the conversation about wetland preservation and sustainable land-use management. Full article
Show Figures

Figure 1

Figure 1
<p>Abiotic and biotic conditions in Greece are suitable for reed beds and, indirectly, reed fire burning. (<b>a</b>) The hydrographic network of Greece (4th degree class) <a href="https://geodata.gov.gr/maps/?locale=el" target="_blank">https://geodata.gov.gr/maps/?locale=el</a>, accessed on 4 January 2024. (<b>b</b>) The location of the Ramsar wetlands in Greece (purple dots signify Ramsar wetlands of international importance, black dots signify the existence of general wetlands). Source: [<a href="#B67-land-13-00538" class="html-bibr">67</a>] using <a href="http://www.ekby.gr/ekby/en/EKBY_Publications_en.html" target="_blank">http://www.ekby.gr/ekby/en/EKBY_Publications_en.html</a>, accessed on 4 January 2024, Reprinted/adapted with permission from Ref. [<a href="#B67-land-13-00538" class="html-bibr">67</a>]. (<b>c</b>) Corine Label 3 exclusively presenting LUs relating to current wetland conditions.</p>
Full article ">Figure 2
<p>Two versions of the reed-bed-burning frequency vs. size or magnitude rank (in log-log space). <b>Left</b>: the classic power law representation of the frequency–size distribution. Tones of grey indicate hypothetical mechanisms generating different categories of reed bed burning sizes, explanations on the meanings of grey tones are provided in the text below. <b>Right</b>: the proposed categorizing of reed-bed-burning events according to their respective size. For further explanation and details, see the text below.</p>
Full article ">Figure 3
<p>Spider chart comparing the frequencies, total area burned, and SI of reed bed burning in Greece (2000–2022). Data refer exclusively to land uses comprising existing or converted wetlands, primarily variations of agricultural land setups, but also infrastructure (airports), tourism activities (beaches, dunes, sands), and industrial activities (salines and salt marshes). Blue line: frequency; red line: total area burned; purple line: SI. Axes are log-transformed.</p>
Full article ">Figure 4
<p>Summary descriptives of the severity index of wildfires per vegetation type in Greece, from 2000–2022. Boxplots represent the median (horizontal thick line), the first and third quartiles (box), and the 1.5 interquartile range (whiskers). Black dots are outliers. 1: Crop residue; 2: agricultural land; 3: forest; 4: forested area; 5: shrubland/grassland; 6: reed bed burning.</p>
Full article ">Figure 5
<p>Pairwise comparison of severity indexes per vegetation type after Kruskal–Wallis independent sample test. Significance values have been adjusted after Bonferroni correction for multiple tests. Nodes show the average rank of SI per vegetation type. Code: 1: reed-bed-burning SI; 2. Crop residue burnings SI; 3. Agriculture land wildfire SI; 4. Forest wildfire SI; 5. Forested areas SI; 6. Shrubland/grassland wildfire SI. Each SI series consists of 276 monthly recordings, 2000–2022. Extract from the dashboard of IBM SPSS v. 28.</p>
Full article ">Figure 6
<p>Sequence plot of the reed bed burnings/month time series at NUTS 0, i.e., Creece’s level. Data are natural-logarithm-transformed, and first-degree differencing is applied. The blue line represents the area/month series, the green line the frequency/month series, and the red line the SI/month series. Two hundred seventy-six records (months) are reported (1/2000-12/2022). Extract from the dashboard of IBM SPSS v. 28.</p>
Full article ">Figure 7
<p>Indicative examples of ARIMA (1,1,1) models of time series analysis of severity indexes of reed bed burnings in two-time scales, yearly vs. monthly, (<b>a</b>) vs. (<b>b</b>). Red lines present the observed values, blue lines are the fit lines, and dots are the upper and lower confidence limits. Extracts from the dashboard of IBM SPSS v. 8. (<b>c</b>,<b>d</b>) present the Fast Fourier Transform smoothing of the SI series distribution models at a scale of 10 years (or 120 months)—extracts from the dashboard of the XLSTAT package. RMSE* represents the normalized value calculated as RMSE/(max–min values).</p>
Full article ">Figure 8
<p>(<b>Map 1</b>) Pyrogeographic map of reed bed burning during 2020–2022. The size of the dots indicates the magnitude of burning events in the corresponding locations. Clusters of events suggest the reed-bed-burning hotspots in Greece (NUTS 0) and, indirectly, the presence of existing and converted wetlands where abiotic conditions, especially wetland-related hydric soil conditions, allow for the presence and post-burning recovery of <span class="html-italic">P. australis</span> beds. Light-black polygons are the boundaries of NUTS 1 (prefectures); light-grey lines are the hydrographic network of Greece.</p>
Full article ">Figure 9
<p>(<b>Map 2</b>) Indicative examples of reed-bed-burning distribution in two converted wetlands (Yiannitsa and Kopaida) and two existing Ramsar wetlands of international importance (Thrace: Lake Ismarida, Porto, and lagoons; and Ileia: Cothychi).</p>
Full article ">Figure 10
<p>(<b>Map 3</b>) Blocks of adjacent grid cells present positive values of the score function. This applies to both converted and existing wetlands in Greece. Red arrows indicate the locations of the extensive land reclamation works in Greece for more than a century to develop agricultural land and secure food sufficiency for the growing population.</p>
Full article ">Figure A1
<p>Satellite image (NASA Terra) of the mega-fire conditions in the Peloponnese on 26 August 2007. Coastal wetlands of the prefecture of Ilia burned for more than a week before suppression.</p>
Full article ">
21 pages, 5722 KiB  
Article
How to Coordinate the Relationship between Urban Space Exploitation, Economic Development, and Ecological Environment: Evidence from Henan Province, China
by Xiaotong Xie, Kunlin Wu, Yingchao Li, Shanshan Guo and Xiaoshun Li
Land 2024, 13(4), 537; https://doi.org/10.3390/land13040537 - 17 Apr 2024
Cited by 1 | Viewed by 810
Abstract
With the rapid development of urbanization, China is facing problems, such as uncoordinated regional development, imbalanced land space development, and ecological environment pollution. This poses a huge threat to the sustainable development of China’s economy and society. Therefore, there is an urgent need [...] Read more.
With the rapid development of urbanization, China is facing problems, such as uncoordinated regional development, imbalanced land space development, and ecological environment pollution. This poses a huge threat to the sustainable development of China’s economy and society. Therefore, there is an urgent need to determine how to coordinate the relationship between the space exploitation, economic development, and ecological environment (SEE) of urban areas. In this study, taking the Henan Province as an example, long time-series data (2000–2020) were used, at a city scale. Then, we developed a logical framework to reveal the interrelationship and intrinsic mechanism between SEE. Next, we explored the spatiotemporal coupling characteristics of SEE using a linear weighting method and a coupling coordination analysis. We found that, from 2000 to 2020, the comprehensive level of SEE showed an obvious trend of change, and different cities have different coupling coordination degrees. However, the overall coupling coordination level is steadily developing and tending to improve. Furthermore, with the spatial autocorrelation method, we analyzed spatial correlation patterns and collaboration/trade-off relationships for SEE. Through the analysis, positive correlation types (HH, LL) cluster significantly and negative correlation types (HL, LH) have low clustering. Meanwhile, we found significant spatial differences in cooperation/trade-off relationships between different years. This research can serve as a reference and as methodological guidance for achieving coordination and sustainable development of the economy, space, and environment. Full article
(This article belongs to the Special Issue Environmental Sustainability Assessment of Land System)
Show Figures

Figure 1

Figure 1
<p>Logical framework of urban system of space exploitation, economic development, and ecological environment (SEE).</p>
Full article ">Figure 2
<p>Geographical location of Henan Province.</p>
Full article ">Figure 3
<p>Research process and framework.</p>
Full article ">Figure 4
<p>Evolution trend of SEE during 2000–2020.</p>
Full article ">Figure 5
<p>Temporal variation in coupling coordination degree of SEE during 2000–2020.</p>
Full article ">Figure 6
<p>Spatial variation in coupling coordination degree of SEE during 2000–2020. (<b>a</b>) Comprehensive coordination degree. (<b>b</b>) Coordination degree between space exploitation and economic development (SEcon). (<b>c</b>) Coordination degree between space exploitation and ecological environment (SEcol). (<b>d</b>) Coordination degree between economic development and ecological environment (EconEcol).</p>
Full article ">Figure 7
<p>Moran’s scatter plot of coupling coordination degree of SEE during 2000–2020.</p>
Full article ">Figure 8
<p>Local spatial correlation of coupling coordination degree of SEE from 2000 to 2020. (<b>a</b>) Local spatial correlation of coupling coordination degree of space exploitation. (<b>b</b>) Local spatial correlation of coupling coordination degree of economic development. (<b>c</b>) Local spatial correlation of coupling coordination degree of ecological environment.</p>
Full article ">Figure 9
<p>Spatial relationship of collaboration/trade-off between SEE from 2000 to 2020. (<b>a</b>) Spatial relationship of collaboration/trade-off between SEcon. (<b>b</b>) Spatial relationship of collaboration/trade-off between SEcol. (<b>c</b>) Spatial relationship of collaboration/ trade-off between EconEcol.</p>
Full article ">
32 pages, 26516 KiB  
Article
Integrating Heritage and Environment: Characterization of Cultural Landscape in Beijing Great Wall Heritage Area
by Ding He, Wenting Chen and Jie Zhang
Land 2024, 13(4), 536; https://doi.org/10.3390/land13040536 - 17 Apr 2024
Viewed by 1001
Abstract
The Great Wall, as a globally important large-scale linear cultural heritage asset, is an example of the integration of architecture and landscape, demonstrating the interaction and feedback between heritage and the environment. In the context of advocating the holistic protection of cultural heritage [...] Read more.
The Great Wall, as a globally important large-scale linear cultural heritage asset, is an example of the integration of architecture and landscape, demonstrating the interaction and feedback between heritage and the environment. In the context of advocating the holistic protection of cultural heritage and surroundings, this study utilizes landscape character assessment (LCA) to identify the landscape character of the Great Wall heritage area. Taking the heritage area of the Great Wall in Beijing, China, as an example, principal component analysis (PCA), two-step clustering, and the eCognition software were used to identify and describe the landscape character types, and the interaction mechanism between heritage and the environment was further explored through the reclassification process. A total of 20 landscape character types and 201 landscape character areas were identified in the study area, and a deep coupling relationship between heritage and the environment and cultural landscape spatial patterns were found in the core heritage area. The heritage and environmental character of linear heritage areas should be integrated so as to protect, manage, and plan cultural heritage areas at the landscape level. This study identifies and describes the character of the coupling of heritage and the environment in the Great Wall area for the first time, expands the types and methods of landscape character assessment, and carries out the exploration to combine natural and cultural elements of large-scale linear cultural heritage areas. Full article
(This article belongs to the Section Land Planning and Landscape Architecture)
Show Figures

Figure 1

Figure 1
<p>The research area and the distribution of side walls, fortified towers, beacon towers, and fortresses.</p>
Full article ">Figure 2
<p>Methodological framework for landscape character assessment based on the integration of heritage and the environment.</p>
Full article ">Figure 3
<p>Results of the two-step cluster analysis: (<b>a</b>) the area of the landscape character types of the Beijing Great Wall heritage area; (<b>b</b>) the proportion of the various natural landscape-level variables in each landscape character type (link to <a href="#land-13-00536-t001" class="html-table">Table 1</a>); and (<b>c</b>) the box plots of the kernel densities of the cultural heritage variables for each landscape character type (link to <a href="#land-13-00536-t002" class="html-table">Table 2</a>).</p>
Full article ">Figure 3 Cont.
<p>Results of the two-step cluster analysis: (<b>a</b>) the area of the landscape character types of the Beijing Great Wall heritage area; (<b>b</b>) the proportion of the various natural landscape-level variables in each landscape character type (link to <a href="#land-13-00536-t001" class="html-table">Table 1</a>); and (<b>c</b>) the box plots of the kernel densities of the cultural heritage variables for each landscape character type (link to <a href="#land-13-00536-t002" class="html-table">Table 2</a>).</p>
Full article ">Figure 4
<p>Map of landscape character types in the Beijing Great Wall heritage area (machine identification).</p>
Full article ">Figure 5
<p>Landscape character areas: (<b>a</b>) delineation in eCognition with scale parameter 30; (<b>b</b>) delineation in eCognition with scale parameter 50; and (<b>c</b>) delineation by manual adjustments.</p>
Full article ">Figure 6
<p>The core area of the Beijing Great Wall heritage site.</p>
Full article ">Figure A1
<p>F-FT-B-12 field survey sheet for the Shitang Road (formerly known as the Lupi Pass Great Wall, undeveloped), located in the eastern foothills of the Yunmeng Mountain and the west bank of the Miyun Reservoir. Generally speaking, the Great Wall stretches across the top of the mountain, from west to east, while the Great Wall on Shitang Road has a section that turns sharply downward, in a north–south direction, only because of the towering mountains, complex terrain, dense fortresses, and numerous passes near the river, which were historically easy to defend and difficult to attack. This is a very characteristic landscape area and also the only place where mountains, valleys, rivers, lakes, and the Great Wall converge and overlap. There were chestnut trees here in ancient times. Although the garrison generals in the Ming Dynasty had rations issued by the court, they were located in deep forests and could use chestnuts to fill up their hunger when they encountered floods, torrential rains, or inconveniences in transportation. Here, there are also the Baiyihua Counter-war Red Memorial Hall, the Shitanglu Village, the Bell and Drum Tower, the Parrot Cliff, and other cultural sites.</p>
Full article ">Figure A2
<p>F-FT-B-13 field survey sheet. The Great Wall is the section from Gubeikou to Simatai, which is located in the Yanshan Mountain Range, with steep peaks on both sides, and the wall is built along the ridge, through which the Chaohe River flows from north to south. The clustered area is on a plain with a low degree of elevation, which was the first military defense line for northeastern Beijing and has been an important pass or postal transportation route since ancient times. It is located on a relatively flat and open terrain, with historically a large number of troops stationed here and a large scale of settlements, where the Chaoheguan, Simatai, Jijiaying, and Xinchengzi Fortresses are all located. Due to the special geographic location of Gubeikou, there are not only magnificent natural landscapes but also heavy historical and cultural deposits. Due to historical evolution, location advantages, and the change of several dynasties and military forces, Gubeikou is not only a “military town” but also an important hub for multi-ethnic settlement and multi-cultural (Confucianism, Buddhism, and Taoism), commercial, and trade exchanges inside and outside of the Customs and Excise Department. Under the special effects of geography, military, culture, and the economy, it has created numerous scenic spots and unique human landscapes in the area.</p>
Full article ">Figure A3
<p>F-FT-B-14 field survey sheet. The site on this terrain is more special: from Juyongguan to the north of Beijing, on both sides of the mountains, the center is only a goat path to a sudden piece of open land, known as the gateway to Juyongguan. The Fork Fortress is Juyongguan, and the Badaling Pass military outpost has always been the east–west and north–south transportation hub and military stronghold to which various dynasties sent heavy guards. The higher altitude of the open ground, where a city was built, has an important military significance. In the Ming Dynasty, the Fork Road Fortress was used as a garrison city, and there was a schoolyard, i.e., a military drill ground, outside the west gate. At the end of the Qing Dynasty, the defensive function of the Great Wall was gradually lost, and the military drill ground became a sunbathing ground for the common people. The site has been a major transportation route since ancient times, and merchants, caravans, various means of transportation, and Chinese and foreign guests passed through here in ancient times. There is only one main street, running east–west in the city, which is surrounded by infrastructure such as postal houses, stores, chagongyuan, and temples.</p>
Full article ">Figure A4
<p>F-FT-B-15 field survey sheet for the Fork Road Fortress area. The terrain is more special: from Juyongguan to the north of the capital, on both sides of the mountains, there is only a goat path in the middle, after which, suddenly, there is a piece of open space, known as the gateway to Juyongguan. The Fork Road Fortress is Juyongguan, and the Badaling military outpost has always been the east–west and north–south transportation hub and a military strongholds to which various dynasties sent heavy guards. In the higher altitude of the open ground, a fortress with important military significance was built. In the Ming Dynasty, the Fork Road Fortress was used as a garrison fortress, and there was a military drill ground outside the west gate. At the end of the Qing Dynasty, the defensive function of the Great Wall was gradually lost, and the military drill ground became a sunbathing ground for the citizens. This site has been a major transportation route since ancient times, and merchants, various means of transportation, and foreign guests passed through here in ancient times. There is only one main street running east–west in the city, which is surrounded by infrastructure such as postal houses, stores, and temples.</p>
Full article ">Figure A5
<p>F-FT-B-16 field survey sheet for the Yanqing district of the Great Wall in the East Road, side wall section, located in the central part of the Yanqing district terrain, on a flat elevation area. The trend is roughly in south–east to north–west directions, with dozens of beacon towers concentrated along the wall and the fortress around the defense belt. From Sihai town through the LiuBinBaoXiang-to-XiangYingXiang line of the beacon with the East Road side wall and Sihaizhih fortress, haizikou fortress, HeiHanLing fortress, ZhouShiGou fortress, XiangYing fortress, and other fortresses, each fortress is a corner, together constituting a strong fortification.</p>
Full article ">
21 pages, 6313 KiB  
Article
Assessment of Uncertainties in Ecological Risk Based on the Prediction of Land Use Change and Ecosystem Service Evolution
by Chang You, Hongjiao Qu, Shidong Zhang and Luo Guo
Land 2024, 13(4), 535; https://doi.org/10.3390/land13040535 - 17 Apr 2024
Cited by 1 | Viewed by 807
Abstract
With the rapid progress in urbanization and economic development, the impact of land use change (LUC) on ecosystem services is becoming increasingly significant. However, the accuracy of ecological risk assessment faces challenges due to the presence of uncertainty factors. Using the PLUS model, [...] Read more.
With the rapid progress in urbanization and economic development, the impact of land use change (LUC) on ecosystem services is becoming increasingly significant. However, the accuracy of ecological risk assessment faces challenges due to the presence of uncertainty factors. Using the PLUS model, this study aims to simulate and predict land use changes (LUCs), focusing on the southern hilly regions in southeastern China as a case study, conducting an in-depth assessment of ecological risk uncertainty. Firstly, a spatiotemporal simulation of LUCs in the southern hilly region from 1990 to 2030 was conducted under multiple scenarios. Subsequently, differences in the spatial and temporal distribution of ecosystem service value (ESV) across different years and forecast scenarios in the southern hilly region were revealed, followed by a detailed analysis of the impact of LUCs on ESV. Finally, by calculating the Ecological Risk Index (ERI), the study systematically analyzed the evolution trend of ecological risk in the southern hilly region of China from 1990 to 2030. The main research findings are as follows: (1) the conversion proportions of different land use types vary significantly under different scenarios. Compared to 2020, under the 2030 National Development Scenarios (NDSs), there has been a slight decrease of around 3% in the total conversion area of farmland, forest, and grassland. However, under the Ecological Protection Scenario (EPS) and Urban Development Scenario (UDS) scenarios, there has been an increase in the area of forest and grassland, with a rise of approximately 1.5% in converted built-up land. (2) Western cities (e.g., Yueyang and Yiyang), central cities (e.g., Jiujiang), and northeastern cities (e.g., Suzhou) of China exhibit a relatively high ESV distribution, while ESV significantly decreased overall from 2010 to 2020. However, under the EPS and UDS, ESV shows a significant increasing trend, suggesting that these two scenarios may play a crucial role in ecosystem restoration. (3) The conversion of forest and water bodies to farmland has the most significant inhibitory effect on ESV, especially during the period from 1990 to 2000, providing substantial data support for relevant policy formulation. (4) From 1990 to 2030, ecological risk gradually increased in western, central, and southwestern cities of the southern hilly region, with the highest ecological risk values under the EPS scenario in northern cities (e.g., Chizhou and Tongling). Under the UDS scenario, there has been a significant decrease in ecological risk, providing valuable insights for future ecological conservation and sustainable development. However, a limitation lies in the need for further enhancement of the scenario’s simulation authenticity. This study offers a new perspective for understanding the impact of LUCs on ecosystem services and the uncertainty of ecological risks, providing crucial reference points for land resource management and the formulation of ecological conservation policies. Full article
(This article belongs to the Special Issue Ecological and Disaster Risk Assessment of Land Use Changes)
Show Figures

Figure 1

Figure 1
<p>Overview of the study area. Note: the image in the black box in the lower right corner represents an enlarged thumbnail of the South China Sea islands and other parts of the islands.</p>
Full article ">Figure 2
<p>The framework for land simulation.</p>
Full article ">Figure 3
<p>Spatial and temporal changes in land use from 1990 to 2030 under various scenarios. Note: (<b>a.1</b>–<b>f.1</b>) represent enlarged versions of thumbnails of sample areas in the northwestern part of the study area, respectively. (<b>a.2</b>–<b>f.2</b>) represent enlarged versions of thumbnails of sample areas in the southeastern part of the study area, respectively.</p>
Full article ">Figure 4
<p>Spatial and temporal distribution of ESV in the southern hilly region under multiple scenarios from 1990 to 2030.</p>
Full article ">Figure 5
<p>The evolving trends in changes to the ESV from 1990 to 2020 and the projected scenarios from 2020 to 2030. Note: NDS: Natural Development Scenario; EPS: Ecological Protection Scenario; and UDS: Urban Development Scenario.</p>
Full article ">Figure 6
<p>Impact of different types of LUCs on ESV.</p>
Full article ">Figure 7
<p>Spatiotemporal changes in ERI from 1990 to 2020 and under various forecasting scenarios from 2020 to 2030.</p>
Full article ">Figure 8
<p>Contribution of driving factors to LUC. Note: DH: distance from major highways; DR: distance from the railway; DV: distance from the river; GL: GDP per land; DP: density of population; AT: annual average temperature; and AP: mean annual precipitation.</p>
Full article ">
16 pages, 2360 KiB  
Article
Review of Urbanization-Associated Farmland Research in China: A Sustainability Perspective
by Qiqi Yang, Lijie Pu and Sihua Huang
Land 2024, 13(4), 534; https://doi.org/10.3390/land13040534 - 17 Apr 2024
Viewed by 925
Abstract
Farmland loss in drastically urbanizing landscapes has long been a research concern for resource management, landscape planning, and spatial governance, especially in the context of China. In recent years, the issue of urbanization-associated farmland loss (UAFL) seems to be increasingly recognized as relevant [...] Read more.
Farmland loss in drastically urbanizing landscapes has long been a research concern for resource management, landscape planning, and spatial governance, especially in the context of China. In recent years, the issue of urbanization-associated farmland loss (UAFL) seems to be increasingly recognized as relevant to sustainability. To date, however, existing studies have not yet comprehensively addressed the research gap between UAFL and sustainability. Here, we aim to help fill this knowledge gap by considering UAFL research as an example of the broader land/landscape-related literature, in a hope of informing future studies to better advance sustainability through land-related approaches. Specifically, we combined bibliometric analyses with code-based content analysis to reveal the knowledge base, thematic evolution, and historiographic paths of the literature on UAFL across China and the empirical case studies’ relevance to sustainability. Our main findings include: (1) the examined literature barely draws insights from sustainability science and sustainability only started to arise as a notable topic at around 2016; (2) over half of the empirical studies show awareness in advancing sustainability and interest in understanding the social-environmental drivers and processes underlying landscape dynamics, yet few demonstrate methodological transdisciplinarity; (3) those sustainability-relevant studies either frame UAFL as depletion of the farmland resource that may threat China’s food security and consequently hinder sustainable urbanization or frame UAFL as part of widespread landscape dynamics that affect the environmental outcome(s) or social–environmental tradeoffs of landscape multi-functions; and (4) existing empirical studies are disproportionately focused on 1991–2006, national, regional, and city scales, and some of China’s most developed areas. Our findings provide an overview of this specific research avenue on UAFL and, more importantly, point to the imperative for land/landscape scholars to break out of their disciplinary silos, especially in the natural sciences, to generate more actionable sustainability insights. Full article
Show Figures

Figure 1

Figure 1
<p>Flow diagram of data collection based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. See text for the four criteria to filter eligible studies for thematic coding and case synthesis.</p>
Full article ">Figure 2
<p>Thematic clustering of the topics identified from the <span class="html-italic">keywords</span> (<b>A</b>), <span class="html-italic">titles</span>, and <span class="html-italic">abstracts</span> (<b>B</b>), as well as their temporal evolution (<b>C</b>,<b>D</b>). The node size of a phrase is proportionate to its relative frequency. The analyses adopted VOSviewer’s default settings; the association strength method was used for normalizing the strength of the links between nodes.</p>
Full article ">Figure 3
<p>Main paths of the development of UAFL research literature in China, based on citation linkages among the top 25 papers with the most local citations (from within the sampled 615 papers) (see <a href="#app1-land-13-00534" class="html-app">Table S3</a> for bibliographic details). The six seminal papers shaded gray are among the top 20 cited references within the 615 papers (detailed in <a href="#land-13-00534-t001" class="html-table">Table 1</a>), suggesting their relatively larger influences on subsequent research about UAFL in China. Note that the two seminal papers published in 2005 by Tan and his colleagues is distinguished in the main text by Tan et al. (2005a) [<a href="#B61-land-13-00534" class="html-bibr">61</a>] and Tan et al. (2005) [<a href="#B41-land-13-00534" class="html-bibr">41</a>].</p>
Full article ">Figure 4
<p>Sustainability features of UAFL case studies in China (N = 103): (<b>A</b>) oriented toward addressing social–environmental sustainability impacts or not; (<b>B</b>) delving into underlying social–environmental processes or not; and (<b>C</b>) adopting qualitative, quantitative, or mixed research methodology.</p>
Full article ">Figure 5
<p>Empirical focuses of UAFL case studies in China (N = 103): (<b>A</b>) study period; (<b>B</b>) geographic scale; and (<b>C</b>) study area. Word size in panels A and C are proportionate to its relative frequency.</p>
Full article ">
Previous Issue
Next Issue
Back to TopTop