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Land
Volume 12
Issue 7
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Land, Volume 12, Issue 7 (July 2023) – 209 articles

Cover Story (view full-size image): Climate and land-use change impact catchment hydrology and water quality; however, research has not clearly identified the land-use change required to achieve specific water quality targets under future climate conditions. Our study investigated the effects of land use and climate change scenarios on the streamflow and nutrient loads of a New Zealand lake catchment. Our findings showed that increasing forest coverage resulted in reduced streamflow and nutrient loads, and land-use change strategies combined with climate change mitigation based on RCP8.5 would lead to the largest reduction in flow and nutrient loads. This research offers valuable insights into land-use change strategies for mitigating nutrient loads in lake catchments, providing a blueprint for similar regions experiencing land-use transformations. View this paper
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21 pages, 8227 KiB  
Article
Assessment of the Vulnerability of the Coast of Lake Alakol to Modern Geomorphological Processes of Relief Formation
by Akhmetkal Medeu, Adilet Valeyev, Farida Akiyanova, Yuisya Lyy, Gulnura Issanova and Yongxiao Ge
Land 2023, 12(7), 1475; https://doi.org/10.3390/land12071475 - 24 Jul 2023
Cited by 1 | Viewed by 1577
Abstract
Over the last few decades, increasing water levels of Lake Alakol have led to the activation of processes of modern relief formation of the coastal territory. This study will make it possible to assess the vulnerability of the lake shore to modern relief-forming [...] Read more.
Over the last few decades, increasing water levels of Lake Alakol have led to the activation of processes of modern relief formation of the coastal territory. This study will make it possible to assess the vulnerability of the lake shore to modern relief-forming processes, which pose a threat to the economic and infrastructural development of the coast. Through a combination of field research methods, analysis of the archival materials and satellite images, GIS mapping, as well as the application of the Coastal Vulnerability Index, developed by Gornitz, a map of the modern relief of the coast of Lake Alakol was created, where 13 geomorphological types of relief were identified, and a map of relief-forming processes and leading exogenous processes were identified. The values of the assessment of the degree of vulnerability of the coast to dangerous processes by the Gornitz method were obtained, where a high vulnerability covers 67.4% of the coast, an average vulnerability covers 2.9%, a weak vulnerability covers 13.3%, and low vulnerability occupies 16.4% of the coast. The degree of vulnerability of types of relief in the study area, the coast of Lake Alakol, was determined. High degree occupies 42.8% of the study area, medium—30.7%, weak—25.4%, and low 1.1%. A map of the complex assessment of the degree of vulnerability of the coast of Lake Alakol was created. It was revealed that low accumulative types of relief of the northwest and northeast coasts and alluvial-proluvial types of relief are highly vulnerable due to waterlogging and the intensity of abrasion processes. Identified natural features of the relief formation of the coast of Lake Alakol are recommended as a basis for making decisions on the planning and implementation of any economic activities on the coast, including infrastructure development of the coast and strengthening of the shores. Full article
(This article belongs to the Section Land Innovations – Data and Machine Learning)
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<p>Coastal zone of Lake Alakol: sector (<b>A</b>)—satellite image of Kazakhstan territory, red color marks the study area, blue color, the lake; sector (<b>B</b>)—study area; sector (<b>C</b>)—photos taken by the authors, as examples of different coastal types. Location of sites on the map (sector (<b>B</b>)): photo 1—abrasion northwest coast; photo 2—low-lying accumulative coast near the Katynsu River delta; photo 3—abrasion-accumulative coast type; photo 4—abrasion southwest coast.</p> Full article ">Figure 2
<p>Flow chart of the research process used for this research.</p> Full article ">Figure 3
<p>Types of relief of the coast of Lake Alakol.</p> Full article ">Figure 4
<p>Modern relief-forming processes on different types of coastline of Lake Alakol: (<b>a</b>) flooding of Kamyskala village residential areas as a result of increased water level during filtration through the dam; (<b>b</b>,<b>c</b>) consequences of bank processing, which caused the destructive impact of recreational infrastructure on the coast of Akshi recreation area; (<b>d</b>) bank processing of Koktuma village; (<b>e</b>,<b>f</b>) coastal erosion impact on residential structures of Koktuma village.</p> Full article ">Figure 4 Cont.
<p>Modern relief-forming processes on different types of coastline of Lake Alakol: (<b>a</b>) flooding of Kamyskala village residential areas as a result of increased water level during filtration through the dam; (<b>b</b>,<b>c</b>) consequences of bank processing, which caused the destructive impact of recreational infrastructure on the coast of Akshi recreation area; (<b>d</b>) bank processing of Koktuma village; (<b>e</b>,<b>f</b>) coastal erosion impact on residential structures of Koktuma village.</p> Full article ">Figure 5
<p>Modern relief-forming processes of the coast of Lake Alakol.</p> Full article ">Figure 6
<p>Values of different coastal vulnerability parameters: (<b>a</b>) relief of coast; (<b>b</b>) coastal geology; (<b>c</b>) landform; (<b>d</b>) cliff abrasion; (<b>e</b>) leading process; (<b>f</b>) tidal range, m.</p> Full article ">Figure 7
<p>Assessment of the degree of vulnerability of the coast of Lake Alakol using the Gornitz method (Gornitz, 1991).</p> Full article ">Figure 8
<p>Comprehensive assessment of the degree of vulnerability of the coast of Lake Alakol to modern processes of relief formation.</p> Full article ">
21 pages, 4272 KiB  
Article
Exploration of Spatio-Temporal Evolution and Threshold Effect of Shrinking Cities
by Yuanzhen Song, Weijie He and Jian Zeng
Land 2023, 12(7), 1474; https://doi.org/10.3390/land12071474 - 24 Jul 2023
Cited by 6 | Viewed by 1513
Abstract
Shrinking cities are a global issue with regional characteristics. This paper focuses on the county-level administrative units in the Three Northeastern Provinces in China to identify and classify shrinking cities using a two-step identification method and explores their spatial-temporal evolution. The paper utilizes [...] Read more.
Shrinking cities are a global issue with regional characteristics. This paper focuses on the county-level administrative units in the Three Northeastern Provinces in China to identify and classify shrinking cities using a two-step identification method and explores their spatial-temporal evolution. The paper utilizes the panel threshold regression model for empirical testing. The results indicate the following: (1) The number of shrinking cities in the region is large and deep. Quantitatively, the shrinking cities account for about 50% of the whole; spatially, there are six major shrinking city “groups”, showing the distribution trend around the “Ha-Da” urban corridor. (2) The threshold effect test reveals that GDP is a critical threshold variable influencing the formation of shrinking cities. Moreover, cities are classified into three types based on the threshold values: Type I (GDP > 2,270,731 yuan), Type II (434,832 < GDP ≤ 2,270,731), and Type III (GDP < 434,832). (3) The results of the dual-threshold and grouped regression models show significant variations in the dominant factors of shrinking cities of different scales. Variables such as impervious area, fiscal revenue, and grass area demonstrate relatively stable promoting effects. Full article
(This article belongs to the Special Issue Urbanization in Transition and Coordinated Regional Development: Challenges under Global Change)
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<p>Study area map.</p> Full article ">Figure 2
<p>The number and rate of population loss in the three northeastern provinces.</p> Full article ">Figure 3
<p>The type division of shrinking cities.</p> Full article ">Figure 4
<p>(<b>a</b>) Cumulative count (number) classification spatial distribution; (<b>b</b>) Spatial distribution of population loss range (rate) classification.</p> Full article ">Figure 5
<p>Spatial distribution of shrinking city types.</p> Full article ">
20 pages, 6126 KiB  
Article
Exploring the Comprehensive Evaluation of Sustainable Development in Rural Tourism: A Perspective and Method Based on the AVC Theory
by Lili Liu, Ruonan Wu, Yuanrong Lou, Pingping Luo, Yan Sun, Bin He, Maochuan Hu and Srikantha Herath
Land 2023, 12(7), 1473; https://doi.org/10.3390/land12071473 - 24 Jul 2023
Cited by 6 | Viewed by 1724
Abstract
The coronavirus disease (COVID-19) pandemic has led to a surge in rural tourism, catering to consumers during the pandemic. However, rural tourism faces severe issues of homogeneity and environmental degradation owing to excessive development. Sustainable development of rural tourism is an urgent problem. [...] Read more.
The coronavirus disease (COVID-19) pandemic has led to a surge in rural tourism, catering to consumers during the pandemic. However, rural tourism faces severe issues of homogeneity and environmental degradation owing to excessive development. Sustainable development of rural tourism is an urgent problem. This study, based on the average variable cost (AVC) theory, aims to explore the sustainable development of rural tourism landscapes with a focus on the Shijing area. A landscape evaluation system was established through factor analysis and weight calculations, with ten principal components contributing to a cumulative contribution rate of 77.196%. The weighted values for attractiveness, vitality, and resilience were 0.539, 0.297, and 0.164, respectively. The findings indicate that Caijiapo Village had the highest comprehensive score of 88.79 (good level of performance), whereas Laoyukou Village had the lowest comprehensive score of 80.25 (average level of performance). Caijiapo and Liyukou exhibited the strongest overall strength, whereas Liyuanpo and Xiazhuang had moderate overall strength, and Laoyukou had the weakest overall strength. The results reveal that all five villages possess rich natural landscapes and favorable geographical conditions, demonstrating the potential and attractiveness of rural tourism development. However, the overall carrying capacity was moderate and vitality was relatively weak. This supports the AVC theory application in rural tourism research and emphasizes the importance of rural landscape quality and economic vitality. The main contributions of this study are as follows: (1) the establishment of a rural tourism landscape evaluation system based on the AVC theory, providing a scientific assessment method for sustainable development; (2) the case evaluation in the Shiying area provides decision-makers with reference for development strategies; (3) emphasis on the importance of ecological conservation in rural tourism and providing recommendations to address issues of homogenization and environmental degradation. Full article
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<p>Location of the Study Area. (<b>a</b>) The macro location of Huyi District; (<b>b</b>) The specific scope and location of the study area.</p> Full article ">Figure 1 Cont.
<p>Location of the Study Area. (<b>a</b>) The macro location of Huyi District; (<b>b</b>) The specific scope and location of the study area.</p> Full article ">Figure 2
<p>Research Framework.</p> Full article ">Figure 3
<p>Reliability Analysis of Sample Factor Layer and Total Sample Size.</p> Full article ">Figure 4
<p>Distribution of weights for the factor layer in AVC rural landscape evaluation. (C1 to C10 represent Natural Landscape, Cultural Landscape, Location Conditions, Residential Environment, Economic Vitality, Industrial Structure, Tourism Development, Ecological Environment Capacity, Spatial Resource Capacity, and Psychological Carrying Capacity, respectively).</p> Full article ">Figure 5
<p>Distribution of weights for the indicator layer.</p> Full article ">Figure 6
<p>Evaluation results of indicators at the project level.</p> Full article ">Figure 7
<p>Evaluation results of indicators at the factor level.</p> Full article ">Figure 8
<p>The distribution of three-force analysis results of five village groups. (Different colors represent the three-force analysis of different villages, the curve represents the distribution of scoring values, and the black dots represent specific numerical values).</p> Full article ">Figure 9
<p>Comparative Analysis of Three Forces in Shijing Area.</p> Full article ">
18 pages, 1861 KiB  
Article
Evaluation and Optimization of Restorative Environmental Perception of Treetop Trails: The Case of the Mountains-to-Sea Trail, Xiamen, China
by Honglin Wu, Li Zhu, Jiang Li, Ni Zhang, Yilin Sun, Yue Tang, Xiaokang Wang and Chuang Cheng
Land 2023, 12(7), 1472; https://doi.org/10.3390/land12071472 - 24 Jul 2023
Cited by 3 | Viewed by 1754
Abstract
A treetop trail is an elevated linear green open space that plays a key role in forming a scientifically rational urban space and meeting the growing leisure needs of the people. Taking the Mountains-to-Sea Trail in Xiamen, China as a case, and through [...] Read more.
A treetop trail is an elevated linear green open space that plays a key role in forming a scientifically rational urban space and meeting the growing leisure needs of the people. Taking the Mountains-to-Sea Trail in Xiamen, China as a case, and through 426 questionnaires, this study explores the dimensions of the perceived restorative environment components of greenway recreationists and impacts on behavioral intentions. The demographic factors lead us to the following three conclusions. First, from an age perspective, restorative environmental perceptions are strongest among those aged 60 and above and weakest among those aged 18–30. Second, in terms of place of permanent residence, local visitors have stronger restorative environmental perceptions than other city users. Third, in relation to the number of accompanying travelers, individuals who embark on solo journeys experience the most robust perception, while that diminishes as the count reaches three or more companions. A structural equation model (SEM) is used to present the quantitative relationship among avoidance motivation, treetop trail environmental quality, restorative environmental perception, place attachment, and loyalty. The results showed that users’ escape motivation has a direct and indirect positive correlation with restorative environmental perceptions, and environmental perceptions have a significant positive correlation with restorative environmental perceptions. Furthermore, their place attachment to the restorative nature of the treetop trails positively affected their loyalty. This study provides essential factors to consider when constructing treetop trails in high-density cities. Full article
(This article belongs to the Section Land Planning and Landscape Architecture)
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<p>Mountains-to-Sea Trail routes, representative images of significant locations, and questionnaire distribution locations.</p> Full article ">Figure 2
<p>Structural equation modeling.</p> Full article ">Figure 3
<p>Standard estimates of the structural equation model path analysis.</p> Full article ">
18 pages, 2790 KiB  
Article
The Flow Matrix Offers a Straightforward Alternative to the Problematic Markov Matrix
by Jessica Strzempko and Robert Gilmore Pontius, Jr.
Land 2023, 12(7), 1471; https://doi.org/10.3390/land12071471 - 24 Jul 2023
Viewed by 2461
Abstract
The Flow matrix is a novel method to describe and extrapolate transitions among categories. The Flow matrix extrapolates a constant transition size per unit of time on a time continuum with a maximum of one incident per observation during the extrapolation. The Flow [...] Read more.
The Flow matrix is a novel method to describe and extrapolate transitions among categories. The Flow matrix extrapolates a constant transition size per unit of time on a time continuum with a maximum of one incident per observation during the extrapolation. The Flow matrix extrapolates linearly until the persistence of a category shrinks to zero. The Flow matrix has concepts and mathematics that are more straightforward than the Markov matrix. However, many scientists apply the Markov matrix by default because popular software packages offer no alternative to the Markov matrix, despite the conceptual and mathematical challenges that the Markov matrix poses. The Markov matrix extrapolates a constant transition proportion per time interval during whole-number multiples of the duration of the calibration time interval. The Markov extrapolation allows at most one incident per observation during each time interval but allows repeated incidents per observation through sequential time intervals. Many Markov extrapolations approach a steady state asymptotically through time as each category size approaches a constant. We use case studies concerning land change to illustrate the characteristics of the Flow and Markov matrices. The Flow and Markov extrapolations both deviate from the reference data during a validation time interval, implying there is no reason to prefer one matrix to the other in terms of correspondence with the processes that we analyzed. The two matrices differ substantially in terms of their underlying concepts and mathematical behaviors. Scientists should consider the ease of use and interpretation for each matrix when extrapolating transitions among categories. Full article
(This article belongs to the Special Issue New Approaches to Land Use/Land Cover Change Modeling)
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<p>The example data in the format of the (<b>a</b>) Raw matrix, (<b>b</b>) Flow matrix, and (<b>c</b>) Markov matrix. The gray cells are the matrix entries, and the white cells explain the entries. The rows of each matrix are the categories at the calibration interval’s start time <span class="html-italic">t</span><sub>0</sub>, and the columns are categories at the end time <span class="html-italic">t</span><sub>1</sub>. Numerical values assume the duration of the calibration time interval is one.</p> Full article ">Figure 2
<p>The three graphs on the left show the Flow extrapolation while the three graphs on the right show the Markov extrapolation from a calibration interval that starts at time 0 and ends at time 1. One legend applies to each pair of graphs. The upper pair shows the size of each category via (<b>a</b>) Flow and (<b>b</b>) Markov, where Markov shows persistence and gain from the preceding time point. The middle pair shows the cumulative number of incidents via (<b>c</b>) Flow and (<b>d</b>) Markov. The lower pair shows the temporal difference from time 0 in the bottom three segments via (<b>e</b>) Flow and (<b>f</b>) Markov.</p> Full article ">Figure 3
<p>(<b>a</b>) Map and (<b>b</b>) bars for the cumulative number of incidents during two time intervals along with the category at the end of the second time interval for categories Marsh, Water, and Other. Final means 1971 for the Calibration (33) bar, 2004 for the two Extrapolation (66) bars, and 2013 for the Validation (75) bar.</p> Full article ">Figure 4
<p>The three graphs on the left show the Flow extrapolation while the three graphs on the right show the Markov extrapolation from a calibration interval that starts at 1938 and ends at 1971. One legend applies to each pair of graphs. The upper pair shows the size of each category via (<b>a</b>) Flow and (<b>b</b>) Markov, where each Markov bar shows transitions from the previous 14 years. The middle pair shows the cumulative number of incidents via (<b>c</b>) Flow and (<b>d</b>) Markov. The lower pair shows differences from 1938 in the bottom three segments via (<b>e</b>) Flow and (<b>f</b>) Markov extrapolations.</p> Full article ">Figure 5
<p>(<b>a</b>) Map and (<b>b</b>) bars for the cumulative number of incidents during two time intervals along with the category at the end of the second time interval for categories Built, Forest, and Other. Final means 1985 for the first Calibration (14) bar whereas Final means 1999 for the other three bars.</p> Full article ">Figure 6
<p>The three graphs on the left show the Flow extrapolation while the three graphs on the right show the Markov extrapolation from a calibration interval that starts at 1971 and ends at 1985. One legend applies to each pair of graphs. The upper pair shows the size of each category via (<b>a</b>) Flow and (<b>b</b>) Markov, where each Markov bar shows transitions from the previous 14 years. The middle pair shows the cumulative number of incidents via (<b>c</b>) Flow and (<b>d</b>) Markov. The lower pair shows the difference from 1971 in the bottom three segments via (<b>e</b>) Flow and (<b>f</b>) Markov extrapolations.</p> Full article ">
21 pages, 6808 KiB  
Article
Spatiotemporal Characteristics and Habitat Quality Analysis in the Temperate Desert Sub-Region of Ordos Plateau, China
by Min Pei, Xiaohuang Liu, Jinjie Wang, Jiufen Liu, Xiaofeng Zhao, Hongyu Li, Ran Wang, Xinping Luo, Liyuan Xing, Chao Wang and Honghui Zhao
Land 2023, 12(7), 1470; https://doi.org/10.3390/land12071470 - 24 Jul 2023
Cited by 5 | Viewed by 1325
Abstract
Habitat quality has great significance in terms of regional ecological conservation and human welfare. In this study, we evaluated the spatial and temporal characteristics of land use and habitat quality in the temperate desert sub-region of the Ordos Plateau using patch-generating land use [...] Read more.
Habitat quality has great significance in terms of regional ecological conservation and human welfare. In this study, we evaluated the spatial and temporal characteristics of land use and habitat quality in the temperate desert sub-region of the Ordos Plateau using patch-generating land use simulation (PLUS) and integrated valuation of ecosystem services and trade-offs (InVEST) models. From 2000 to 2020, the areas of grassland, cropland, and unused land in the study area increased significantly; the areas of water bodies and woodland increased slightly; and the area of wasteland decreased significantly. Moreover, the habitat quality in the temperate desert subzone of the Ordos Plateau showed a trend of initial increase and then decrease between 2000 and 2020. The areas of lower and low habitat quality first decreased and then increased, and the overall area decreased over time. Conversely, the areas of high and higher habitat quality initially increased and then decreased, and the overall area increased over time. The area of medium habitat quality first decreased and then increased, although the overall change was minimal. Based on the PLUS model, the predicted habitat quality of the study area in 2025 under the natural development scenario was compared to that predicted under the ecological conservation scenario. The comparison of results showed higher habitat quality and lower habitat degradation under the ecological conservation development scenario. These results can be used to provide a scientific basis and decision reference for the sustainable use of land resources and encouragement of high-quality socio-economic development in the temperate desert sub-region of the Ordos Plateau. Full article
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<p>Location map of the Ordos Plateau.</p> Full article ">Figure 2
<p>Technology roadmap.</p> Full article ">Figure 3
<p>Land use change: (<b>a</b>) land use in 2020; (<b>b</b>) land use in 2015; (<b>c</b>) land use in 2010; (<b>d</b>) land use in 2005; (<b>e</b>) land use in 2000.</p> Full article ">Figure 4
<p>Direction of change in different land types: (<b>a</b>) cultivated land; (<b>b</b>) woodlands; (<b>c</b>) grasslands; (<b>d</b>) water bodies; (<b>e</b>) wasteland; (<b>f</b>) unused land.</p> Full article ">Figure 5
<p>Changes in habitat quality over time: (<b>a</b>) habitat quality in 2020; (<b>b</b>) habitat quality in 2015; (<b>c</b>) habitat quality in 2010; (<b>d</b>) habitat quality in 2005; (<b>e</b>) habitat quality in 2000.</p> Full article ">Figure 6
<p>Change in habitat degradation over time: (<b>a</b>) 2020; (<b>b</b>) 2015; (<b>c</b>) 2010; (<b>d</b>) 2005; (<b>e</b>) 2000.</p> Full article ">Figure 7
<p>Habitat quality level over time: (<b>a</b>) habitat quality rating for 2020; (<b>b</b>) habitat quality rating for 2015; (<b>c</b>) habitat quality rating for 2010; (<b>d</b>) habitat quality rating for 2005; (<b>e</b>) habitat quality rating for 2000.</p> Full article ">Figure 8
<p>Different landscape species change directions: (<b>a</b>) higher habitat quality; (<b>b</b>) high habitat quality; (<b>c</b>) medium habitat quality; (<b>d</b>) low habitat quality; (<b>e</b>) lower habitat quality.</p> Full article ">Figure 9
<p>Map of habitat quality and land use in the period 2000–2020: (<b>a</b>) 2020; (<b>b</b>) 2015; (<b>c</b>) 2010; (<b>d</b>) 2005; (<b>e</b>) 2000.</p> Full article ">Figure 10
<p>Land use and habitat quality grades under different conditions: (<b>a</b>) land use under ecological protection in 2025: (<b>b</b>) habitat quality level in 2025 under ecological conservation scenarios; (<b>c</b>) land use in the context of natural development in 2025; (<b>d</b>) habitat quality in 2025 under natural development scenarios.</p> Full article ">Figure 11
<p>The corresponding areas of individual habitat quality levels under different development conditions.</p> Full article ">
19 pages, 3993 KiB  
Article
Spatiotemporal Evolution and Correlation Analysis of Carbon Emissions in the Nine Provinces along the Yellow River since the 21st Century Using Nighttime Light Data
by Yaohui Liu, Wenyi Liu, Peiyuan Qiu, Jie Zhou and Linke Pang
Land 2023, 12(7), 1469; https://doi.org/10.3390/land12071469 - 23 Jul 2023
Cited by 7 | Viewed by 1577
Abstract
Monitoring carbon emissions is crucial for assessing and addressing economic development and climate change, particularly in regions like the nine provinces along the Yellow River in China, which experiences significant urbanization and development. However, to the best of our knowledge, existing studies mainly [...] Read more.
Monitoring carbon emissions is crucial for assessing and addressing economic development and climate change, particularly in regions like the nine provinces along the Yellow River in China, which experiences significant urbanization and development. However, to the best of our knowledge, existing studies mainly focus on national and provincial scales, with fewer studies on municipal and county scales. To address this issue, we established a carbon emission assessment model based on the “NPP-VIIRS-like” nighttime light data, aiming to analyze the spatiotemporal variation of carbon emissions in three different levels of nine provinces along the Yellow River since the 21st century. Further, the spatial correlation of carbon emissions at the county level was explored using the Moran’s I spatial analysis method. Results show that, from 2000 to 2021, carbon emissions in this region continued to rise, but the growth rate declined, showing an overall convergence trend. Per capita carbon emission intensity showed an overall upward trend, while carbon emission intensity per unit of GDP showed an overall downward trend. Its spatial distribution generally showed high carbon emissions in the eastern region and low carbon emissions in the western region. The carbon emissions of each city mainly showed a trend of “several”; that is, the urban area around the Yellow River has higher carbon emissions. Meanwhile, there is a trend of higher carbon emissions in provincial capitals. Moran’s I showed a trend of decreasing first and then increasing and gradually tended to a stable state in the later stage, and the pattern of spatial agglomeration was relatively fixed. “High–High” and “Low–Low” were the main types of local spatial autocorrelation, and the number of counties with “High–High” agglomeration increased significantly, while the number of counties with “Low–Low” agglomeration gradually decreased. The findings of this study provide valuable insights into the carbon emission trends of the study area, as well as the references that help to achieve carbon peaking and carbon neutrality goals proposed by China. Full article
(This article belongs to the Special Issue Regional Sustainable Management Pathways to Carbon Neutrality)
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<p>Geographical location of the study area.</p> Full article ">Figure 2
<p>The workflow of this study.</p> Full article ">Figure 3
<p>Temporal characteristics of provincial-level carbon emissions in the study area from 2000 to 2021.</p> Full article ">Figure 4
<p>Percentage of carbon emissions in the study area from 2000 to 2021.</p> Full article ">Figure 5
<p>Spatial characteristics of provincial-level carbon emissions in the study area from 2000 to 2021.</p> Full article ">Figure 6
<p>Temporal characteristics of per capita carbon emission intensity in the study area from 2000 to 2021.</p> Full article ">Figure 7
<p>Temporal characteristics of carbon emission intensity per unit GDP in the study area from 2000 to 2021.</p> Full article ">Figure 8
<p>Spatial characteristics of municipal-level carbon emissions in the study area from 2000 to 2021.</p> Full article ">Figure 9
<p>Spatial characteristics of county-level carbon emissions in the study area from 2000 to 2021.</p> Full article ">Figure 10
<p>LISA map of county-level carbon emissions in the study area from 2000 to 2021.</p> Full article ">
27 pages, 19470 KiB  
Article
Physical Environment Study on Social Housing Stock in Italian Western Alps for Healthy and Sustainable Communities
by Yuqing Zhang, Bin Li, Luca Caneparo, Qinglin Meng, Weihong Guo and Xiao Liu
Land 2023, 12(7), 1468; https://doi.org/10.3390/land12071468 - 23 Jul 2023
Cited by 5 | Viewed by 1787
Abstract
Climate change has reduced the comfort of community environments, and there is an urgent need to improve the health and well-being of low-income residents through design and technical measures. Therefore, this paper conducts research in the context of an ongoing social housing renovation [...] Read more.
Climate change has reduced the comfort of community environments, and there is an urgent need to improve the health and well-being of low-income residents through design and technical measures. Therefore, this paper conducts research in the context of an ongoing social housing renovation project in Aosta, Italy, in a cold winter and hot summer Alpine environment. The study combined interviews, field measurements, and multiple software simulations to analyze the home of an older adult experiencing energy deprivation. The study found that the indoor acoustic environment quality meets the requirements of various sound-related standards. Still, the lighting and thermal environment must be designed to reduce glare and western sun exposure, and the air quality could improve. Residents’ demand for renovation is low technology, low cost, and high comfort. Therefore, suggestions for combining active and passive transformation measures and maximizing the use of climate and resources are proposed. The lighting and thermal environment are optimized based on the green wisdom of the Haylofts building of the Walser family in the Alps: increase ventilation and reduce indoor air age to improve air quality. Overall, a comprehensive assessment of extreme climatic conditions facilitates the quantitative and qualitative study and control of social housing environments, improves occupant comfort, and decarbonizes such social building stock. Full article
(This article belongs to the Topic Sustainable Development and Coordinated Governance of Urban and Rural Areas under the Guidance of Ecological Wisdom)
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<p>Buildings and construction’s share of global final energy and energy-related CO<sub>2</sub> emissions, 2020 (Reference from: <a href="https://globalabc.org/resources/publications/2021-global-status-report-buildings-and-construction/" target="_blank">https://globalabc.org/resources/publications/2021-global-status-report-buildings-and-construction/</a>, accessed on 29 July 2022).</p> Full article ">Figure 2
<p>Aosta Social Housing: Location of the chosen building.</p> Full article ">Figure 3
<p>Aosta Social Housing: (<b>a</b>) Gazzera building top view; (<b>b</b>) Building second-floor plan.</p> Full article ">Figure 4
<p>(<b>a</b>) Annual incident solar radiation; (<b>b</b>) Psychrometric chart (The abscissa in the psychrometric chart represents the dry bulb temperature (°C), the ordinate represents the absolute humidity (g/kg)).</p> Full article ">Figure 5
<p>Comfort percentages, selected design techniques: (<b>a</b>) Passive solar heating; (<b>b</b>) Direct evaporative cooling; (<b>c</b>) Thermal mass effects; (<b>d</b>) Natural ventilation; (<b>e</b>) Indirect evaporative cooling; (<b>f</b>) Exposed mass + Night-purge ventilation.</p> Full article ">Figure 6
<p>Outdoor Environment (from 30 May to 6 June 2022).</p> Full article ">Figure 7
<p>Environment instruments: (<b>a</b>) Monitoring position (outdoor and indoor); (<b>b</b>) Preparation before measuring.</p> Full article ">Figure 8
<p>Acoustic environment results, Equivalent Continuous Level (Leq, dB (A)).</p> Full article ">Figure 9
<p>Thermal environment results, Air Temperature (°C).</p> Full article ">Figure 10
<p>Thermal environment results, Relative Humidity (%).</p> Full article ">Figure 11
<p>Indoor air quality results, TVOC (ppm).</p> Full article ">Figure 12
<p>Cumulative insolation simulation results.</p> Full article ">Figure 13
<p>Retrofit design with wisdom from Walser haylofts. (<b>A</b>): before renovation; (<b>B</b>): after renovation. (<a href="https://www.alagna.it/en/routes&#x2013;walks&#x2013;trekking&#x2013;monterosa/the&#x2013;antique&#x2013;hamlets/" target="_blank">https://www.alagna.it/en/routes–walks–trekking–monterosa/the–antique–hamlets/</a>, accessed on 12 June 2023).</p> Full article ">Figure 14
<p>Phoenics 2019 software simulation results: (<b>a</b>) PMV (before renovation); (<b>b</b>) PMV (after renovation).</p> Full article ">
22 pages, 7081 KiB  
Article
Spatial Spillover and Convergent Mechanism of Urban–Rural Financial Imbalances: Evidence from China
by Ying Yu, Yong Li, Pengfei Ge and Hua Rong
Land 2023, 12(7), 1467; https://doi.org/10.3390/land12071467 - 23 Jul 2023
Viewed by 958
Abstract
Based on the perspective of financial geography, this study analyzed the convergent mechanism of urban–rural financial imbalances under the influence of spatial spillover through the theoretical framework of spatial process, spatial action, and spatial convergence. Then, we empirically tested the spatial spillover, spatial [...] Read more.
Based on the perspective of financial geography, this study analyzed the convergent mechanism of urban–rural financial imbalances under the influence of spatial spillover through the theoretical framework of spatial process, spatial action, and spatial convergence. Then, we empirically tested the spatial spillover, spatial difference, and spatial convergence of urban–rural financial imbalances in China from 1991 to 2021. We found that urban–rural financial imbalances showed significant spillover effects and heterogeneous characteristics. Spillovers based on financial radiation and exclusion were apparent during the urban financial agglomeration stage, decreasing with geographical distance, and had an essential impact on the convergence of provincial urban–rural financial imbalance. As such spillovers declined during the financial diffusion period, new spillovers at the technology and information dimensions, which were less geographically constrained, came into play and contributed to urban–rural financial convergence. The policy implications are that it is necessary to pay attention to the spatial interaction of urban–rural financial inequality, correctly use their spillover effects to achieve financial convergence, and activate new spatial spillover channels according to their spatial interaction mode changes for further urban and rural financial convergence. Full article
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<p>Convergence of urban–rural financial imbalances under spatial spillover effects. Notes: Drawn by the author.</p> Full article ">Figure 2
<p>Space and temporal evolution of urban–rural financial imbalances in China from 1991 to 2019. Note: The eastern region includes Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, and Hainan. The central region includes Shanxi, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, and Hunan. The western region includes Inner Mongolia, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang.</p> Full article ">Figure 2 Cont.
<p>Space and temporal evolution of urban–rural financial imbalances in China from 1991 to 2019. Note: The eastern region includes Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, and Hainan. The central region includes Shanxi, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, and Hunan. The western region includes Inner Mongolia, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang.</p> Full article ">Figure 3
<p>Quartiles of urban–rural financial imbalances.</p> Full article ">Figure 4
<p>Relationship between spatial coefficients and geographical distance. Note: The spatial spillover effects are significant in the financial agglomeration stage (1991–2003), so we choose this period for analysis.</p> Full article ">
17 pages, 2275 KiB  
Article
Reputation, Network, and Performance: Exploring the Diffusion Mechanism of Local Governments’ Behavior during Inter-Governmental Environmental Cooperation
by Yihang Zhao, Jing Xiong and De Hu
Land 2023, 12(7), 1466; https://doi.org/10.3390/land12071466 - 23 Jul 2023
Cited by 1 | Viewed by 1505
Abstract
The selective behavior of local governments during regional environmental cooperation could generate a diffusion effect through the black box of reputation mechanism. This study incorporates the reputation mechanism, social capital, and environmental governance performance into a unified analysis framework, empirically testing the moderating [...] Read more.
The selective behavior of local governments during regional environmental cooperation could generate a diffusion effect through the black box of reputation mechanism. This study incorporates the reputation mechanism, social capital, and environmental governance performance into a unified analysis framework, empirically testing the moderating effect of the implementation rate of environmental cooperative projects (indicating reputation) on the relationship between two types of social capital and environmental governance performance among cities in the Yangtze River Delta (YRD) and Beijing–Tianjin–Hebei (BTH) regions. The inter-governmental environmental cooperation news and policies are collected by Data Capture technology as a dataset, and a set of social-economic data is also adopted. The spatial econometric regression results show that an increase in reputation could both strengthen the leadership and coordination ability (bridging social capital) of the central cities in the YRD and BTH regions, thus improving their environmental governance performance. However, the bonding social capital path could only significantly work in the BTH region, which unexpectedly increases pollutant emission through excessive internal cohesion. The results indicate that a “community of entangled interest” should be constructed among cities within urban agglomerations, which requires local governments to weaken the concept of their administrative boundary. At the same time, in order to avoid excessive internal condensation, a clear division of rights and responsibilities is also necessary during continuous inter-governmental environmental cooperation. We believe that these findings could provide empirical evidence for local governments to avoid failing to the traps of “agglomeration shadow”. Full article
(This article belongs to the Special Issue Regional Sustainable Development of Yangtze River Delta, China II)
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<p>The time-varying trend of the inter-governmental cooperation policies and news text amounts in YRD and BTH regions. (Notes: We have collected the inter-governmental cooperation policies and news texts during 2009–2020 in the field of education, environmental protection, infrastructure, medical treatment, social security and tourism. It could be observed that the amount gap between cooperative implementation and cooperative willingness is the hugest during regional environmental cooperation).</p> Full article ">Figure 2
<p>The simplified regional analytic model.</p> Full article ">Figure 3
<p>The theoretical analytic framework.</p> Full article ">Figure 4
<p>The inter-governmental environmental cooperation network in YRD. (<b>a</b>) Willingness network; (<b>b</b>) Implementation network. (Note: the willingness network density is 4.3020, while implementation network density is 1.7721).</p> Full article ">Figure 5
<p>The inter-governmental environmental cooperation network in BTH. (<b>a</b>) Willingness network; (<b>b</b>) Implementation network. (Note: the willingness network density is 7.411, while implementation network density is 3.949).</p> Full article ">
16 pages, 2734 KiB  
Article
Strategies for Green Space Management in Mountain Cities Based on the Habitat Suitability for Urban Birds Breeding
by Xiongbin Zhu, Sucharita Srirangam and TamilSalvi Mari
Land 2023, 12(7), 1465; https://doi.org/10.3390/land12071465 - 22 Jul 2023
Cited by 1 | Viewed by 1342
Abstract
The reproduction suitability of urban birds reflects the health status and service level of urban ecosystems. Therefore, studying the relationship between the nest density of urban birds and environmental factors has certain reference significance for guiding green space management. In this study, 67 [...] Read more.
The reproduction suitability of urban birds reflects the health status and service level of urban ecosystems. Therefore, studying the relationship between the nest density of urban birds and environmental factors has certain reference significance for guiding green space management. In this study, 67 green spaces of Liupanshui city in the Wumeng Mountain Area were selected as study sites. Through the statistics of the number of bird’s nests in the plots in 2020, a stepwise regression analysis was conducted on 10 environment-influencing factors. The results show that the nest density of birds in urban green space is not significantly correlated with the plot size, noise, light pollution, vegetation diversity, proportion of paved land, proportion of native plants, or distance from water body, but is significantly correlated with the canopy coverage of arbor, spatial openness, and distance from non-artificial environment to plot. The research identified the environmental factors affecting nest density, and frames a method to compare the density of bird’s nests in urban green space. Based on this, strategies for the construction and management of green space are put forward, so as to provide reference for ecological city construction and alleviate the correlation between the expansion of urban construction land and the deterioration of bird habitats. Full article
(This article belongs to the Special Issue Sustainable Development in Urban and Regional Planning: New Findings, New Tools and New Perspectives)
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<p>Location Map of Liupanshui City.</p> Full article ">Figure 2
<p>Schematic diagram of the study area and surrounding terrain.</p> Full article ">Figure 3
<p>Number map of urban green space in Liupanshui City (The numbers in the figure represent the plot number of green space).</p> Full article ">Figure 4
<p>Number map of verification sites in Xuanwei City (The numbers in the figure represent the plot number of green space).</p> Full article ">Figure 5
<p>Schematic diagram of space opening calculation.</p> Full article ">Figure 6
<p>Schematic diagram of the relationship between green space location and land development intensity (The numbers in the figure represent the plot number of green space).</p> Full article ">
19 pages, 6100 KiB  
Review
Mountainous Areas: Alleviating the Shortage of Cultivated Land Caused by Changing Dietary Structure in China
by Yuhan Wang, Chenyujing Yang, Yuanyuan Zhang and Yongji Xue
Land 2023, 12(7), 1464; https://doi.org/10.3390/land12071464 - 22 Jul 2023
Cited by 4 | Viewed by 2062
Abstract
Achieving food security and improving nutrition is one of the United Nations Sustainable Development Goals. With rapid socioeconomic development, the dietary structure of the Chinese population has changed significantly, leading to increased demand for cultivated land. At the same time, rapid urbanization has [...] Read more.
Achieving food security and improving nutrition is one of the United Nations Sustainable Development Goals. With rapid socioeconomic development, the dietary structure of the Chinese population has changed significantly, leading to increased demand for cultivated land. At the same time, rapid urbanization has continuously reduced the amount of cultivated land in China, and there is an urgent necessity for the nation to alleviate the shortage of cultivated land to meet the population’s evolving dietary consumption needs. A review of the literature indicates that the use of mountainous areas to produce agricultural products for the population can effectively reduce the use of cultivated land on the plains and mitigate the shortage of cultivated land to meet dietary consumption needs. According to the different natural and socioeconomic conditions of mountainous areas, this study concludes that the adoption of mountain hillside, mountain understory, and mountainous limited cultivated land use patterns to develop agricultural production in mountainous areas is an effective approach to address the shortage of cultivated land caused by changes in the Chinese dietary structure. Full article
(This article belongs to the Section Water, Energy, Land and Food (WELF) Nexus)
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<p>Rural residents’ per capita consumption of major foodstuffs. Between 2005 and 2021, per capita consumption of staple food grain in rural areas decreased from 208.85 kg to 170.8 kg; per capita consumption of vegetables and edible mushrooms increased slightly from 102.28 kg to 107 kg; per capita consumption of meat increased from 22.42 kg to 30.9 kg; per capita consumption of aquatic products and total consumption of eggs and milk increased from 12.15 kg to 33.2 kg (data from the China Statistical Yearbook 2005–2021). The dashed line in the figure shows the trend in per capita consumption of each of the major foodstuffs.</p> Full article ">Figure 2
<p>Study area: Zigui County, Hubei Province.</p> Full article ">Figure 3
<p>Example of Stereoscopic cultivation in Zigui County, Hubei Province, China. (<b>a</b>) Zigui County mountainous area’s three layers of green industry, according to the altitude economic gradient layout of forests, forming a low mountain navel orange belt; a medium mountain tea, walnut, chestnut belt; and a high mountain vegetable, walnut, and Chinese herbal medicine belt. (<b>b</b>) In the low-altitude zone, Zigui County planted oranges and navel oranges in the low mountain belt below 500 m above sea level, where the temperature and heat are amenable to cultivation (<a href="http://www.yichang.gov.cn/content-62936-1038659-1.html" target="_blank">http://www.yichang.gov.cn/content-62936-1038659-1.html</a> (accessed on 13 March 2023)). (<b>c</b>) The medium-altitude zone shows walnuts grown on sloping land (<a href="http://zigui.cjyun.org/p/29685.html" target="_blank">http://zigui.cjyun.org/p/29685.html</a> (accessed on 13 March 2023)). (<b>d</b>) The high-altitude zone shows alpine vegetables grown in the mountains above 800 m (<a href="http://www.yichang.gov.cn/html/zhengwuyizhantong/zhengwuzixun/tupianxinwen/2017/0731/984741.html" target="_blank">http://www.yichang.gov.cn/html/zhengwuyizhantong/zhengwuzixun/tupianxinwen/2017/0731/984741.html</a> (accessed on 13 March 2023)). These photographs are from the author’s drawings and the Yichang Municipal Government website.</p> Full article ">Figure 4
<p>Study area: Xiaoxinganling Mountains, Yichun City, Heilongjiang Province.</p> Full article ">Figure 5
<p>Example of raising pigs under forests in Xiaoxinganling Mountains, Yichun City, Heilongjiang Province, China. (<b>a</b>) In Yichun, pigs are free-ranging in the forest with plenty of space to move around (<a href="https://yichun.dbw.cn/system/2009/12/21/052273439.shtml" target="_blank">https://yichun.dbw.cn/system/2009/12/21/052273439.shtml</a> (accessed on 13 March 2023)). (<b>b</b>–<b>d</b>) Pigs free-ranging in the forest (<a href="https://heilongjiang.dbw.cn/system/2017/08/31/057765807.shtml" target="_blank">https://heilongjiang.dbw.cn/system/2017/08/31/057765807.shtml</a> (accessed on 13 March 2023); <a href="https://www.yc.gov.cn/xwzx/ycyw/2018/12/105940.html" target="_blank">https://www.yc.gov.cn/xwzx/ycyw/2018/12/105940.html</a> (accessed on 13 March 2023); <a href="http://nynct.gxzf.gov.cn/xxgk/ztjj/lsxztgd/gxhy/yqygypp/qzs/t2053503.shtml" target="_blank">http://nynct.gxzf.gov.cn/xxgk/ztjj/lsxztgd/gxhy/yqygypp/qzs/t2053503.shtml</a> (accessed on 13 March 2023)). <a href="#land-12-01464-f005" class="html-fig">Figure 5</a>a,b are from official government news sites; <a href="#land-12-01464-f005" class="html-fig">Figure 5</a>c,d are from government websites.</p> Full article ">Figure 6
<p>Study area: Hani Terraces, Yuanyang County, Honghe Autonomous Prefecture, Yunnan Province.</p> Full article ">Figure 7
<p>Example of the rice–fish–duck integrated farming model in Hani terraces, Honghe Autonomous Prefecture, Yunnan Province, China. (<b>a</b>) The Hani have restructured the hills into layers of terraces to expand the area under cultivation (<a href="https://difang.gmw.cn/yn/2019-09/20/content_33175447.htm" target="_blank">https://difang.gmw.cn/yn/2019-09/20/content_33175447.htm</a> (accessed on 13 March 2023)). (<b>b–d</b>) In the terraces, ducks are stocked on the water and underwater, and fish fry are placed in the rice fields, where fish, ducks, and rice are cultivated together (<a href="https://baijiahao.baidu.com/s?id=1744836957018380136&amp;wfr=spider&amp;for=pc" target="_blank">https://baijiahao.baidu.com/s?id=1744836957018380136&amp;wfr=spider&amp;for=pc</a> (accessed on 13 March 2023); <a href="http://www.jiangsu.gov.cn/art/2019/7/4/art_64753_8607835.html" target="_blank">http://www.jiangsu.gov.cn/art/2019/7/4/art_64753_8607835.html</a> (accessed on 13 March 2023); <a href="http://www.moa.gov.cn/ztzl/zywhycsl/dypzgzywhyc/201305/t20130531_3480248.htm" target="_blank">http://www.moa.gov.cn/ztzl/zywhycsl/dypzgzywhyc/201305/t20130531_3480248.htm</a> (accessed on 13 March 2023)). <a href="#land-12-01464-f007" class="html-fig">Figure 7</a>a is from a newspaper report; <a href="#land-12-01464-f007" class="html-fig">Figure 7</a>b is from Xinhua report; <a href="#land-12-01464-f007" class="html-fig">Figure 7</a>c is from the People’s Government of Jiangsu Province; and <a href="#land-12-01464-f007" class="html-fig">Figure 7</a>d is from the Ministry of Agriculture and Rural Affairs of the People’s Republic of China.</p> Full article ">Figure 7 Cont.
<p>Example of the rice–fish–duck integrated farming model in Hani terraces, Honghe Autonomous Prefecture, Yunnan Province, China. (<b>a</b>) The Hani have restructured the hills into layers of terraces to expand the area under cultivation (<a href="https://difang.gmw.cn/yn/2019-09/20/content_33175447.htm" target="_blank">https://difang.gmw.cn/yn/2019-09/20/content_33175447.htm</a> (accessed on 13 March 2023)). (<b>b–d</b>) In the terraces, ducks are stocked on the water and underwater, and fish fry are placed in the rice fields, where fish, ducks, and rice are cultivated together (<a href="https://baijiahao.baidu.com/s?id=1744836957018380136&amp;wfr=spider&amp;for=pc" target="_blank">https://baijiahao.baidu.com/s?id=1744836957018380136&amp;wfr=spider&amp;for=pc</a> (accessed on 13 March 2023); <a href="http://www.jiangsu.gov.cn/art/2019/7/4/art_64753_8607835.html" target="_blank">http://www.jiangsu.gov.cn/art/2019/7/4/art_64753_8607835.html</a> (accessed on 13 March 2023); <a href="http://www.moa.gov.cn/ztzl/zywhycsl/dypzgzywhyc/201305/t20130531_3480248.htm" target="_blank">http://www.moa.gov.cn/ztzl/zywhycsl/dypzgzywhyc/201305/t20130531_3480248.htm</a> (accessed on 13 March 2023)). <a href="#land-12-01464-f007" class="html-fig">Figure 7</a>a is from a newspaper report; <a href="#land-12-01464-f007" class="html-fig">Figure 7</a>b is from Xinhua report; <a href="#land-12-01464-f007" class="html-fig">Figure 7</a>c is from the People’s Government of Jiangsu Province; and <a href="#land-12-01464-f007" class="html-fig">Figure 7</a>d is from the Ministry of Agriculture and Rural Affairs of the People’s Republic of China.</p> Full article ">
17 pages, 3563 KiB  
Article
The Impact of Intra-City and Inter-City Innovation Networks on City Economic Growth: A Case Study of the Yangtze River Delta in China
by Xianzhong Cao, Bo Chen, Yi Guo and Zhenzhen Yi
Land 2023, 12(7), 1463; https://doi.org/10.3390/land12071463 - 22 Jul 2023
Cited by 1 | Viewed by 1488
Abstract
Innovation networks promote regional innovation and economic growth. Using the patent data of cooperative inventions and the panel data of socio-economic statistics for 2010–2019, this study quantitatively analyzes the spatial structure evolution of intra-city and inter-city innovation networks for 41 cities in the [...] Read more.
Innovation networks promote regional innovation and economic growth. Using the patent data of cooperative inventions and the panel data of socio-economic statistics for 2010–2019, this study quantitatively analyzes the spatial structure evolution of intra-city and inter-city innovation networks for 41 cities in the Yangtze River Delta and their influence on economic growth. This study shows that these networks are increasingly connected and have a highly similar Z-shaped spatial structure. City economic growth is generally high, relatively stable, and mainly positively influenced by inter-city innovation networks. Intra-city innovation networks have no significant effect on economic growth; however, they are complementary to the inter-city ones. Full article
(This article belongs to the Special Issue Regional Sustainable Development of Yangtze River Delta, China II)
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<p>Diagram of the intra-city and inter-city innovation cooperation networks in the Yangtze River Delta from 2010 to 2019.</p> Full article ">Figure 2
<p>Illustration of the intra-city and inter-city innovation networks in the Yangtze River Delta from 2010 to 2019.</p> Full article ">Figure 2 Cont.
<p>Illustration of the intra-city and inter-city innovation networks in the Yangtze River Delta from 2010 to 2019.</p> Full article ">Figure 3
<p>Calculated value of total factor productivity of cities in the Yangtze River Delta from 2010 to 2019.</p> Full article ">Figure 4
<p>The spatial dynamic evolution of total factor productivity in cities in the Yangtze River Delta from 2010 to 2019.</p> Full article ">Figure 5
<p>Scatter diagram of the distribution of the intra-city and inter-city innovation networks in the Yangtze River Delta from 2010 to 2019.</p> Full article ">Figure 6
<p>Diagram of the interaction mechanism between urban innovation networks and regional growth in the Yangtze River Delta.</p> Full article ">
21 pages, 3064 KiB  
Article
Building a Cadastral Map of Europe through the INSPIRE and Other Related Initiatives
by Vlado Cetl, Sanja Šamanović, Olga Bjelotomić Oršulić and Anka Lisec
Land 2023, 12(7), 1462; https://doi.org/10.3390/land12071462 - 22 Jul 2023
Cited by 2 | Viewed by 2659
Abstract
Digital cadastral maps with accompanying land-related attributes have become a fundamental dataset for many application fields, e.g., spatial planning and development, protecting state lands, securing of land tenure, facilitating land reforms, agriculture, forestry, land management, taxation, etc. In order to fulfil its main [...] Read more.
Digital cadastral maps with accompanying land-related attributes have become a fundamental dataset for many application fields, e.g., spatial planning and development, protecting state lands, securing of land tenure, facilitating land reforms, agriculture, forestry, land management, taxation, etc. In order to fulfil its main objectives, cadastral data needs to be available and accessible, which is, among the others, emphasized also within the United Nations Framework for Effective Land Administration (FELA). This is not only important on the national level but also beyond, including at the European level where use cases and consequently demand for pan-European data sets have evolved in recent years. In order to satisfy these needs, several initiatives regarding cadastral and other geospatial data have been launched in the last 20 years. It started with the Permanent Committee on Cadastre in the European Union, the European Land Information Service, INSPIRE, UN-GGIM Europe and recent European policies on open data and high-value datasets. Our main question is, did those initiatives result in the possibility of building a cadastral map of Europe or not? Is it possible to create a cadastral map of Europe on the desktop or an open online GIS application? Within the paper, we take the opportunity to reflect on the development and implementation of European spatial data infrastructure (INSPIRE) with the main focus on the availability and accessibility of cadastral data. We also take into consideration other European initiatives related to cadastral data. The overall findings show that there is still work to be carried out. Technological developments and recent policy initiatives will certainly be drivers for future improvement. Full article
(This article belongs to the Special Issue New Insights in Integrated Land Management)
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<p>Research methodology.</p> Full article ">Figure 2
<p>INSPIRE themes, organised in three annexes. Source: INSPIRE Directive.</p> Full article ">Figure 3
<p>Distributed Service Oriented Architecture of INSPIRE. Source: European Commission, Joint Research Centre.</p> Full article ">Figure 4
<p>Available cadastral parcel datasets in EU MS and EFTA countries. Source: INSPIRE Geoportal, European Commission, Joint Research Centre.</p> Full article ">Figure 5
<p>Metadata records for cadastral data.</p> Full article ">Figure 6
<p>Relationship between regional and national cadastral data sets.</p> Full article ">Figure 7
<p>Indicators representing the percentage of spatial data sets available through viewing services (NSi2.1) and downloading (NSi2.2) services.</p> Full article ">Figure 8
<p>Countries (green) with access to cadastral data and countries (red) without access.</p> Full article ">
19 pages, 3719 KiB  
Article
Differences in High-Quality Development and Its Influencing Factors between Yellow River Basin and Yangtze River Economic Belt
by Yiwei Wang and Ningze Yang
Land 2023, 12(7), 1461; https://doi.org/10.3390/land12071461 - 21 Jul 2023
Cited by 4 | Viewed by 1388
Abstract
As a national strategy, the development of the Yangtze River Economic Belt (YREB) and the ecological protection and high-quality development (HQD) of the Yellow River Basin (YRB) are of great significance for promoting the HQD of the regional economy. Based on the panel [...] Read more.
As a national strategy, the development of the Yangtze River Economic Belt (YREB) and the ecological protection and high-quality development (HQD) of the Yellow River Basin (YRB) are of great significance for promoting the HQD of the regional economy. Based on the panel data in the YRB and the YREB from 2006 to 2019, this paper constructed an evaluation index system of HQD with five dimensions of “innovation development, coordination development, green development, openness development, and sharing development”, and we used the entropy weight method, kernel density method, and Tobit panel model to analyze the differences in the HQD and the similarities and differences of the influencing factors between the two regions. The research findings were as follows: (1) The HQD of the YRB and the YREB was consistent with the national trend, showing a fluctuating upward trend. The HQD of the YRB was always lower than that of the YREB. The kernel density curves in both regions had a rightward trailing pattern, with polarization and unbalanced development. (2) From the perspective of the spatial distribution pattern, the HQD of the YRB presented a spatial distribution characteristic of “high at both ends and low in the middle”. In contrast, the HQD of the YREB maintained the characteristic of “high in the east and low in the west”. (3) The level of human capital, the level of foreign direct investment, and the economic scale played a significant positive role in improving the HQD of the YRB. The level of human capital, urbanization, foreign direct investment, and economic scale significantly improved the HQD of the YREB. Full article
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<p>Map of the study area.</p> Full article ">Figure 2
<p>Trends in high-quality development in the Yellow River Basin, the Yangtze River Economic Belt, and the country from 2006 to 2019.</p> Full article ">Figure 3
<p>Kernel density of the Yellow River Basin.</p> Full article ">Figure 4
<p>Kernel density of the Yangtze River Economic Belt.</p> Full article ">Figure 5
<p>Evolution of spatial distribution pattern of high-quality development level in the Yellow River Basin in 2006, 2010, 2015, and 2019.</p> Full article ">Figure 6
<p>Evolution of the spatial distribution pattern of high-quality development in the Yangtze River Economic Belt in 2006, 2010, 2015, and 2019.</p> Full article ">
22 pages, 15383 KiB  
Article
Refuge Green Space Equity: A Case Study of Third Ring Road on Chengdu
by Yilun Cao, Yuhan Guo, Yuhao Fang and Xinwei He
Land 2023, 12(7), 1460; https://doi.org/10.3390/land12071460 - 21 Jul 2023
Cited by 1 | Viewed by 1729
Abstract
As part of urban green space and emergency shelters, refuge green spaces (RGS) contribute significantly to the resilience of cities to natural disasters. In contrast, few studies have been conducted to assess the equity of RGS in relation to their planning layout. The [...] Read more.
As part of urban green space and emergency shelters, refuge green spaces (RGS) contribute significantly to the resilience of cities to natural disasters. In contrast, few studies have been conducted to assess the equity of RGS in relation to their planning layout. The presented research aims to quantitatively evaluate the equity of RGS within Chengdu’s Third Ring Road, and to propose corresponding optimization measures in conjunction with future green space planning. The rapid evacuation capacity of the RGS was evaluated by calculating the equity of the RGS in walking modes of 5, 10 and 15 min using an improved three-step floating catchment area method (3SFCA). Based on the results, RGS had an average equity in the study area. The total number of RGS within the Third Ring Road of Chengdu was insufficient, with an uneven spatial distribution and a structure to be optimized. The rapid evacuation capacity of RGS in 5 and 10 min needs to be further improved. The short-term resettlement capacity of RGS after 15 min was relatively good. Using Moran’s I index, the RGS equity and house price results were analyzed and no significant aggregation and polarization were observed. Following the evaluation, recommendations are made for optimizing and adding future RGS in accordance with Chengdu Green Space System Planning. The equity of RGS has been significantly improved after optimization, which can meet the needs of over 90% of residents for 15 min. This study provided feasible suggestions for the layout and structural optimization of the future RGS within the Third Ring Road of Chengdu, which aimed to create a RGS network with complex functions, to meet the multiple needs of citizens. Full article
(This article belongs to the Special Issue Constructed Green Areas as a Challenge for Spatial Planning at the Local and Regional Levels)
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<p>Map of Chengdu Ring Road.</p> Full article ">Figure 2
<p>Map of RGS in Research Area.</p> Full article ">Figure 3
<p>(<b>a</b>) Population distribution map; (<b>b</b>) house price distribution map.</p> Full article ">Figure 4
<p>Map of RGS coverage.</p> Full article ">Figure 5
<p>RGS Overall 5 Minutes Equity.</p> Full article ">Figure 6
<p>RGS Overall 10 minutes equity.</p> Full article ">Figure 7
<p>RGS overall 15 Minutes equity.</p> Full article ">Figure 8
<p>5 minutes equity of emergency sheltered green space.</p> Full article ">Figure 9
<p>10 minutes equity of temporary sheltered green space.</p> Full article ">Figure 10
<p>15 minutes equity of disaster prevention park space.</p> Full article ">Figure 11
<p>RGS judgment matrix construction.</p> Full article ">Figure 12
<p>Map of RGS additions locations.</p> Full article ">Figure 13
<p>Satellite Map of Future RGS Additions.</p> Full article ">Figure 14
<p>Overall RGS equity statistics before and after the additions.</p> Full article ">Figure 15
<p>RGS classification equity chart before and after additions.</p> Full article ">Figure 16
<p>Map of house price—5 min RGS equity.</p> Full article ">Figure 17
<p>(<b>a</b>) Map of house price—10 min RGS equity; (<b>b</b>) map of house price—15 min RGS equity.</p> Full article ">
17 pages, 1158 KiB  
Article
Interplay of Urbanization and Ecological Environment: Coordinated Development and Drivers
by Ruixu Chen, Yang Chen, Oleksii Lyulyov and Tetyana Pimonenko
Land 2023, 12(7), 1459; https://doi.org/10.3390/land12071459 - 21 Jul 2023
Cited by 22 | Viewed by 3569
Abstract
The interplay between urbanization and ecological environmental efficiency has gained increasing significance in the context of sustainable development, as rapid urban growth poses challenges to resource consumption, greenhouse gas emissions, and the overall ecological well-being of urban areas. Understanding and analyzing the coordinated [...] Read more.
The interplay between urbanization and ecological environmental efficiency has gained increasing significance in the context of sustainable development, as rapid urban growth poses challenges to resource consumption, greenhouse gas emissions, and the overall ecological well-being of urban areas. Understanding and analyzing the coordinated development of urbanization and ecological environmental efficiency, as well as assessing the influence of drivers on this relationship, is crucial for developing effective policies and strategies that promote environmentally sustainable urban development. This study establishes an urbanization index based on four key aspects: economy, society, population, and ecology. This investigation focuses on 30 provinces in China spanning from 2011 to 2020. The following methods are applied: global Malmquist–Luenberger productivity index, entropy method, TOPSIS model, coupled coordination degree model, panel-corrected standard error (PCSE), and feasible generalized least squares (FGLS) models. The empirical results demonstrate a favorable level of coordinated development between urbanization and the ecological environment overall, with more pronounced regional evolution trends. The trade openness, energy structure, and digitalization level play significant roles in effectively promoting the coordinated development of urbanization and the ecological environment to varying extents. The growth of trade openness and digitalization level promote coordinated development between urbanization and the ecological environment by 0.125 and 0.049, respectively. However, the increase in the energy structure decreases it by 0.509. These results have significant implications for policymakers, urban planners, and stakeholders, emphasizing the need for a balanced approach that prioritizes ecological environmental protection in urbanization efforts. This study underscores the importance of sustainable urban development strategies to ensure long-term ecological and environmental sustainability. Full article
(This article belongs to the Special Issue Dynamics of Urbanization and Ecosystem Services Provision II)
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<p>The average value of the coupling and coordination degree of urbanization and ecological environment efficiency in 30 provinces in China.</p> Full article ">Figure 2
<p>National and four major regional evolution trends. (<b>a</b>) Whole country; (<b>b</b>) East; (<b>c</b>) Central; (<b>d</b>) West; (<b>e</b>) East–north.</p> Full article ">Figure 2 Cont.
<p>National and four major regional evolution trends. (<b>a</b>) Whole country; (<b>b</b>) East; (<b>c</b>) Central; (<b>d</b>) West; (<b>e</b>) East–north.</p> Full article ">
15 pages, 1279 KiB  
Article
Decoupling Analysis of Carbon Emissions and Forest Area in China from 2004 to 2020
by Shusen Zhu, Hui Sun, Xuechao Xia and Zedong Yang
Land 2023, 12(7), 1458; https://doi.org/10.3390/land12071458 - 21 Jul 2023
Cited by 1 | Viewed by 1229
Abstract
As the largest ecological carbon sequestration systems on the Earth, forests play a significant role in reducing carbon dioxide, and countries around the world are actively expanding their forest areas. However, China’s carbon emissions and forest area have shown an upward trend, which [...] Read more.
As the largest ecological carbon sequestration systems on the Earth, forests play a significant role in reducing carbon dioxide, and countries around the world are actively expanding their forest areas. However, China’s carbon emissions and forest area have shown an upward trend, which has seriously hindered the implementation of forestry carbon sequestration projects. This paper analyzed the temporal variation, spatial distribution, and deviation degree of the forest area and carbon emissions in China from 2004 to 2020 by using a decoupling model and a coordination model. Firstly, according to the decoupling model, the national carbon emissions and forest area are negatively decoupled. At the provincial level, Beijing, Shanghai, Jiangsu, Guizhou, Yunnan, and Gansu have weak decoupling. Expansive link areas include Shanxi, Henan, Hubei, Ningxia, and Xinjiang. The other 19 provinces show expansive negative decoupling. Secondly, according to the coordination model, national carbon emissions are coordinated to the forest area. Zhejiang, Fujian, Jiangxi, and Guangdong are basically coordinated provinces. More coordinated provinces include Ningxia. The other 25 provinces are coordinated provinces. Finally, according to the comprehensive measurement model, Inner Mongolia, Qinghai, Shaanxi, Hainan, Jilin, Anhui, Liaoning, and Heilongjiang are high-quality expansive negative decoupling provinces. Chongqing, Hunan, Tianjin, Shandong, Hebei, and Guangxi are moderate to strong expansive negative decoupling provinces. This study not only provides a new perspective for analyzing forest carbon sinks, but also provides theoretical guidance for enhancing the natural carbon sink capacity, helping to achieve global carbon peak and carbon neutrality goals. Full article
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<p>Change trend for China’s forest area and carbon emissions from 2004 to 2020.</p> Full article ">Figure 2
<p>Spatial pattern for the average growth and the average growth rate of the forest area in China from 2004 to 2020.</p> Full article ">Figure 3
<p>Spatial pattern for the average growth and the average growth rate of carbon emissions in China from 2004 to 2020.</p> Full article ">
25 pages, 4944 KiB  
Article
Tactical Urbanism Interventions for the Urban Environment: Which Economic Impacts?
by Marco Rossitti, Alessandra Oppio, Francesca Torrieri and Marta Dell’Ovo
Land 2023, 12(7), 1457; https://doi.org/10.3390/land12071457 - 21 Jul 2023
Cited by 1 | Viewed by 4054
Abstract
In the last decades, the emergence of new social, environmental, and economic demands, exacerbated by the COVID-19 pandemic, has led urban planning to innovate its themes, methods, and approaches. In this context, temporary urbanism has emerged as a mainstream approach. How-ever, the impacts [...] Read more.
In the last decades, the emergence of new social, environmental, and economic demands, exacerbated by the COVID-19 pandemic, has led urban planning to innovate its themes, methods, and approaches. In this context, temporary urbanism has emerged as a mainstream approach. How-ever, the impacts of temporary approaches to urban planning are far from being fully understood. In this light, this study focuses on one of the mainstream approaches to temporary urbanism, tactical urbanism, and tries to understand its economic impacts on contemporary cities. Indeed, despite the growing interest in tactical urbanism interventions and their value as an urban regeneration tool, there are no specific reflections focused on investigating their economic effects. Based on these premises, this paper focuses on different tactical urbanism experiences in the Italian context and tries to assess the economic impacts of tactical urbanism interventions by adopting the lens of real estate values as a suitable proxy when dealing with urban environments. The first obtained results show that the experiences of tactical urbanism, partly because of their temporary nature and their tendency toward minimal intervention, fail to trigger regeneration processes or produce significant economic impacts on the territory. Instead, such experiences can play a role in accelerating or consolidating urban regeneration processes already underway, and, in this sense, they contribute to the generation of economic impact on the territory. Full article
(This article belongs to the Special Issue Landscapes at Risk. Social Capital Asset in the COVID-Scape Climate)
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<p>Methodological framework.</p> Full article ">Figure 2
<p>Documents by year developed using the Scopus database.</p> Full article ">Figure 3
<p>Keyword co-occurrence network developed with VOSviewer version 1.6.17.</p> Full article ">Figure 4
<p>Tactical urbanism interventions in Italy.</p> Full article ">Figure 5
<p>Average market value in the city and micro-zone where the tactical urbanism interventions have been developed.</p> Full article ">Figure 6
<p>Tactical urbanism intervention in Milan.</p> Full article ">Figure 7
<p>Variation in the market value of properties in the NoLo neighborhood.</p> Full article ">Figure 8
<p>Variation in the market value of properties in different years.</p> Full article ">Figure 9
<p>Via Spoleto/Venini tactical urbanism interventions.</p> Full article ">
21 pages, 7274 KiB  
Article
Improving Urban Habitat Connectivity for Native Birds: Using Least-Cost Path Analyses to Design Urban Green Infrastructure Networks
by Maggie MacKinnon, Maibritt Pedersen Zari and Daniel K. Brown
Land 2023, 12(7), 1456; https://doi.org/10.3390/land12071456 - 21 Jul 2023
Cited by 3 | Viewed by 3716
Abstract
Habitat loss and fragmentation are primary threats to biodiversity in urban areas. Least-cost path analyses are commonly used in ecology to identify and protect wildlife corridors and stepping-stone habitats that minimise the difficulty and risk for species dispersing across human-modified landscapes. However, they [...] Read more.
Habitat loss and fragmentation are primary threats to biodiversity in urban areas. Least-cost path analyses are commonly used in ecology to identify and protect wildlife corridors and stepping-stone habitats that minimise the difficulty and risk for species dispersing across human-modified landscapes. However, they are rarely considered or used in the design of urban green infrastructure networks, particularly those that include building-integrated vegetation, such as green walls and green roofs. This study uses Linkage Mapper, an ArcGIS toolbox, to identify the least-cost paths for four native keystone birds (kererū, tūī, korimako, and hihi) in Wellington, New Zealand, to design a network of green roof corridors that ease native bird dispersal. The results identified 27 least-cost paths across the central city that connect existing native forest habitats. Creating 0.7 km2 of green roof corridors along these least-cost paths reduced cost-weighted distances by 8.5–9.3% for the kererū, tūī, and korimako, but there was only a 4.3% reduction for the hihi (a small forest bird). In urban areas with little ground-level space for green infrastructure, this study demonstrates how least-cost path analyses can inform the design of building-integrated vegetation networks and quantify their impacts on corridor quality for target species in cities. Full article
(This article belongs to the Special Issue Sustainable Land-Use Dynamics and Green Infrastructure Mapping)
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<p>Study species distributions across the Lambton Harbour-Oriental Bay catchment area, which defines the city centre and is bordered by the town belt. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0). The four native birds selected for this research are the kererū (image credit ref. [<a href="#B56-land-12-01456" class="html-bibr">56</a>] CC BY CCO 1.0), tūī (image credit ref. [<a href="#B57-land-12-01456" class="html-bibr">57</a>] CC BY CCO 1.0), korimako (image credit ref. [<a href="#B58-land-12-01456" class="html-bibr">58</a>] CC BY-SA 2.0), and hihi (image credit ref. [<a href="#B59-land-12-01456" class="html-bibr">59</a>] CC BY 4.0). The observation data were obtained from the Global Biodiversity Information Facility (CC BY 4.0) for the kererū [<a href="#B60-land-12-01456" class="html-bibr">60</a>], tūī [<a href="#B61-land-12-01456" class="html-bibr">61</a>], korimako [<a href="#B62-land-12-01456" class="html-bibr">62</a>], and hihi [<a href="#B63-land-12-01456" class="html-bibr">63</a>].</p> Full article ">Figure 2
<p>Workflow for the Linkage Pathways tool. The inputs required are species resistance rasters and core habitat features. The tool produces least-cost paths, actual (or Euclidean) distance paths, cost-weighted distance rasters, and corridor rasters.</p> Full article ">Figure 3
<p>Landscape features of the study area for the Linkage Pathways tool: (<b>a</b>) land cover types and roads in the study area; (<b>b</b>) the three forest land cover types were extracted to create a core habitat map overlayed with topography contours and building heights. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0).</p> Full article ">Figure 4
<p>Species resistance rasters of the existing green infrastructure network for the Linkage Pathways tool: (<b>a</b>) kererū; (<b>b</b>) tūī; (<b>c</b>) korimako; (<b>d</b>) hihi. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0).</p> Full article ">Figure 4 Cont.
<p>Species resistance rasters of the existing green infrastructure network for the Linkage Pathways tool: (<b>a</b>) kererū; (<b>b</b>) tūī; (<b>c</b>) korimako; (<b>d</b>) hihi. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0).</p> Full article ">Figure 5
<p>Urban green infrastructure design using outputs from the Linkage Pathways tool: (<b>a</b>) consolidated least-cost paths connecting core habitats for the four study species; (<b>b</b>) proposed locations for green roofs to supplement the existing green space network. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0).</p> Full article ">Figure 6
<p>Species resistance rasters of the proposed green infrastructure network for the Linkage Pathways tool: (<b>a</b>) kererū; (<b>b</b>) tūī; (<b>c</b>) korimako; (<b>d</b>) hihi. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0).</p> Full article ">Figure 6 Cont.
<p>Species resistance rasters of the proposed green infrastructure network for the Linkage Pathways tool: (<b>a</b>) kererū; (<b>b</b>) tūī; (<b>c</b>) korimako; (<b>d</b>) hihi. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0).</p> Full article ">Figure 7
<p>Least-cost paths and cost-weighted distance maps for the kererū for: (<b>a</b>) the existing green infrastructure network; (<b>b</b>) the proposed green infrastructure network. The numbers identify individual least-cost paths. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0).</p> Full article ">Figure 8
<p>Least-cost paths and cost-weighted distance maps for the tūī for: (<b>a</b>) the existing green infrastructure network; (<b>b</b>) the proposed green infrastructure network. The numbers identify individual least-cost paths. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0).</p> Full article ">Figure 9
<p>Least-cost paths and cost-weighted distance maps for the korimako for: (<b>a</b>) the existing green infrastructure network; (<b>b</b>) the proposed green infrastructure network. The numbers identify individual least-cost paths. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0).</p> Full article ">Figure 10
<p>Least-cost paths and cost-weighted distance maps for the hihi for: (<b>a</b>) the existing green infrastructure network; (<b>b</b>) the proposed green infrastructure network. The numbers identify individual least-cost paths. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0).</p> Full article ">Figure 11
<p>Priority of implementation for the 27 green roof corridors. The base satellite image is from ref. [<a href="#B55-land-12-01456" class="html-bibr">55</a>] (CC BY 4.0).</p> Full article ">
20 pages, 32156 KiB  
Article
Research on Township Industry Development under GEP Accounting—A Case Study of Hanwang Town in Xuzhou City
by Shuai Tong, Jianjie Gao, Fengyu Wang and Xiang Ji
Land 2023, 12(7), 1455; https://doi.org/10.3390/land12071455 - 21 Jul 2023
Cited by 1 | Viewed by 1439
Abstract
The protection and utilization of ecological environment are very important for urban and rural development. At present, a large number of relevant theoretical and practical explorations have been carried out, which confirms the important conclusion that lucid waters and lush mountains are invaluable [...] Read more.
The protection and utilization of ecological environment are very important for urban and rural development. At present, a large number of relevant theoretical and practical explorations have been carried out, which confirms the important conclusion that lucid waters and lush mountains are invaluable assets. The sustainable development of ecological environments is based on coordination with human production and life. In this paper, by constructing an accounting system for the gross ecosystem product (GEP) applicable to Hanwang town, using the market value method, the alternative cost method, the travel cost method, the willingness to pay method and other technical methods, the GEP of Hanwang town is calculated from three aspects: product supply, regulation service and cultural tourism. Finally, the spatial distribution characteristics of value are used to guide the development and layout of ecological industry in Hanwang town. The results showed that the total ecosystem product value of Hanwang town in Xuzhou was relatively high, reaching 1.165 billion CNY, with per capita reaching 30 million CNY, which was 49.16% of the town’s GDP in 2020. The value of cultural tourism is 820 million CNY, the value of regulatory services is 239 million CNY, and the value of product provision is 106 million CNY. The ecological value of Hanwang town varies greatly in spatial distribution. On the whole, the price is low in the southwest, but high in the northeast. The high-value areas are mainly concentrated in three areas: Yudai River Riverside, Xuzhou Paradise in the north, Hanwang Scenic Spot in the middle and the Panaxi Valley tourist spot in the south. Based on the principle of ecological value transformation, combining with the spatial distribution characteristics of ecological value in Hanwang town, four modes of promoting ecological value transformation were proposed: ecological industrialization management, ecological governance and value promotion, ecological resource index trading and ecotourism. This paper preliminarily explores a method to calculate and transform the value of ecological space, which provides feasible concrete strategies for the protection of ecological space and the development of ecological industry in towns. Full article
(This article belongs to the Topic Sustainable Landscape in Rural Areas: Theories, Strategies, and Practices)
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<p>Ecological type distribution map.</p> Full article ">Figure 2
<p>GEP value distribution map.</p> Full article ">Figure 3
<p>Chart of supply value per unit area. (<b>a</b>) Agriculture, forestry, animal husbandry and fishery; (<b>b</b>) water resources; (<b>c</b>) ecological energy.</p> Full article ">Figure 4
<p>Supply value map in each village. (<b>a</b>) Agriculture; (<b>b</b>) forestry; (<b>c</b>) animal husbandry; (<b>d</b>) fishery; (<b>e</b>) water resources; (<b>f</b>) ecological energy.</p> Full article ">Figure 5
<p>Adjusted value distribution map. (<b>a</b>) Comprehensive adjustment value distribution map Water conservation value distribution map; (<b>b</b>) water conservation; (<b>c</b>) soil conservation; (<b>d</b>) carbon fixation and oxygen release; (<b>e</b>) air purification; (<b>f</b>) climate regulation.</p> Full article ">Figure 6
<p>Adjusted value distribution map in each village. (<b>a</b>) Comprehensive adjustment value distribution map; (<b>b</b>) water conservation; (<b>c</b>) soil conservation; (<b>d</b>) water control and storage; (<b>e</b>) carbon fixation and oxygen release; (<b>f</b>) air purification; (<b>g</b>) water purification; (<b>h</b>) climate regulation.</p> Full article ">Figure 6 Cont.
<p>Adjusted value distribution map in each village. (<b>a</b>) Comprehensive adjustment value distribution map; (<b>b</b>) water conservation; (<b>c</b>) soil conservation; (<b>d</b>) water control and storage; (<b>e</b>) carbon fixation and oxygen release; (<b>f</b>) air purification; (<b>g</b>) water purification; (<b>h</b>) climate regulation.</p> Full article ">Figure 7
<p>Attractions and value distribution. (<b>a</b>) Cultural tourism value distribution map; (<b>b</b>) Nuclear density map of tourist attractions.</p> Full article ">Figure 8
<p>Agriculture, forestry, animal husbandry and fishery industry planning. (<b>a</b>) Plan of Hanwang town Agricultural Processing Industrial Park; (<b>b</b>) fishery spatial planning; (<b>c</b>) forestry business model diagram.</p> Full article ">Figure 9
<p>Tourism structure and land use adjustment. (<b>a</b>) Planning map of tourism space structure; (<b>b</b>) land use adjustment and new attractions.</p> Full article ">Figure 10
<p>Tour routes and service facilities. (<b>a</b>) Town area tourism route planning; (<b>b</b>) layout plan of tourism service facilities.</p> Full article ">
15 pages, 1837 KiB  
Article
Spatial Patterns of Urban Green-Blue Spaces and Residents’ Well-Being: The Mediating Effect of Neighborhood Social Cohesion
by Xinrui Wang, Libin Ouyang, Jian Lin, Pengfei An, Wanjing Wang, Lin Liu and Longfeng Wu
Land 2023, 12(7), 1454; https://doi.org/10.3390/land12071454 - 21 Jul 2023
Cited by 6 | Viewed by 2298
Abstract
Urban green-blue spaces (UGBS) can benefit residents’ well-being through multiple pathways. Previous studies have confirmed that the quantity and composition of UGBS can promote neighborhood social cohesion, which subsequently contributes to residents’ physical and mental health. However, there has been little attention paid [...] Read more.
Urban green-blue spaces (UGBS) can benefit residents’ well-being through multiple pathways. Previous studies have confirmed that the quantity and composition of UGBS can promote neighborhood social cohesion, which subsequently contributes to residents’ physical and mental health. However, there has been little attention paid to the spatial patterns of UGBS in such relationships. This study adopted landscape pattern indexes to characterize the spatial patterns of UGBS and explored the mediation effect of neighborhood social cohesion between the spatial patterns of UGBS and residents’ well-being, measured by self-rated health (SRH) and happiness. Partial Least Squares Structural Equation Model (PLS-SEM) was used for analyses with data obtained from the 2018 Shandong Provincial Social Survey Questionnaire (SGSS), which included 773 selected residents in urban areas. The results indicated that (1) there was a mediation effect of neighborhood social cohesion between the spatial patterns of UGBS and residents’ SRH and happiness; (2) the aggregation and diversity of UGBS had greater impacts on enhancing neighborhood social cohesion than the size, complexity, and fragmentation; (3) the aggregation and diversity of UGBS had indirect effects on improving happiness and SRH, and the aggregation of UGBS had a direct positive effect on SRH. By focusing on the spatial patterns of UGBS and neighborhood social cohesion, this study extends current debates on the pathways among UGBS, social cohesion, and public health. Urban planning strategies were proposed to increase the benefits of UGBS in urban areas. Full article
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<p>Study area and sample communities within 3 km buffers.</p> Full article ">Figure 2
<p>PLS-SEM path diagram of the correlations among the characteristics of UGBS (size, aggregation, fragmentation, complexity, and diversity), neighborhood social cohesion, personal attributes, economic level, and residents’ SRH (** <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.01).</p> Full article ">Figure 3
<p>PLS-SEM path diagram of the correlations among the characteristics of UGBS (size, aggregation, fragmentation, complexity, and diversity), neighborhood social cohesion, personal attributes, economic level, and residents’ happiness (* <span class="html-italic">p</span> &lt; 0.1; ** <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.01).</p> Full article ">
19 pages, 2605 KiB  
Article
Measuring the Urban Resilience Abased on Geographically Weighted Regression (GWR) Model in the Post-Pandemic Era: A Case Study of Jiangsu Province, China
by Yi Liu, Tiantian Gu, Lingzhi Li, Peng Cui and Yan Liu
Land 2023, 12(7), 1453; https://doi.org/10.3390/land12071453 - 20 Jul 2023
Cited by 4 | Viewed by 2030
Abstract
Since China declared that the post-epidemic era would begin in April 2020, the prevention and control of epidemics have become routine. The capacity of cities to respond to future public health emergencies will be enhanced if the resilience of cities is accurately measured [...] Read more.
Since China declared that the post-epidemic era would begin in April 2020, the prevention and control of epidemics have become routine. The capacity of cities to respond to future public health emergencies will be enhanced if the resilience of cities is accurately measured and an emphasis is placed on improving resilience levels. Under the 4R framework, this study quantifies and analyzes the level of resilience of the cities in Jiangsu Province from both subjective and objective perspectives. By selecting explanatory variables and developing a GWR model, the spatial distribution characteristics of the quantified scores of resilience and the spatial characteristics of the influencing factors are analyzed. The results indicate that cities in southern Jiangsu should invest more in economic development and medical resources in the post-epidemic period. Northern Jiangsu should prioritize boosting the health and social work sector’s gross domestic product. Coastal cities must enhance their capacity for innocuous waste treatment. Full article
(This article belongs to the Special Issue Impacts of the COVID-19 Pandemic on Urban Planning, Design, and Management)
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<p>The flow chart of the evaluation system.</p> Full article ">Figure 2
<p>The identification of resilience assessment indicators.</p> Full article ">Figure 3
<p>Map of spatial variation in urban resilience and resilience scores.</p> Full article ">Figure 4
<p>Spatial visualization of regression.</p> Full article ">Figure 5
<p>Spatially varying values of GWR model regression coefficients.</p> Full article ">Figure 5 Cont.
<p>Spatially varying values of GWR model regression coefficients.</p> Full article ">
15 pages, 544 KiB  
Article
Effectiveness in Rural Governance: Influencing Factors and Driving Pathways—Based on 20 Typical Cases of Rural Governance in China
by Yu Peng, Xiaobing Peng, Xu Li, Mingyue Lu and Mingze Yin
Land 2023, 12(7), 1452; https://doi.org/10.3390/land12071452 - 20 Jul 2023
Cited by 6 | Viewed by 4381
Abstract
Effective rural governance is the foundation for achieving rural revitalization and promoting the modernization of China’s system and governance capacity in the new era. The elucidation of the influencing factors and driving pathways underlying effective rural governance has significant importance in facilitating the [...] Read more.
Effective rural governance is the foundation for achieving rural revitalization and promoting the modernization of China’s system and governance capacity in the new era. The elucidation of the influencing factors and driving pathways underlying effective rural governance has significant importance in facilitating the advancement of rural revitalization. Drawing upon the Actor-Network Theory (ANT), this study introduces an analytical framework of “human actor dimension—non-human actor dimension”. The study employs the fuzzy-set Qualitative Comparison Analysis (fsQCA) to explore the effective governance pathways within 20 typical cases of rural governance. The study reveals that a cooperative-based collective economy is a necessary condition for effective governance, while possessing a resource advantage is a core condition. Villager autonomy, local culture, and new technology are marginal conditions for effective governance, while the absence of elite participation fails to promote effective governance. The combination of human variables and resource compacts gives rise to “human actor-resource compacts” and “non-human actor-resource compacts”. The study further elaborates on the efficacious model of rural governance through three multifactor driving pathways: “human actor-non-human actor resource sparse linkage”. The research emphasizes the importance of fortifying rural governance and revitalization through the cultivation of relationships, enhancing government management systems, embracing technological innovation, supporting community economies, and advocating mechanisms that empower rural elites and talent. Full article
(This article belongs to the Special Issue State of the Art on Agriculture in Rural Areas: For Sustainable Land Management)
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<p>Analytical framework for governance effectiveness. Figure source: Author-created.</p> Full article ">
22 pages, 25990 KiB  
Article
Recommendations for Landslide Early Warning Systems in Informal Settlements Based on a Case Study in Medellín, Colombia
by Moritz Gamperl, John Singer, Carolina Garcia-Londoño, Lisa Seiler, Julián Castañeda, David Cerón-Hernandez and Kurosch Thuro
Land 2023, 12(7), 1451; https://doi.org/10.3390/land12071451 - 20 Jul 2023
Cited by 2 | Viewed by 1822
Abstract
Fatalities from landslides are rising worldwide, especially in cities in mountainous regions, which often expand into the steep slopes surrounding them. For residents, often those living in poor neighborhoods and informal settlements, integrated landslide early warning systems (LEWS) can be a viable solution, [...] Read more.
Fatalities from landslides are rising worldwide, especially in cities in mountainous regions, which often expand into the steep slopes surrounding them. For residents, often those living in poor neighborhoods and informal settlements, integrated landslide early warning systems (LEWS) can be a viable solution, if they are affordable and easily replicable. We developed a LEWS in Medellín, Colombia, which can be applied in such semi-urban situations. All the components of the LEWS, from hazard and risk assessment, to the monitoring system and the reaction capacity, were developed with and supported by all local stakeholders, including local authorities, agencies, NGO’s, and especially the local community, in order to build trust. It was well integrated into the social structure of the neighborhood, while still delivering precise and dense deformation and trigger measurements. A prototype was built and installed in a neighborhood in Medellín in 2022, comprising a dense network of line and point measurements and gateways. The first data from the measurement system are now available and allow us to define initial thresholds, while more data are being collected to allow for automatic early warning in the future. All the newly developed knowledge, from sensor hardware and software to installation manuals, has been compiled on a wiki-page, to facilitate replication by people in other parts of the world. According to our experience of the installation, we give recommendations for the implementation of LEWSs in similar areas, which can hopefully stimulate a lively exchange between researchers and other stakeholders who want to use, modify, and replicate our system. Full article
(This article belongs to the Special Issue New Perspectives for the Monitoring and Early Detection of Geohazards)
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<p>Example of a typical monthly stakeholder meeting for an integrated LEWS. The involvement of all stakeholders is deeply interlinked with the risk cycle and the four elements of the LEWS (risk analysis, monitoring and forecast, alert dissemination, and reaction capacity). Adapted from Sharma [<a href="#B38-land-12-01451" class="html-bibr">38</a>] and Werthmann [<a href="#B39-land-12-01451" class="html-bibr">39</a>].</p> Full article ">Figure 2
<p>Final installation plan for the monitoring system in Bello Oriente. Overall, 111 measurement nodes, over 1 km of horizontal measurement lines, and three gateways were installed on site. Locations of nodes 40 and 115, displayed in <a href="#land-12-01451-f003" class="html-fig">Figure 3</a>, are indicated by the red circles.</p> Full article ">Figure 3
<p>Change in inclination of an infrastructure node (node 40, surface inclinometer only, <b>top</b>) and a subsurface node (node 115) equipped with a surface inclinometer (<b>middle</b>) and a subsurface inclinometer (SSP, <b>bottom</b>) at 1.5 m depth from 1 January to 17 May 2023. See <a href="#land-12-01451-f002" class="html-fig">Figure 2</a> for the sensor locations. (X-axis: downhill).</p> Full article ">Figure 4
<p>Photos of the installation of the measurement system in Bello Oriente in 2022. (<b>Left</b>): Installation of a subsurface probe with a measurement node on top. (<b>Right</b>): low-cost sensor enclosure in a remote location.</p> Full article ">Figure 5
<p>Picture of one of the meetings, with various stakeholders of the project. Picture: C. Garcia.</p> Full article ">Figure 6
<p>Photos of the participation of the community in the four components of the LEWS. Pictures: C. Garcia.</p> Full article ">Figure 7
<p>Sensor protections as small seats or benches made out of bricks, supplemented by short inscriptions and bright colors.</p> Full article ">Figure 8
<p>(<b>Left</b>): Gateway B functions as a small public space, with a large bench and an information sign. (<b>Right</b>): LoRa<sup>®</sup> infrastructure node combined with a wall painting: “Lora the parrot” embodies the sensor.</p> Full article ">Figure 9
<p>Point markers indicate the location of the horizontal CSM lines.</p> Full article ">Figure 10
<p>Inform@Risk wiki page, accessible under <a href="http://www.informatrisk.com" target="_blank">www.informatrisk.com</a> (accessed on 10 June 2023). The wiki is a central place for all information about the LEWS. Currently, the wiki is available in three languages, english, german, and spanish (further content and languages can be added by users).</p> Full article ">Figure 11
<p>Overview of the open-source information about the monitoring system provided on the wiki- and GitHub pages. The licenses, CERN-OHL-W-2.0 for hardware and GPL-3.0 for software, allow open distribution, modification, and publication of all materials, as long as reference to the source is given.</p> Full article ">Figure 12
<p>The Inform@Risk framework for integrated LEWS.</p> Full article ">
27 pages, 15498 KiB  
Article
Land System Simulation of Ruoergai Plateau by Integrating MaxEnt and Boltzmann Entropy into CLUMondo
by Ziyun Sun, Yuqi Wang, Juru Lin and Peichao Gao
Land 2023, 12(7), 1450; https://doi.org/10.3390/land12071450 - 20 Jul 2023
Cited by 5 | Viewed by 1289
Abstract
In the context of global change, land cover change is significantly influenced by human activities. However, there is limited knowledge about the potential economic and ecological benefits that land cover change on the Ruoergai Plateau will bring by 2035, considering the existing development [...] Read more.
In the context of global change, land cover change is significantly influenced by human activities. However, there is limited knowledge about the potential economic and ecological benefits that land cover change on the Ruoergai Plateau will bring by 2035, considering the existing development plans. In our study, the CLUMondo model was improved by integrating the MaxEnt model and Boltzmann entropy and used to predict the structure and intensity of land change in China’s Ruoergai Plateau. The results show that the model integrated with MaxEnt and Boltzmann entropy is the most accurate in four contrasting experiments that have a Kappa of 0.773. The predicted results show that with the increase in the demand for ecological benefits, the total area of the water area shows a clear increasing trend. With 0.25% GDP growth, the water area is about 178 km2. With 2.5% GEP growth, the water area is about 202 km2. The latter is 24 km2 more than the former, an increase of about 13.6%. With the increase in the demand for economic benefits, the total area of construction land shows a clear increasing trend. Grassland, forest, and cropland are partly converted into construction land, because of the higher economic benefits of construction land. At the same time, the density of construction land will increase. With 12.6% GDP growth, the high-density construction area is about 399 km2. With 126.1% GEP growth, the water area is about 761 km2. High-density construction land increased by 90.7% (about 362 km2). In the low elevation area near the mountains of Ruoergai County, a new concentration of construction land will appear. The simulation results are of great significance for guiding ecological protection and urban construction in Ruoergai. Full article
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<p>Location and extent of the study area in Ruoergai Plateau.</p> Full article ">Figure 2
<p>The land use/cover types and land use intensity data. (<b>a</b>) Six land use types distribution map of the Ruoergai Plateau. The results obtained are reliable because we have compared them with the land data from the Resource and Environment Science and Data Center [<a href="#B52-land-12-01450" class="html-bibr">52</a>] (<b>b</b>) Twelve land use intensity types of the Ruoergai Plateau. All the data have a 1 km resolution. The latter is divided by the natural breakpoint method based on the former.</p> Full article ">Figure 3
<p>The production schematic diagram of compact cropland and scattered cropland.</p> Full article ">Figure 4
<p>The driving factors.</p> Full article ">Figure 5
<p>The overall framework of the integrated model (modified from reference [<a href="#B57-land-12-01450" class="html-bibr">57</a>]).</p> Full article ">Figure 6
<p>The main work of this study.</p> Full article ">Figure 7
<p>The core idea of calculating Boltzmann entropy for quantitative spatial raster data (modified from reference [<a href="#B60-land-12-01450" class="html-bibr">60</a>]).</p> Full article ">Figure 8
<p>The Boltzmann entropy results were calculated by DEM on the Ruoergai Plateau. The higher the value, the greater the Botzmann entropy of the pixel, the greater the heterogeneity of space.</p> Full article ">Figure 9
<p>Four sets of contrasting experiments were used to predict the 2021 land system based on 2017 data. (<b>a</b>) The model is integrated with MaxEnt and Boltzmann entropy. (<b>b</b>) The model is integrated with Boltzmann entropy. (<b>c</b>) The model is integrated with MaxEnt. (<b>d</b>) The original model.</p> Full article ">Figure 10
<p>The confusion matrix between 2017 and 2021.</p> Full article ">Figure 11
<p>Predicted results of land use types under 9 scenarios. Subfigure (<b>a</b>–<b>i</b>) correspond to scenarios 1–9, respectively.</p> Full article ">Figure 12
<p>Typical areas of land type and intensity distribution on the Ruoergai Plateau in 2021. The areas in the two red boxes are the selected typical areas.</p> Full article ">Figure 13
<p>Local area 1 ((<b>a</b>–<b>i</b>), in order, original 2021 scenario, scenarios 1–9).</p> Full article ">Figure 14
<p>Local area 2 ((<b>a</b>–<b>i</b>), in order, original 2021 scenario, scenarios 1–9).</p> Full article ">Figure 15
<p>Summary of 2035 area for various land use types under different scenarios.</p> Full article ">Figure 16
<p>Areas of (<b>a</b>) cropland; (<b>b</b>) forest; (<b>c</b>) grassland; (<b>d</b>) water; (<b>e</b>) construction; (<b>f</b>) unutilized land in 2035 under different simulation scenarios.</p> Full article ">Figure 17
<p>Summary of the pixel-by-pixel transformations of the Ruoergai Plateau’s land systems from 2021 to 2035 in scenario 9. (i.e., if 126.1% GDP increase and 2.5% GEP increase become possible).</p> Full article ">
1 pages, 163 KiB  
Correction
Correction: Mottaghi et al. Caring for Blue-Green Solutions (BGS) in Everyday Life: An Investigation of Recreational Use, Neighborhood Preferences and Willingness to Pay in Augustenborg, Malmö. Land 2023, 12, 336
by Misagh Mottaghi, Jonas Nordström, Salar Haghighatafshar, Karin Jönsson, Mattias Kärrholm and Catharina Sternudd
Land 2023, 12(7), 1449; https://doi.org/10.3390/land12071449 - 20 Jul 2023
Viewed by 600
Abstract
There was an error in the original publication [...] Full article
(This article belongs to the Special Issue Blue-Green Infrastructure Solutions: A Sustainable Way to Urban Development)
28 pages, 6689 KiB  
Article
Assessment of Land Ecological Security from 2000 to 2020 in the Chengdu Plain Region of China
by Lindan Zhang, Wenfu Peng and Ji Zhang
Land 2023, 12(7), 1448; https://doi.org/10.3390/land12071448 - 20 Jul 2023
Cited by 11 | Viewed by 1393
Abstract
The purpose of land ecological security (LES) assessment is to evaluate the influence of land use and human activities on the land ecosystem. Its ultimate objective is to offer decision-making assistance and direction for safeguarding and rejuvenating the well-being and effectiveness of the [...] Read more.
The purpose of land ecological security (LES) assessment is to evaluate the influence of land use and human activities on the land ecosystem. Its ultimate objective is to offer decision-making assistance and direction for safeguarding and rejuvenating the well-being and effectiveness of the land ecosystem. However, it is important to note that there are still significant uncertainties associated with current land ecological safety assessments. This paper presents a comprehensive evaluation model that combines the strengths of subjective and objective weighting methods. The model is built upon an index system developed using the Pressure-State-Response (PSR) framework. To verify the level of LES, theThe results of classifying the total ecosystem service valueTotal Ecosystem Service Value are utilized to verify the level of LES. Furthermore, spatial distribution patterns of regional land ecological safety levels are analyzed using statistical techniques, such as Moran’s I, Mann–Whitney U-test, and Kruskal–Wallis H-test. The findings indicate that: (1) theThe evaluation model developed in this paper achieves a validation accuracy of 75.55%, indicating that it provides a more accurate reflection of the level of land ecological safety in the region; (2) The ecological security index is generally safe, with a mean value in the moderate safety range. It experienced a turning point in 2010, showing initial deterioration followed by improvement, mainly due to the transition between unsafe and relatively safe zones. (3) The level of economic development, topography, and urban-–rural structure are significant factors influencing the spatial concentration of LES in the region, ultimately shaping the spatial pattern of LES in the Chengdu Plain region. Full article
(This article belongs to the Topic Urban Land Use and Spatial Analysis)
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<p>Location of the study area.</p> Full article ">Figure 2
<p>Technical route.</p> Full article ">Figure 3
<p>Bar chart depicting different land ecological security zones in different subregions for different years (“GDP” represents the economic development level zones, ranging from 4 to 1, indicating: highly developed economic areas, moderately developed economic areas, relatively underdeveloped economic areas, and economically backward areas. “GEO” represents the landform type zones, ranging from 3 to 1, indicating: mountainous region, low-hilly region, plain, and plateau. “City” represents the urban–rural division, with 2 representing rural areas and 1 representing urban areas).</p> Full article ">Figure 4
<p>Results of land ecological safety evaluation at the grid scale in the Chengdu Plain region.</p> Full article ">Figure 5
<p>Results of the evaluation of LES at the township scale in the Chengdu Plain region.</p> Full article ">Figure 6
<p>Local Moran index mapping of the pressure dimension in the Chengdu Plain region.</p> Full article ">Figure 7
<p>Local Moran index mapping for the state dimension in the Chengdu Plain region.</p> Full article ">Figure 8
<p>Local Moran index mapping of response dimensions in the Chengdu Plain region.</p> Full article ">
14 pages, 3183 KiB  
Article
Analyzing the Land Use and Cover Change Inside and Outside China’s Ecological Function Area
by Yajuan Wang, Yongheng Rao and Hongbo Zhu
Land 2023, 12(7), 1447; https://doi.org/10.3390/land12071447 - 20 Jul 2023
Cited by 3 | Viewed by 1830
Abstract
The establishment of nature reserves and ecological function areas is crucial for preserving the natural environment and the invaluable services provided by ecosystems. In our study, we conducted a comprehensive analysis using the 2011–2020 Chinese land cover dataset to examine the impact of [...] Read more.
The establishment of nature reserves and ecological function areas is crucial for preserving the natural environment and the invaluable services provided by ecosystems. In our study, we conducted a comprehensive analysis using the 2011–2020 Chinese land cover dataset to examine the impact of ecological function areas on regional land use and cover change. This analysis allowed us to quantify and visualize the intensity, aggregation effects, and transformation paths of land cover change while considering China’s ecological function areas. Our findings highlight notable disparities in land cover types between the ecological function area and its surroundings. Within the ecological function area, forest and grassland dominate, constituting 67% of the total land cover. In contrast, outside the ecological function area, there is a greater presence of wasteland, in addition to forest and grassland. Moreover, the abundance of impervious surfaces, which are closely linked to human activities, is significantly higher outside the ecological function area, almost double the amount found inside. By examining specific land cover types, we observed that forests exhibit the least change within the ecological function area, whereas croplands experience the least change outside. Throughout the study period, approximately 8.1% of land cover pixels underwent changes, with some areas displaying a frequency of change reaching up to 2. Interestingly, the number of high-frequency land use and cover change pixels inside the ecological function area is only half of the outside. Notably, a higher percentage of impervious surfaces within the ecological function area (0.13%) were converted into cropland compared to the outside (0.07%). Understanding the dynamics of land cover change within China’s ecological function areas provides valuable insights for effective land resource management and planning. It enables us to make informed decisions to ensure the sustainable development and conservation of these areas. Full article
(This article belongs to the Special Issue Terrestrial Vegetation Dynamics and Its Response to Environmental Change)
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<p>Distribution of ecological function areas in China.</p> Full article ">Figure 2
<p>Research framework.</p> Full article ">Figure 3
<p>The average value of land cover types structure from 2011 to 2020 inside and outside the ecological function area (the inner circle indicates the average proportion of land types inside the ecological function area, and the outer circle indicates the average proportion of land types outside the ecological function area). The proportion of wetlands is relatively small, so it is not displayed in the figure.</p> Full article ">Figure 4
<p>Cumulative changes of land cover inside and outside the ecological function area. (<b>a</b>,<b>b</b>) Are the cumulative number of change pixels inside and outside ecological function areas, respectively, and (<b>c</b>,<b>d</b>) is the rate of the cumulative change inside and outside ecological function areas, respectively.</p> Full article ">Figure 5
<p>Frequency of land cover type changes based on ecological function areas. The green line is the boundary of ecological function areas; if the frequency is displayed in the green circle, it indicates that the event occurred in the ecological function areas.</p> Full article ">Figure 6
<p>Analysis of coldspots and hotspots of land cover type change frequency.</p> Full article ">Figure 7
<p>Transformation distribution of different land cover types based on ecological function areas. Specifically, cropland means that other land use types are converted to cropland, and forest means that other types are converted to forest, and so on.</p> Full article ">Figure 8
<p>Land cover transformation types from 2011 to 2020. (<b>a</b>,<b>b</b>) Respectively indicate the land use type transfer within and outside the ecological function area.</p> Full article ">
19 pages, 72082 KiB  
Article
Analysis and Evaluation of the Service Capacity of a Waterfront Public Space Using Point-of-Interest Data Combined with Questionnaire Surveys
by Pinyue Ouyang and Xiaowen Wu
Land 2023, 12(7), 1446; https://doi.org/10.3390/land12071446 - 20 Jul 2023
Cited by 2 | Viewed by 1491
Abstract
The analysis and evaluation of the service capacity of an urban public space is of great importance for optimizing spatial design and ensuring sustainable regeneration of the space. Point-of-interest (POI) data analysis is a common method for evaluating the performance of public space [...] Read more.
The analysis and evaluation of the service capacity of an urban public space is of great importance for optimizing spatial design and ensuring sustainable regeneration of the space. Point-of-interest (POI) data analysis is a common method for evaluating the performance of public space since it contains various geographical information about specific facilities. However, this method is incapable of providing intuitive and clear feedback on the usage of the space, such as visitor experience and satisfaction levels. In this paper, we present a hybrid approach that combines POI data with questionnaire surveys to comprehensively analyze and evaluate the service capacity of the facilities in a waterfront public space. By taking the Changning section of the Suzhou Creek in Shanghai as an example, we evaluate and verify the utilization rate and satisfaction level of public facilities based on this hybrid approach with three satisfaction factors: accessibility, landscape visual quality, and service functions. The results reveal that the service space that can be reached on foot provides the most satisfaction in terms of accessibility, followed by the space that can be reached by bicycle. When it comes to landscape visual quality, visitors are more concerned with the view around the facility than with the greenery. Regarding service functions, the service facility with beverage outlets, fitness, and small gatherings is more appealing. The proposed approach will be useful for further developing advanced public space evaluation strategies with real-time feedback capabilities, as well as for the intelligent design and long-term regeneration of future public spaces. Full article
(This article belongs to the Section Land Planning and Landscape Architecture)
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<p>The location of the Changning Section in Shanghai Suzhou Creek.</p> Full article ">Figure 2
<p>POI data of ten waterfront public service stations.</p> Full article ">Figure 3
<p>Research framework.</p> Full article ">Figure 4
<p>(<b>a</b>) Station F (Hongqiao Riverside Park) and (<b>b</b>) Station J (Huazheng Service Station) in the 15 min walking radius with the residential area.</p> Full article ">Figure 5
<p>(<b>a</b>) Station C (Fengling Park), (<b>b</b>) Station D (Rock Park), (<b>c</b>) Station E (Tianyuan Riverfront Park), and (<b>d</b>) Station F (Hongqiao Riverside Park) in surrounding transport stops in 5 min, 10 min, 15 min’s radiation.</p> Full article ">Figure 5 Cont.
<p>(<b>a</b>) Station C (Fengling Park), (<b>b</b>) Station D (Rock Park), (<b>c</b>) Station E (Tianyuan Riverfront Park), and (<b>d</b>) Station F (Hongqiao Riverside Park) in surrounding transport stops in 5 min, 10 min, 15 min’s radiation.</p> Full article ">Figure 6
<p>Site photo of Station C (Fengling Park).</p> Full article ">Figure 7
<p>(<b>a</b>) Station D (Rock Park) and (<b>b</b>) Station F (Hongqiao Riverside Park) in the 15 min walking radius with the urban green space. (<b>c</b>) Station G (Doho Creative Park) and (<b>d</b>) Station H (Thirty-Seven People’s Evening School Station) in the 15 min walking radius with the urban green space.</p> Full article ">Figure 8
<p>Purpose of visits for different age groups.</p> Full article ">Figure 9
<p>Space requirements for different age groups.</p> Full article ">Figure 10
<p>Chart of the purpose of visits.</p> Full article ">Figure 11
<p>Diagram of space requirements.</p> Full article ">Figure 12
<p>(<b>a</b>) Station D (Rock Park) and (<b>b</b>) Station F (Hongqiao Riverside Park) in the 15 min walking radius within the nearby commercial area.</p> Full article ">Figure 13
<p>(<b>a</b>) Station F (Hongqiao Riverside Park) and (<b>b</b>) Station I (Zhongshan Park) in the 15 min walking radius with the public green space.</p> Full article ">
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