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Article

Sustainable Development, Territorial Disparities in Land Resources, and Soil Degradation: A Multi-Temporal Approach

by
Marco Maialetti
1,
Luca Salvati
2,* and
Francesco Maria Chelli
3
1
Independent Researcher, I-00195 Rome, Italy
2
Department of Methods and Models for Economics, Territory and Finance (MEMOTEF), Faculty of Economics, Sapienza University of Rome, Via del Castro Laurenziano 9, I-00161 Rome, Italy
3
Department of Economics and Social Science, Polytechnic University of Marche, Piazza R. Martelli 8, I-60121 Ancona, Italy
*
Author to whom correspondence should be addressed.
Resources 2024, 13(9), 125; https://doi.org/10.3390/resources13090125
Submission received: 1 August 2024 / Revised: 27 August 2024 / Accepted: 5 September 2024 / Published: 6 September 2024
Browse Figures
Figure 1
<p>(<b>Left</b>) A map of Italy indicating the position of the Latium region (in red) and illustrating the spatial distribution of a simplified aridity index (average values between 1951 and 1980), indicating Latium as a traditional sub-humid region at that time (see <a href="#sec2dot1-resources-13-00125" class="html-sec">Section 2.1</a>); (<b>middle</b>) the administrative structure governing land; red indicates the boundaries of the Nuts-3 provinces (VT: Viterbo, RI: Rieti, RM: Rome, LT: Latina, and FR: Frosinone), and gray indicates the boundaries of the Nuts-5 municipalities; (<b>right</b>) the altimetry (<b>right</b>) of the Latium region; three color tones with different darknesses were used to outline the elevation gradient (light: &lt;100 m at the sea level; intermediate: 101–500 m at the sea level; dark: &gt;500 m at the sea level).</p> "> Figure 2
<p>A summary schematization of the elementary variables, thematic (quality) indicators, and the composite Environmentally Sensitive Area Index, ESAI.</p> "> Figure 3
<p>The spatial distribution of the average population density in the Latium region by municipality and province in 1961 (<b>left</b>) and 2021 (<b>right</b>); three color tones with different darknesses were used to highlight increasing density (light: &lt;200 inhabitants/km<sup>2</sup>; intermediate: 201–500 inhabitants/km<sup>2</sup>; and dark: &gt;500 inhabitants/km<sup>2</sup>); VT: Viterbo; RI: Rieti; RM: Rome; LT: Latina; FR: Frosinone).</p> "> Figure 4
<p>Spatial distribution of ESAI scores in Latium; 1960 (<b>upper left</b>), 1990 (<b>upper right</b>), 2020 (<b>lower left</b>), and percent difference between the beginning and the end of the observation period (<b>lower right</b>); white pixels indicate completely built-up areas (such as compact settlements in cities), lakes, and mountainous rocks/permanent glaciers that were not evaluated for soil degradation.</p> ">
Versions Notes

Abstract

:
The present study investigates territorial disparities in selected socioeconomic forces and environmental factors underlying soil degradation that may lead to early desertification processes in a dry Mediterranean region exposed to increasing human pressure. To verify if spatial disparities in land resources have increased over time, a standard approach based on the Environmentally Sensitive Area Index (ESAI) was adopted to evaluate sixty years of territorial transformations in Latium, Central Italy, a region prone to intense processes of land resource depletion. The ESAI provides a standard, holistic assessment of soil degradation based on the estimation of four different ‘resource qualities’ (climate, soil, vegetation, and land use) and their change over sufficiently long time windows; in this study, the procedure was run at three reference years (1960, 1990, and 2020). The observed divergence in soil degradation levels between coastal and inland districts arose during the study period, with a consequent reduction in the local-scale variability of the ESAI. Such differential processes observed along the elevation gradient in Central Italy are likely due to anthropogenic factors affecting land use and leveraging crop intensification in flat districts and farmland abandonment in steep areas. New findings to be achieved in the context of human impacts on land resource depletion are regarded as an original contribution to the study of early desertification processes in advanced economies.

1. Introduction

The intrinsic complexity of ecological processes and their latent interaction with socioeconomic dynamics is an important challenge for science and policy and thus requires a continuous improvement of (both traditional and advanced) assessment procedures [1,2,3]. Global, regional, and local issues related to spatially unbalanced natural resources, polarization of economic activities in a few poles, and social inequalities are particularly challenging for any monitoring approach [4] because of the intrinsic complexity of data integration and the increasing demand of approaches based on a truly multidisciplinary thinking [5]. By providing basic and integrated information that reflects complex, non-linear, and sometimes hardly predictable (biophysical and socioeconomic) dynamics [6], a comprehensive analysis of regional convergence (or divergence) in territorial processes is assumed to be particularly relevant in such a perspective [7].
Being launched nearly twenty years ago, the Lisbon strategy of the European Union has introduced sustainable development as a target of multiple policy agendas, dealing with social, economic, and environmental dimensions [8]. In this perspective, a new strategic objective of territorial cohesion was added as a third (research and policy) dimension to the old targets of socioeconomic cohesion [9]. The existence of persistent disparities and increasing human pressure on land resources—thanks to global change dynamics, including landscape transformations and local warming—call for an integrated and multidisciplinary approach quantifying environmental impacts at large and designing common policy responses [10].
As a consequence of unequal growths of population, settlements, and economic activities between coastal and inland districts, spatial disparities in Southern Europe have been particularly intense over the last decades, despite a number of policy actions mitigating such differentials, assumed to limit economic growth and, together, to harm the environmental quality and the appropriate functioning of natural ecosystems [11]. In this context, demographic gaps between populations residing in urban centers—as opposed to rural areas—were significantly widening, and the economic decline of inland districts exalted social inequalities between highly dynamic (and accessible) lowlands and more remote and peripheral areas, as far as advanced services, human capital/skills, and job opportunities are concerned [12,13,14].
Land resource depletion, the increasing level of soil degradation, and the consequent emergence of a latent—while generalized—risk of early desertification in traditionally sub-humid (or moderately semi-dry) areas in Mediterranean Europe are representative examples of the complex interplay between the environmental and the economic spheres of (continuously evolving) landscapes featuring a millenary history of human–nature interactions [15]. Land resource depletion, mainly in the form of soil degradation, implies a long-term decline in soil productivity, being a pre-requisite of low ecological sustainability [16], especially in conditions of local warming [17]. It is widely assumed that human-driven disparities in territorial assets and land resources have a direct and measurable impact on soil degradation and early desertification risk [18], since this process is not static and responds to a plethora of biophysical and economic forces, usually acting together [19].
Territorial unbalances in land assets/qualities and their depletion over time are a key issue in environmental planning and policy [20]. This issue is not restricted to the specific location where it is observed statically [21], spreading to neighboring districts, accelerating rural poverty and igniting social conflicts for the few available resources [22], e.g., land ownership, soil fertility, water, energy, and infrastructure [23]. In light of a quantitative assessment of land resource depletion, the present study elaborates descriptive information on the spatial convergence of the level of soil degradation and its consequences for early desertification risk and discusses the consequent policy implications for the sustainable development of rural and peri-urban districts [24]. A diachronic analysis of territorial complexities with national (or regional) coverage is especially needed when run at adequately fine spatial resolutions and may inform refined policies targeting a truly sustainable development path for local districts [25]. To verify—in a representative case for the Mediterranean region—if territorial disparities in land resources have increased over time [26], a standard approach was adopted, considering sixty years of territorial transformations along the elevation gradient in the Latium region, Central Italy.
In the 1950s and the 1960s, this area was traditionally classified as being exposed to wet (or moderately semi-dry) climate regimes [27]. Actually, it is recognized as being increasingly prone to intense processes of land resource depletion because of local warming and soil aridity [28]. The operational approach is based on the Environmentally Sensitive Area Index (ESAI), providing a standard, holistic assessment of soil degradation based on the estimation of four different ‘resource qualities’ (namely climate, soil, vegetation, and land-use) and their change over sufficiently long time windows [29]. Based on a descriptive analysis of the spatial distribution of the ESAI values at three reference years (1960, 1990, and 2020), the divergence in soil degradation levels between coastal and inland areas was assumed to consolidate over time [30]. New findings to be achieved in the context of human impacts on land resource depletion in advanced economies [31] are finally discussed as an original contribution to the study of early desertification processes on a local scale.

2. Methodology

2.1. Study Area

The investigated area covers the whole (Nuts-2 sensu Eurostat) administrative region of Latium, Central Italy, one of the twenty Italian regions, and is partitioned into five provinces (Viterbo, Rieti, Rome, Latina, and Frosinone) and 378 municipalities guaranteeing local governance [32]. Encompassing a total area of nearly 17,065 km2, the Latium region displays a complex topography, with different climatic belts along the elevation gradient, developing steeply from coastal (Tyrrhenian Sea) to inland zones. In the last 70 years, Latium has experienced intense land-use changes due to agricultural intensification, urban expansion, tourism development, and industrial concentration [27] in selected service nodes (Fiano, Colleferro, Civitavecchia, Pomezia, Frosinone, and Cassino), as well as overgrazing, wildfires, and fragmentation of semi-natural landscapes around large cities (mainly Rome) and intermediate towns. Moreover, climate conditions became moderately drier, especially along the coastal rim, where annual rainfalls fell to 550–600 mm, on average, from 700–750 mm recorded in the 1950s and 1960s [33] as a consequence of local warming and soil aridification (Figure 1).

2.2. Data Source and Elementary Variables

The Environmentally Sensitive Area Index (ESAI) is a well-known indicator of soil degradation and early desertification risk in the Mediterranean region and has been increasingly used in other parts of the world—after minor adjustments—and at the global scale, using the same operational philosophy [34]. The ESAI specifically estimates soil degradation conditions and early desertification risk as a combination of unsustainable land management together with a particular set of ecological factors, including poor soil, dry/arid climate, and low-quality vegetation cover [35,36,37]. According to the original ESAI scheme (Figure 2), whose technical description can be extensively found in Salvati et al. [32], the elementary variables selected to investigate the level of soil degradation and early desertification risk [38], as a measure of land resource depletion over time, refer to four research dimensions (climate, soil, vegetation, and land management). The four thematic (i.e., ‘quality’) indicators reflect such research dimensions [39], as illustrated in Figure 2.
The layers used in this study, in accordance with the current literature [40], are extensively regarded as reliable, comparable, and up-to-date at a regional scale in Mediterranean countries (see [23] for a broad discussion on the demand/supply of statistical information assessing desertification risk in Mediterranean countries). Our investigation covers a time window of 60 years from 1960 to 2020 [41], using comparable data needed to develop the full ESAI model [42]. To the best of our knowledge, the data sources available at the national and regional scale did not allow a more detailed frequency of diachronic observations to assure full comparability over both time and space [43]. The following paragraphs provide details on both elementary variables and quality indicators composing the ESAI [44].

2.2.1. Soil Quality

Soil depth and texture, slope, and the nature of the parent material, assumed as proxies of soil quality, were obtained from a digital map derived from the European Soil Database at a resolution of 1 km2 (Joint Research Center, Ispra). In our case, assuming the above-mentioned variables as soil (structural) characteristics determined by the joint action of pedogenesis (macro-climate, soil organisms, morphology, and climate) and considering the relatively short time window investigated, soil attributes were regarded as static [45].

2.2.2. Climate Quality

Climate quality was described using mean annual precipitation, aridity index, and exposition [33]. Average annual precipitation and aridity index (the ratio of precipitation to reference evapotranspiration, sensu United Nations Environmental Program, UNEP) were calculated on a decadal basis using information available in the National Agro-meteorological Database of the Italian Ministry of Agriculture and Forestry Policies [46], providing homogeneous and complete statistical coverage at the regional level [47]. Exposition (expressed as the landscape orientation degree from 1° to 360°) was derived from the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) database, a global 30 m resolution digital elevation model (DEM) generated from stereoscopic pairs of optical ASTER images [48].

2.2.3. Vegetation Quality

The impact of vegetation cover/land use on soil degradation and early desertification risk was assessed through four standard variables [49], namely vegetation cover, fire risk, the level of protection against soil erosion assured by vegetation, and the degree of drought resistance reflected in the current vegetation cover type [50]. These indicators were derived from elaborations on comparable, diachronic land-use maps, including a Corine-like ‘Land Use Map of Italy’ released by the National Research Council (CNR) and the Italian Touring Club (TCI) in 1960 and two Corine land cover maps, dated 1990 and 2018 [51]. The four indicators described above were calculated according to Kosmas and coworkers [47].

2.2.4. Land Management Quality

Land management quality was estimated as the result of population dynamics and specific land-use transformations [52]. Demographic density and the annual growth rate of the population—both measured at the municipal scale using census data released by Istat, the Italian National Statistical Institute—were used as proxies of human pressure [53]. An indicator of land-use intensity was obtained by processing the digital maps mentioned above and classifying each land class according to the assumed intensity of economic use [54]. Technical details on the elementary variables, thematic partial indicators, and data sources were provided in earlier studies [55].

2.3. Thematic Indicators

Following a standard benchmark [50] and elaborating on the elementary variables mentioned above, the ESAI scheme produced four (partial) indicators—Climate Quality Index (CQI), Soil Quality Index (SQI), Vegetation Quality Index (VQI), and Land Management Quality Index (MQI)—estimated as the geometric mean of the different scores assigned to each input variable (Table 1). Applied to vastly different field conditions all over Southern Europe [56], this score system was extensively verified on the field, both directly and remotely, and represents a standard in the estimation of soil degradation under Mediterranean ecological conditions [57]. The final ESAI value was then estimated at each spatial unit (1 km2 grid) as the geometric mean of the four partial indicators described above. Indicators were appropriately transformed into a score ranging from 1 (the lowest level of degradation) to 2 (the highest level of degradation), based on a well-known score system [58].

2.4. Descriptive Statistics of the Composite Index (ESAI)

The mean value of the ESAI score and its coefficient of variation over a given spatial domain were estimated at both the administrative regional level (Nuts-2: Latium) and the province (Nuts-3) level. In agreement with the National Action Plan to Combat Desertification in Italy, these partitions allow the classification of the investigated territory using different geographical and political levels that are easily interpretable for stakeholders and practitioners, support the identification of active strategies to combat early desertification, and mitigate the depletion of land resources. Descriptive statistics of the ESAI score were calculated for each territorial unit based on the ‘zonal statistics’ tool provided with the ArcGis software (Version 10, ESRI, Inc., Redwoods, CA, USA), and a weighted mean area of the score recorded on each elementary pixel and belonging to a given spatial unit was computed.

3. Results

3.1. A Preliminary Scrutiny of Territorial Conditions

Including a predominantly hilly morphology (45.6%), with flat (28.2%) and mountainous (26.2%) areas scattered throughout the region, Latium is located in the very center of the Italian peninsula. It borders Tuscany to the northwest, Umbria to the north, Marche to the northeast, Abruzzo and Molise to the east, Campania to the southeast, and the Tyrrhenian Sea to the west, with Vatican City being a small enclave within its regional administrative borders. Since the early 1960s, the resident population has grown by over one and a half million inhabitants in Latium, reaching nearly 5.5 million inhabitants and representing more than 9% of the Italian population (Figure 3). In such environmental settings featuring a huge—and spatially polarized—increase in human pressure, the average score of the ESAI rose, at the regional level, from 1.34 in 1960 to 1.36 in 2020, with annual percent variations amounting to +0.03% between 1960 and 1990 and +0.02% between 1990 and 2020. This trend reflects a moderate—while generalized—worsening of ecological conditions, especially (but not exclusively) in the first time window investigated here, from 1960–1990 (Table 2).

3.2. Descriptive Statistics

More specifically, the most frequent ESAI score classes in the early 1960s reflected land classified at intermediate risk (1.30–1.40) and medium-low risk (1.20–1.30), with surface areas extending up to 38% of the spatial coverage of this study. Both for 1990 and 2020, these classes underwent a slight reduction in size (33% and 30%, respectively, of the regional area, to the advantage of the medium-high risk class (1.40–1.50)). Land classified as ‘critically’ exposed to soil degradation (ESAI > 1.50) also expanded from 1.7% (1960) to 7.5% (2020) of the regional surface area in Latium. After an initial expansion from 0.3% (1960) to 3.4% (1990), land experiencing a very low risk (ESAI < 1.20) expanded slightly in 2020 (4.1%). Between 1960 and 1990, the absolute range (maximum–minimum score) of the ESAI arose by 0.11%, increasing even more between 1990 and 2020 (0.52%). In the first time window (1960–1990), there was a decrease in both the minimum and the maximum ESAI scores, respectively, by 0.13% and 0.07%. In the second time window (1990–2020), the minimum value remained almost stable, and the maximum value rose moderately (+0.16%), reflecting an increase in territorial disparities behind soil degradation that may underlie a spatially unbalanced mechanism of land resource depletion.
A descriptive scrutiny of the explicit trend in the predisposing factors delineates how climate and vegetation cover display, on average, medium-high quality at the regional level, despite a slight worsening observed in the last sixty years. A generalized medium-low soil quality appears to be a factor of potential degradation, while in opposition with the other indicators, the quality of land management, initially set at intermediate values, improved moderately over time. Interestingly, the resident population settled primarily (96–97%) in areas classified at intermediate risk (1.3 < ESAI < 1.4).

3.3. Spatial Analysis

A refined investigation of the statistical distribution of the ESAI scores using Nuts-3 provinces as the elementary analysis units outlines inhomogeneous spatial trends, distinguishing Viterbo and Rieti (northern and rural Latium) from the remaining provinces. The former context experienced a slight, average improvement in their predisposing conditions; the latter context underwent worse and worse predisposing conditions (Figure 4). The Rome province was classified at the highest risk in comparison with the surrounding territories, as a result of the exceptionally high human pressure. In other words, the average profile of soil degradation status in Latium, based on a comparative, diachronic scrutiny of the ESAI scores, seems to be greatly influenced by the inherent (environmental and socioeconomic) dynamics observed in metropolitan Rome.

4. Discussion

A simplified (interpretative) framework assuming environmental, social, and economic factors as increasing spatial inequalities in land resource distribution along the elevation gradient was adopted in this study, testing their impacts on soil degradation processes. Although a number of empirical exercises based on elementary indicators and composite indexes of soil degradation have been carried out at different spatial scales and geographical coverages in the Mediterranean region, relatively few applications were aimed at ascertaining the impact of specific determinants of degradation at the local scale. Our study specifically assumes socioeconomic and environmental disparities as shaping the regional distribution of land resource availability [54].
High levels of soil degradation, as measured using the ESAI framework, were observed in the study area, likely because of the joint impact of human pressure and local warming [45]. Considering territorial disparities in land resources as a driver of local-scale, early desertification risk, earlier studies carried out in flat districts of the study area demonstrated how intense droughts, soil aridity and poor land management, reduced water availability, settlement sprawl, overgrazing, and wildfires may leverage soil sealing, salinization, and compaction [56]. These are the most relevant mechanisms triggering land resource depletion and soil degradation in such socioeconomic contexts [27]. In steep zones, soil degradation was dependent upon the latent interaction between defined socioeconomic pressures, e.g., rural depopulation and land abandonment, soil erosion, farm-holders’ ageing, unwanted woodland expansion, and extensification of agricultural systems [38,39,40]. Meanwhile, at the regional scale, the latter dynamics could even mitigate the effects of the former ones—accounting for a stable level of soil degradation over time. A local-scale analysis clearly revealed the increasing fragility of both flat and steep land in the study area [41].
Empirical studies, like the one illustrated in the present article, have implications of both positive (i.e., research) and normative nature (i.e., policy support), in line with earlier research (e.g., [41] and references therein). Results of this study confirm how a balanced strategy targeting a spatially sustainable regional development should be adopted in Latium and similar regions, mitigating the impact of rapid economic growth in coastal/lowland (more accessible) areas at the expenses of internal, marginal zones [52]. Considering multiple soil degradation systems together means impacting well-defined causal chains that feature complex interrelationships among relevant environmental processes [53]. A multilevel strategy acting at different scales (national, regional, and local) and involving multiple agents (municipalities, irrigation consortia, farmers’ groups, syndicates, and cooperatives) should focus on drivers targeting causal chains, regionalizing general approaches, and promoting stakeholders’ participation at all the relevant governance levels, not only at the local scale [27]. Consequently, the latent ‘message in the bottle’ of our empirical exercise is that local-based policy strategies mitigating land resource depletion in Mediterranean Europe may benefit from a ‘vision’ change from driver-specific to process-specific targets [52].
Assuming the spatial interaction between ‘social’ pressures and ‘ecological’ factors at the base of soil degradation trends in the study area and, more generally, along the elevation gradient in representative Mediterranean regions, the specific investigation of ‘sustainable development’ paths stemming from the empirical results of this study highlights the crucial role of long time-series data and indicators [47]. They are especially vital when applying sophisticated statistical techniques to socio-ecological problems [51]. With the reduction in local-scale variability of the composite index of soil degradation as a consequence, such differential processes observed along the elevation gradient in Central Italy are likely due to anthropogenic factors affecting land use and leveraging (i) crop intensification in flat districts and (ii) farmland abandonment in steep areas [50]. With this perspective in mind, the original contribution of this study lies in the use of a standard index of soil degradation as a proxy of territorial disparities [34]. The consequent analysis, based on simplified (descriptive and graphical) tools, outlines the importance of soil degradation at the base of persistent conditions for spatial inequalities [59].

5. Conclusions

To our knowledge, likely for the first time in advanced economies, the present study provides a historical analysis of soil degradation, considering past (1960–2010), present (2020), and future (2030) points in time, representing an additional novelty in the academic literature dealing with early desertification processes. The negative soil degradation trends envisaged in this empirical exercise—and the consequent, increasing rate of land resource depletion forecast for the coming future—explicitly document the role of multilevel environmental and social policies in the alleviation of land degradation risk in Southern Europe. This definitely represents an original contribution to a refined comprehension of socioeconomic and environmental processes at the base of a territorially balanced sustainable development.

Author Contributions

Conceptualization, M.M. and F.M.C.; methodology, L.S.; software, M.M.; validation, M.M.; formal analysis, L.S.; investigation, F.M.C.; resources, F.M.C.; data curation, M.M.; writing—original draft preparation, L.S. and F.M.C.; writing—review and editing, M.M. and L.S.; visualization, M.M.; supervision, L.S.; project administration, L.S.; funding acquisition, L.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Official statistics released by multiple national and communitarian authorities, including the Italian National Statistical Institute (Istat), the National Institute for Environmental Research and Protection (Ispra), the European Environment Agency (Eea), and Eurostat, were used in this study.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. (Left) A map of Italy indicating the position of the Latium region (in red) and illustrating the spatial distribution of a simplified aridity index (average values between 1951 and 1980), indicating Latium as a traditional sub-humid region at that time (see Section 2.1); (middle) the administrative structure governing land; red indicates the boundaries of the Nuts-3 provinces (VT: Viterbo, RI: Rieti, RM: Rome, LT: Latina, and FR: Frosinone), and gray indicates the boundaries of the Nuts-5 municipalities; (right) the altimetry (right) of the Latium region; three color tones with different darknesses were used to outline the elevation gradient (light: <100 m at the sea level; intermediate: 101–500 m at the sea level; dark: >500 m at the sea level).
Figure 1. (Left) A map of Italy indicating the position of the Latium region (in red) and illustrating the spatial distribution of a simplified aridity index (average values between 1951 and 1980), indicating Latium as a traditional sub-humid region at that time (see Section 2.1); (middle) the administrative structure governing land; red indicates the boundaries of the Nuts-3 provinces (VT: Viterbo, RI: Rieti, RM: Rome, LT: Latina, and FR: Frosinone), and gray indicates the boundaries of the Nuts-5 municipalities; (right) the altimetry (right) of the Latium region; three color tones with different darknesses were used to outline the elevation gradient (light: <100 m at the sea level; intermediate: 101–500 m at the sea level; dark: >500 m at the sea level).
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Figure 2. A summary schematization of the elementary variables, thematic (quality) indicators, and the composite Environmentally Sensitive Area Index, ESAI.
Figure 2. A summary schematization of the elementary variables, thematic (quality) indicators, and the composite Environmentally Sensitive Area Index, ESAI.
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Figure 3. The spatial distribution of the average population density in the Latium region by municipality and province in 1961 (left) and 2021 (right); three color tones with different darknesses were used to highlight increasing density (light: <200 inhabitants/km2; intermediate: 201–500 inhabitants/km2; and dark: >500 inhabitants/km2); VT: Viterbo; RI: Rieti; RM: Rome; LT: Latina; FR: Frosinone).
Figure 3. The spatial distribution of the average population density in the Latium region by municipality and province in 1961 (left) and 2021 (right); three color tones with different darknesses were used to highlight increasing density (light: <200 inhabitants/km2; intermediate: 201–500 inhabitants/km2; and dark: >500 inhabitants/km2); VT: Viterbo; RI: Rieti; RM: Rome; LT: Latina; FR: Frosinone).
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Figure 4. Spatial distribution of ESAI scores in Latium; 1960 (upper left), 1990 (upper right), 2020 (lower left), and percent difference between the beginning and the end of the observation period (lower right); white pixels indicate completely built-up areas (such as compact settlements in cities), lakes, and mountainous rocks/permanent glaciers that were not evaluated for soil degradation.
Figure 4. Spatial distribution of ESAI scores in Latium; 1960 (upper left), 1990 (upper right), 2020 (lower left), and percent difference between the beginning and the end of the observation period (lower right); white pixels indicate completely built-up areas (such as compact settlements in cities), lakes, and mountainous rocks/permanent glaciers that were not evaluated for soil degradation.
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Table 1. A summary synopsis of the ESA weighting system (score) by elementary variable and the respective quality indicator (SQI, CQI, VQI, and MQI); abbreviations for texture classes: C, clay; SiC, silty clay; SiCL, silty clay loam; CL, clay loam; SC, sandy clay; SiL, silt loam; L, loam; SCL, sandy clay loam; SL, sandy loam; Si, silt; LS, loamy sand; and S, sand.
Table 1. A summary synopsis of the ESA weighting system (score) by elementary variable and the respective quality indicator (SQI, CQI, VQI, and MQI); abbreviations for texture classes: C, clay; SiC, silty clay; SiCL, silty clay loam; CL, clay loam; SC, sandy clay; SiL, silt loam; L, loam; SCL, sandy clay loam; SL, sandy loam; Si, silt; LS, loamy sand; and S, sand.
Soil Quality (SQI)Vegetation Quality (VQI)
Texture Fire Risk Corine ClassScore
S2.00Barren; permanent agriculture; crops2.1.2., 2.2.1., 2.2.2., 2.2.3, 3.3.3, 3.3.4, 4.2.31.00
Si, C, SiC1.67Cereals; grasslands; deciduous forests2.1.1., 2.4.1., 2.4.2., 2.4.3, 2.4.4., 3.1.1., 3.1.3., 3.2.1, 3.2.41.33
SC, SiL, SiCL1.33Mediterranean maquis3.2.31.67
L, SCL, SL, LS, CL1.00Conifer3.1.22.00
Soil depthSoil erosion protection
<152.00Mixed Mediterranean maquis-evergreen wood2.4.4., 3.1.3., 3.2.4.1.0
15–301.67Mediterranean maquis; conifer wood; evergreen permanent agriculture (olive trees); permanent grassland3.2.3., 3.1.2., 3.2.1., 3.2.3.1.3
30–751.33Deciduous wood3.1.1.1.6
>751.00Permanent agriculture (orchard)2.2.2.1.8
Crops; grasslands; barren2.1.1., 2.1.2., 2.2.1., 2.4.1.,
2.4.2., 2.4.3., 3.3.3., 3.3.4., 4.2.3.		2.0
Avai. water capacityDrought resistance
<802.00Mixed Mediterranean maquis-evergreen wood3.2.3., 3.2.4., 3.3.3., 3.3.4.1.0
80–1201.67Conifer; deciduous; olives2.2.3., 3.1.1., 3.1.2., 3.1.3.1.2
120–1801.33Permanent agriculture2.2.1., 2.2.2., 2.4.4.1.4
>1801.00Permanent grasslands2.4.1., 3.2.1., 4.2.3.1.7
SlopeCrops; barren2.1.1., 2.1.2., 2.4.2., 2.4.3.2.0
>35%2.00Vegetation cover
18–35%1.67>40% 1.0
6–18%1.3310–40%2.1.1., 2.2.1., 2.2.2., 2.2.3., 2.4.1., 2.4.2., 2.4.3., 2.4.4., 3.2.1., 4.2.3.1.8
<6%1.00<10%3.3.3., 3.3.4.2.0
Climate Quality (CQI)Land Management Quality (MQI)
Aridity indexLand-use intensityCorine classScore
<0.52.0Olive; deciduous and conifer wood; Mediterranean maquis2.1.2., 2.2.1., 2.2.2., 2.4.2.1.00
0.5–0.651.8Mixed woodland–farmland areas3.2.4., 3.3.4.1.33
0.65–0.81.6Annual crops (not irrigated); permanent grassland2.1.1., 2.3.1., 2.4.1., 2.4.3.1.67
0.8–1.01.4Permanent (and irrigated) agriculture2.1.2., 2.2.1., 2.2.2., 2.4.2.2.00
1.0–1.51.2Population density
>1.51.0<100 1.0
Annual rainfall rate100–200 1.2
<2802.0200–400 1.4
280–6501.5400–700 1.6
>6501.0700–1000 1.8
Exposition >1000 2.0
−1°1.00Population growth rate
225–359°1.00<20% 1.0
0–135°1.0020–40% 1.5
136–224°2.00>40% 2.0
Table 2. Statistical distribution of the average Environmentally Sensitive Area Index (ESAI) scores in the study area by administrative level (region: Nuts-2 level; province: Nuts-3 level) and year (soil quality—assessed on the basis of structural soil attributes that change rarely and over broader temporal scales—was assumed as being stable over time; see Section 2.2.2 for details); ESAI scores ranged from 1, the lowest degradation level, to 2, the highest degradation level.
Table 2. Statistical distribution of the average Environmentally Sensitive Area Index (ESAI) scores in the study area by administrative level (region: Nuts-2 level; province: Nuts-3 level) and year (soil quality—assessed on the basis of structural soil attributes that change rarely and over broader temporal scales—was assumed as being stable over time; see Section 2.2.2 for details); ESAI scores ranged from 1, the lowest degradation level, to 2, the highest degradation level.
Variable196019902020% Change, 1960–1990% Change, 1990–2020
Average ESAI, score1.341.351.360.030.02
Percent share of land classified at different levels of soil degradation (ESAI score)
<1.20.33.44.031.90.5
1.2–1.338.329.028.9−0.80.0
1.3–1.438.932.829.6−0.5−0.2
1.4–1.519.733.030.02.3−0.2
>1.52.71.87.5−1.16.3
Statistical distribution of ESAI scores
Minimum1.171.131.12−0.130.00
Maximum1.631.611.65−0.070.16
Absolute range0.460.470.520.110.53
Predisposing factors (thematic indicators of the ESAI, score)
Climate quality1.081.171.140.28−0.14
Vegetation quality1.511.531.530.040.00
Land management1.361.311.34−0.120.12
Soil quality-1.48---
NUTS-3 provinces (ESAI score)
Viterbo1.341.381.370.09−0.02
Rieti1.301.321.290.04−0.10
Rome1.371.381.410.010.10
Latina1.341.351.370.040.07
Frosinone1.301.311.320.020.02
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Maialetti, M.; Salvati, L.; Chelli, F.M. Sustainable Development, Territorial Disparities in Land Resources, and Soil Degradation: A Multi-Temporal Approach. Resources 2024, 13, 125. https://doi.org/10.3390/resources13090125

AMA Style

Maialetti M, Salvati L, Chelli FM. Sustainable Development, Territorial Disparities in Land Resources, and Soil Degradation: A Multi-Temporal Approach. Resources. 2024; 13(9):125. https://doi.org/10.3390/resources13090125

Chicago/Turabian Style

Maialetti, Marco, Luca Salvati, and Francesco Maria Chelli. 2024. "Sustainable Development, Territorial Disparities in Land Resources, and Soil Degradation: A Multi-Temporal Approach" Resources 13, no. 9: 125. https://doi.org/10.3390/resources13090125

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