Assessing the Impact of Climate Change on the Landscape Stability in the Mediterranean World Heritage Site Based on Multi-Sourced Remote Sensing Data: A Case Study of the Causses and Cévennes, France
Abstract
:1. Introduction
2. Materials
2.1. Study Area
2.2. Data and Pre-Processing
3. Research Framework and Methods
3.1. Research Framework
3.2. Methods
3.2.1. Relative Humidity Calculation
3.2.2. Land Cover Change Analysis
3.2.3. Landscape Stability Assessment
- (1)
- Landscape Index Selection and Calculation
- (2)
- Construction of the Landscape Stability Assessment Model
3.2.4. Geographical Detector for Climate Factor Analysis
- (1)
- Factor detection. By testing the spatial variability of individual meteorological factors, the factors with significant influence on landscape stability were identified. The formula is shown below:
- (2)
- Detection of Interactions. The relationships among various factors and their effects on the dependent variable were assessed and analyzed by computing and contrasting the q-values for individual and combined factor influences. The factors considered in this study include temperature, precipitation, potential evaporation, and relative humidity. As detailed in Table 3, we evaluated their interactions by examining each factor in combination with every other factor, offering an analysis of all possible combinations.
4. Results and Analysis
4.1. Climate Change Characteristics
4.1.1. Temperature
4.1.2. Precipitation
4.1.3. Potential Evaporation
4.1.4. Relative Humidity
4.2. Landscape Pattern Evolution
4.2.1. General Landscape Changes
4.2.2. Landscape Metrics Analysis
4.2.3. Landscape Stability Analysis
4.3. Implications of Climate Change for Landscape Stability
5. Discussion
5.1. Climate Dynamics and Their Regional Manifestations
5.1.1. General Climate Change Trends in the Heritage Site
5.1.2. Sub-Regional Climate Variations Based on Köppen–Geiger Classification
5.2. Impacts of Climatic Regional Differences and World Heritage Site Establishment on Landscape Stability
5.2.1. Impacts of Climatic Regional Differences on Landscape Stability
5.2.2. Impact Assessment of the Establishment of the “Causses and Cévennes” World Heritage Site in 2011
5.3. Limitations and Future Work
6. Conclusions
- (1)
- From 1985 to 2020, the Causses and Cévennes World Heritage Site experienced noticeable climate changes characterized by rising temperatures, a slight but non-significant increase in precipitation, enhanced potential evaporation, and a decrease in relative humidity. These changes exacerbated drought conditions within the region and signaled an increased risk of future droughts. This trend has been corroborated in broader studies.
- (2)
- The landscape types in the Causses and Cévennes Heritage Site are predominantly woodland, cropland, shrubland, and grassland. Over the 36-year period, there was a significant reduction in woodland, while the areas of shrubland, grassland, and impervious surface and bare areas increased. Cropland, wetlands, and water bodies underwent initial increases followed by decreases. Landscape-type transitions mainly occurred between woodland, cropland, shrubland, and grassland, particularly between 1985 and 2010. After 2010, transition activities were more moderate. Statistical analysis revealed increased landscape fragmentation and enhanced heterogeneity within the heritage site across the study timeline.
- (3)
- The overall stability of the landscape at the Causses and Cévennes Heritage Site exhibited a downward trend characterized by pronounced spatiotemporal variations. The Causses region had lower stability but was relatively stable, while the Cévennes region, although more stable, experienced fluctuations across different periods. Specifically, stability in the Cévennes region decreased from 1985 to 2010 and then rebounded slightly between 2010 and 2020.
- (4)
- Climatic factors significantly influenced landscape stability, with precipitation being a key factor. Although the long-term trend in precipitation was not significant, its irregularity and high volumes contributed to the expansion of unstable landscape areas. While temperature had a smaller impact, the increase in potential evaporation and the decline in relative humidity due to rising temperatures also significantly affected landscape stability. Interaction detection analysis indicated that climate change affects landscape stability through combined effects, with the interaction between precipitation and temperature being the most pronounced.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Category | Landscape Metrics | Ecological Meaning |
---|---|---|
Area and Edge metrics | Largest Patch Index (LPI) | Determine the predominant landscape type within the landscape as its dominance intensifies with ascending values. Range: [0, 100]. |
Shape metrics | Perimeter-Area Fractal Dimension (PAFRAC) | Reflects landscape shape complexity, where higher values signify increased complexity. Range: [1, 2]. |
Contrast metrics | Total Edge Contrast Index (TECI) | Describes the landscape boundary contrast, with higher values indicating a more pronounced contrast. Generally, patches with different boundary types have higher contrast; additionally, the boundary contrast between landscape types with similar ecological functions is relatively low. Range: [0, 100]. |
Aggregation metrics | Contagion Index (CONTAG) | Reflects the extent of clustering or spreading tendencies among various patch types in the landscape. A higher value signifies stronger connectivity within the landscape. Range: (0, 100]. |
Patch Density (PD) | Describes how fragmented the landscape is; a higher value signifies a greater level of fragmentation. Range: (0, +∞). | |
Diversity metrics | Shannon’s Diversity Index (SHDI) | Reflects the degree of landscape heterogeneity, with higher values indicating a more balanced distribution of landscape types. Range: [0, +∞). |
Landscape Type | Cropland | Woodland | Shrubland | Grassland | Wetland | Water Body | Impervious Surfaces | Bare Areas |
---|---|---|---|---|---|---|---|---|
Cropland | 0 | 0.3 | 0.3 | 0.3 | 0.3 | 0.3 | 0.3 | 0.3 |
Woodland | 0.3 | 0 | 0.3 | 0.1 | 0.6 | 0.9 | 0.3 | 0.6 |
Shrubland | 0.3 | 0.3 | 0 | 0.3 | 0.4 | 0.9 | 0.2 | 0.4 |
Grassland | 0.3 | 0.1 | 0.3 | 0 | 0.6 | 0.9 | 0.3 | 0.6 |
Wetland | 0.3 | 0.6 | 0.4 | 0.6 | 0 | 0.8 | 0.4 | 0.1 |
Water body | 0.3 | 0.9 | 0.9 | 0.9 | 0.8 | 0 | 0.9 | 0.8 |
Impervious surfaces | 0.3 | 0.3 | 0.2 | 0.3 | 0.4 | 0.9 | 0 | 0.4 |
Bare areas | 0.3 | 0.6 | 0.4 | 0.6 | 0.1 | 0.8 | 0.4 | 0 |
Judgment Basis | Types of Interaction |
---|---|
q(X1∩X2) < Min (q(X1), q(X2)) | Nonlinear reduction |
Min (q(X1), q(X2)) < q(X1∩X2) < Max (q(X1), q(X2)) | Univariate nonlinear reduction |
q(X1∩X2) > Max (q(X1), q(X2)) | Bivariate enhancement |
q(X1∩X2) = q(X1) + q(X2) | Mutual independence |
q(X1∩X2) > q(X1) + q(X2) | Nonlinear enhancement |
Landscape Type | 1985 | 2010 | 2020 | Rate of Change (%) | ||||
---|---|---|---|---|---|---|---|---|
Area (km2) | Percentage (%) | Area (km2) | Percentage (%) | Area (km2) | Percentage (%) | 1985–2010 | 2010–2020 | |
Cropland | 597.512 | 9.448 | 926.802 | 14.654 | 913.5 | 14.444 | 55.11 | −1.435 |
Woodland | 4809.597 | 76.049 | 4264.94 | 67.437 | 4207.393 | 66.527 | −11.324 | −1.349 |
Shrubland | 396.017 | 6.262 | 568.229 | 8.985 | 626.259 | 9.902 | 43.486 | 10.212 |
Grassland | 503.63 | 7.963 | 533.823 | 8.441 | 542.196 | 8.573 | 5.995 | 1.568 |
Wetland | 1.063 | 0.017 | 0.319 | 0.005 | 0.335 | 0.005 | −70.038 | 5.268 |
Water body | 1.785 | 0.028 | 2.023 | 0.032 | 1.984 | 0.031 | 13.314 | −1.938 |
Impervious surfaces | 14.749 | 0.233 | 28.119 | 0.445 | 32.579 | 0.515 | 90.643 | 15.864 |
Bare areas | 0 | 0 | 0.099 | 0.002 | 0.107 | 0.002 | 8.447 |
Landscape Metrics | 1985 | 2010 | 2020 | Trend |
---|---|---|---|---|
Shannon’s Diversity Index (SHDI) | 0.661 | 0.811 | 0.825 | ↑↑ |
Perimeter-Area Fractal Dimension (PAFRAC) | 1.453 | 1.468 | 1.452 | ↑↓ |
Total Edge Contrast Index (TECI) | 22.272 | 21.369 | 21.106 | ↓↓ |
Patch Density (PD) | 32.206 | 38.513 | 34.499 | ↑↓ |
Contagion Index (CONTAG) | 64.353 | 57.231 | 57.554 | ↓↑ |
Largest Patch Index (LPI) | 72.742 | 63.475 | 62.886 | ↓↓ |
Level | 1985 | 2010 | 2020 | Change in Area (km2) | |||||
---|---|---|---|---|---|---|---|---|---|
Area (km2) | Percentage (%) | Area (km2) | Percentage (%) | Area (km2) | Percentage (%) | 1985–2010 | 2010–2020 | 1985–2020 | |
Instability | 3409.480 | 54.069 | 3893.360 | 61.743 | 3735.480 | 59.239 | 483.880 | −157.88 | 326.000 |
Less stability | 126.590 | 2.008 | 13.780 | 0.219 | 22.730 | 0.360 | −112.810 | 8.950 | −103.860 |
Relatively stability | 1439.150 | 22.823 | 1400.580 | 22.211 | 1463.330 | 23.206 | −38.570 | 62.750 | 24.180 |
Stability | 932.600 | 14.790 | 900.960 | 14.288 | 966.950 | 15.334 | −31.640 | 65.990 | 34.350 |
Extremely stability | 397.960 | 6.311 | 97.100 | 1.540 | 117.290 | 1.860 | −300.860 | 20.190 | −280.670 |
Year | Factors | Temperature | Precipitation | Relative Humidity | Potential Evaporation |
---|---|---|---|---|---|
1985 | Temperature | 0.110 | |||
Precipitation | 0.547 | 0.321 | |||
Relative humidity | 0.398 | 0.494 | 0.248 | ||
Potential evaporation | 0.587 | 0.543 | 0.457 | 0.366 | |
2010 | Temperature | 0.132 | |||
Precipitation | 0.617 | 0.439 | |||
Relative humidity | 0.506 | 0.541 | 0.353 | ||
Potential evaporation | 0.582 | 0.538 | 0.533 | 0.321 | |
2020 | Temperature | 0.119 | |||
Precipitation | 0.565 | 0.397 | |||
Relative humidity | 0.488 | 0.491 | 0.300 | ||
Potential evaporation | 0.577 | 0.495 | 0.505 | 0.262 |
Landscape Type | 2000 | 2010 | 2020 | Rate of Change (%) | ||||
---|---|---|---|---|---|---|---|---|
Area (km2) | Percentage (%) | Area (km2) | Percentage (%) | Area (km2) | Percentage (%) | 2000–2010 | 2010–2020 | |
Cropland | 915.188 | 14.471 | 926.802 | 14.654 | 913.5 | 14.444 | 1.269 | −1.435 |
Woodland | 4314.303 | 68.217 | 4264.94 | 67.437 | 4207.393 | 66.527 | −1.144 | −1.349 |
Shrubland | 546.128 | 8.635 | 568.229 | 8.985 | 626.259 | 9.902 | 4.047 | 10.212 |
Grassland | 525.204 | 8.304 | 533.823 | 8.441 | 542.196 | 8.573 | 1.641 | 1.568 |
Wetland | 0.297 | 0.005 | 0.319 | 0.005 | 0.335 | 0.005 | 7.161 | 5.268 |
Water body | 2.048 | 0.032 | 2.023 | 0.032 | 1.984 | 0.031 | −1.228 | −1.938 |
Impervious surfaces | 21.092 | 0.334 | 28.119 | 0.445 | 32.579 | 0.515 | 33.314 | 15.864 |
Bare areas | 0.093 | 0.001 | 0.099 | 0.002 | 0.107 | 0.002 | 6.206 | 8.447 |
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Zhu, M.; Zhu, D.; Huang, M.; Gong, D.; Li, S.; Xia, Y.; Lin, H.; Altan, O. Assessing the Impact of Climate Change on the Landscape Stability in the Mediterranean World Heritage Site Based on Multi-Sourced Remote Sensing Data: A Case Study of the Causses and Cévennes, France. Remote Sens. 2025, 17, 203. https://doi.org/10.3390/rs17020203
Zhu M, Zhu D, Huang M, Gong D, Li S, Xia Y, Lin H, Altan O. Assessing the Impact of Climate Change on the Landscape Stability in the Mediterranean World Heritage Site Based on Multi-Sourced Remote Sensing Data: A Case Study of the Causses and Cévennes, France. Remote Sensing. 2025; 17(2):203. https://doi.org/10.3390/rs17020203
Chicago/Turabian StyleZhu, Mingzhuo, Daoye Zhu, Min Huang, Daohong Gong, Shun Li, Yu Xia, Hui Lin, and Orhan Altan. 2025. "Assessing the Impact of Climate Change on the Landscape Stability in the Mediterranean World Heritage Site Based on Multi-Sourced Remote Sensing Data: A Case Study of the Causses and Cévennes, France" Remote Sensing 17, no. 2: 203. https://doi.org/10.3390/rs17020203
APA StyleZhu, M., Zhu, D., Huang, M., Gong, D., Li, S., Xia, Y., Lin, H., & Altan, O. (2025). Assessing the Impact of Climate Change on the Landscape Stability in the Mediterranean World Heritage Site Based on Multi-Sourced Remote Sensing Data: A Case Study of the Causses and Cévennes, France. Remote Sensing, 17(2), 203. https://doi.org/10.3390/rs17020203