Analysis of Spatial and Temporal Variability of Global Wetlands during the Last 20 Years Using GlobeLand30 Data
Abstract
:1. Introduction
2. Data and Methods
2.1. Data
2.2. Characteristic Metrics of Wetland Changes
2.2.1. Change Assessment Metrics
- (1)
- Change in Area
- (2)
- Rate of Change
- (3)
- Change Importance Index
2.2.2. Lorenz Curve and Gini Coefficient
2.2.3. Land Cover Conversion Matrix
3. Results and Analysis
3.1. Changes in Global Wetlands
3.2. Analysis of the Conversions between Wetland with Other Land Cover Types
- Four land cover types, including forest, grass, water, and tundra, were prominent in the conversion to wetlands, accounting for more than 70% and 80% of the increase and decrease areas of wetlands, respectively, according to the conversion importance indices shown in Table 2.
- The conversion from forest, grass, and bare land led to a significant net increase in wetlands, and the conversion from wetland to tundra led to a significant net decrease in wetlands. The conversions between wetlands and other land-cover types were almost balanced.
- According to the major types converted with wetlands, it may indicate that the conversions may be mainly affected by natural factors, such as wetland degradation due to climate warming resulting in conversion to tundra, grass, etc. [28,42]; water expansion submerging the surrounding grass and forest, resulting in the conversion to wetlands [43]; sea-level rise resulting in the loss of coastal wetlands [42,44,45].
- Figure 5a shows the increase in wetland area and the details of other land cover types converted to wetlands from 2000 to 2020, including: (1) the forest-to-wetland conversions were mainly in North America, Asia, and South America, with a total conversion area of 163,400 km2, accounting for approximately 77% of the total global forest-to-wetland conversion area; (2) the grassland-to-wetland conversions were mainly in Africa, Asia, and Oceania, with a total area of 186,900 km2, accounting for approximately 79% of the total global grassland-to-wetland conversion area; (3) the water-to-wetland conversions were mainly in South America, Asia, and Oceania, with a total conversion area of 103,200 km2, accounting for approximately 74% of the total global water-to-wetland conversion area. (4) The shrub-to-wetland conversions occurred mainly in North America, South America, and Africa, with a total area of 53,200 km2, accounting for approximately 84% of the total global shrub-to-wetland conversion area.
- Figure 5b shows the decrease in wetland area and the details of wetlands converted to other land cover types from 2000 to 2020, including: (1) The wetland-to-forest conversions were mainly concentrated in North America, South America, and Asia, with a total conversion area of 127,500 km2, accounting for about 79% of the total global wetland-to-forest conversion area. (2) The wetland-to-grass conversions were mainly in Asia, Africa, and South America, with a total conversion area of 83,800 km2, accounting for about 73% of the total global wetland-to-grassland conversion area. (3) The wetland-to-water conversions were mainly distributed in Asia, North America, and South America, with a total conversion area of 96,100 km2, accounting for about 83% of the total global wetland-to-water body conversion area. (4) The wetland-to-tundra conversions occurred only in North America, Europe, and Asia, with a total area of 155,800 km2. (5) The wetland-to-shrub conversions were mainly in North America, South America, and Africa, with a total area of 26,500 km2, accounting for approximately 87% of the total wetland-to-shrubland conversion area.
- From 2000 to 2010 and 2010 to 2020, the total area of wetlands converted from other land types was approximately 366,200 km2 and 405,500 km2, respectively, and the total area of wetlands converted to other land types was 342,200 km2 and 303,100 km2, respectively.
- Four land cover types, including forest, grass, water, and tundra, were prominent in the conversion to wetlands for both periods, according to the conversion importance indices shown in Table 3.
- According to Figure 6, from 2000 to 2010, the conversion from water and tundra led to a net increase in wetlands, the conversion of wetland-to-grass led to a net decrease in wetlands, and the conversions between wetland and other land cover types were almost balanced. According to Figure 7, from 2010 to 2020, the conversion from forest, grass, shrub, and bare land led to a net increase in wetlands; the conversion of wetland-to-tundra led to a net decrease in wetlands; conversions between wetland and other land cover types were almost balanced.
- By comparing Figure 6 with Figure 7, it can be found that: (1) the conversion areas of grass-to-wetland from 2010 to 2020 contributed considerably to the net increase in wetlands, which was more than six times that of the wetland-to-grass, while there was little difference from 2000 to 2010, and forest and shrub had almost the same situation; (2) the conversion areas of wetland-to-tundra were significantly more than those of tundra-to-wetland from 2010 to 2020, which had a considerable contribution to the net decrease in wetlands, while the opposite was true from 2000 to 2010.
- As illustrated in Figure 8, North America and Africa had net decreases in wetland areas, while other continents had net increases in wetland areas from 2000 to 2010. By comparing Figure 8a with Figure 8b, it can be found that the main types of land covers converted with wetland and the amounts of the conversions to/from wetland were almost the same in each continent.
- As illustrated in Figure 9, North America and Europe had net decreases in wetland areas, whereas other continents had net increases in wetland areas from 2010 to 2020. By comparing Figure 9a with Figure 9b, it can be found that except South America, there were larger differences for the main types of land covers converted with wetland and the amounts of the conversions to/from wetland in other continents during the period.
3.3. Analysis on Equality of Wetland Changes of Global Countries
- As shown in Figure 12a, the Lorenz curve has a high curvature, and approximately 10% of countries have more than 50% of the increase in global wetland area. The Gini coefficient is 0.59 (>0.5 indicates a significant inequality), indicating that the increase in global wetland area was uneven. The three countries with the highest increases in wetland area were Russia, Australia, and Bolivia, accounting for 46% of the global increase in wetland area.
- As shown in Figure 12b, the curvature of the Lorenz curve of the wetland area decreased from 2000 to 2010, and approximately 15% of the countries experienced nearly 70% of the decrease in global wetland area. Its Gini coefficient is 0.69 (>0.5 indicates a significant inequality), indicating that the decrease in global wetland area was more uneven. The three countries with the highest decreases in wetland area were Mali, the Democratic Republic of Congo, and Chad, with a 49% decrease in the global wetland area.
- As shown in Figure 13a, the Lorenz curve has the highest curvature, and approximately 10% of countries have more than 80% of the increase in global wetland area. Its Gini coefficients is 0.86 (>0.5 indicates a significant inequality), indicating that the increase in global wetland area was extremely uneven. The three countries with the highest increases in global wetland area were Australia, Chad, and Kazakhstan, accounting for 60% of the total increase in global wetland area.
- As shown in Figure 13b, the curvature of the Lorenz curve of wetland area decreases for 2010 to 2020 is the smallest, and the curve is close to the perfect equality line because its Gini coefficient is 0.10 (<0.2 indicates perfect equality). The three countries with the largest decreases in wetland area in this period were Canada, Norway, and Finland, with a 97% decrease in global wetland area.
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Oceania | Africa | Asia | South America | Europe | North America | Total | |
---|---|---|---|---|---|---|---|
Area in 2000 (104 km2) | 9.94 | 39.96 | 87.15 | 72.07 | 18.51 | 109.26 | 344.06 |
2000 to 2010 (104 km2) | +0.86 | −1.24 | +1.23 | +1.75 | +0.74 | −0.94 | +2.4 |
2010 to 2020 (104 km2) | +7.78 | +9.18 | +4.06 | +1.65 | −0.97 | −11.46 | +10.24 |
2000 to 2020 (104 km2) | +8.64 | +7.94 | +5.29 | +3.4 | −0.23 | −12.40 | +12.64 |
Landcover types | Cropland | Forest | Grass | Shrub | Water | Tundra | Artificial | Bare land | Ice | Ocean | Total |
---|---|---|---|---|---|---|---|---|---|---|---|
Conversion to Wetland (104 km2)/ Conversion important index | 3.37/ 4.37% | 21.28/ 27.58% | 23.61/ 30.59% | 6.33/ 8.20% | 13.88/ 17.99% | 2.51/ 3.25% | 0.19/ 0.25% | 5.47/ 7.09% | 0.01/ 0.01% | 0.50/ 0.65% | 77.17/ 100% |
Conversion from Wetland (104 km2)/ Conversion important index | 3.83/ 5.94% | 16.19/ 25.09% | 11.51/ 17.84% | 3.04/ 4.72% | 11.59/ 17.96% | 15.58/ 24.14% | 0.53/ 0.83% | 1.89/ 2.93% | ≈0.00/ 0.00% | 0.34/ 0.53% | 64.53/ 100% |
2000–2010 | 2010–2020 | |||
---|---|---|---|---|
Landcover Types | Conversion to Wetland (104 km2)/ Conversion Important Index | Conversion from Wetland (104 km2)/ Conversion Important Index | Conversion to Wetland (104 km2)/ Conversion Important Index | Conversion from Wetland (104 km2)/ Conversion Important Index |
Cropland | 1.54/4.21% | 2.16/6.31% | 1.83/4.51% | 1.67/5.51% |
Forest | 13.22/36.10% | 13.05/38.14% | 8.06/19.88% | 3.14/10.36% |
Grass | 8.13/22.20% | 9.19/26.86% | 15.48/38.18% | 2.32/7.65% |
Shrub | 3.09/8.44% | 2.47/7.22% | 3.24/7.99% | 0.57/1.90% |
Water | 6.47/17.67% | 4.79/14.00% | 7.41/18.27% | 6.80/22.43% |
Tundra | 2.15/5.87% | 0.81/2.37% | 0.36/0.89% | 14.77/48.73% |
Artificial | 0.10/0.27% | 0.20/0.58% | 0.09/0.23% | 0.33/1.10% |
Bareland | 1.76/4.81% | 1.32/3.86% | 3.71/9.15% | 0.57/1.88% |
Ice | 0.00/0.00% | 0.00/0.00% | 0.01/0.02% | 0.0004/0.0014% |
Ocean | 0.16/0.44% | 0.19/0.56% | 0.34/0.84% | 0.15/1.51% |
Total | 36.62 (104 km2) | 34.22 (104 km2) | 40.55 (104 km2) | 30.31 (104 km2) |
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Li, M.; Ti, P.; Zhu, X.; Xiong, T.; Mei, Y.; Li, Z. Analysis of Spatial and Temporal Variability of Global Wetlands during the Last 20 Years Using GlobeLand30 Data. Remote Sens. 2022, 14, 5553. https://doi.org/10.3390/rs14215553
Li M, Ti P, Zhu X, Xiong T, Mei Y, Li Z. Analysis of Spatial and Temporal Variability of Global Wetlands during the Last 20 Years Using GlobeLand30 Data. Remote Sensing. 2022; 14(21):5553. https://doi.org/10.3390/rs14215553
Chicago/Turabian StyleLi, Mengjuan, Peng Ti, Xiuli Zhu, Tao Xiong, Yuting Mei, and Zhilin Li. 2022. "Analysis of Spatial and Temporal Variability of Global Wetlands during the Last 20 Years Using GlobeLand30 Data" Remote Sensing 14, no. 21: 5553. https://doi.org/10.3390/rs14215553
APA StyleLi, M., Ti, P., Zhu, X., Xiong, T., Mei, Y., & Li, Z. (2022). Analysis of Spatial and Temporal Variability of Global Wetlands during the Last 20 Years Using GlobeLand30 Data. Remote Sensing, 14(21), 5553. https://doi.org/10.3390/rs14215553