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Spatial Quantification of Cropland Soil Erosion Dynamics in the Yunnan Plateau Based on Sampling Survey and Multi-Source LUCC Data
- Source :
- Remote Sensing, Vol 16, Iss 6, p 977 (2024)
- Publication Year :
- 2024
- Publisher :
- MDPI AG, 2024.
-
Abstract
- The mapping and dynamic monitoring of large-scale cropland erosion rates are critical for agricultural planning but extremely challenging. In this study, using field investigation data collected from 20,155 land parcels in 2817 sample units in the National Soil Erosion Survey, as well as land use change data for two decades from the National Land Use/Cover Database of China (NLUD-C), we proposed a new point-to-surface approach to quantitatively assess long-term cropland erosion based on the CSLE model and non-homologous data voting. The results show that cropland in Yunnan suffers from serious problems, with an unsustainable mean soil erosion rate of 40.47 t/(ha·a) and an erosion ratio of 70.11%, which are significantly higher than those of other land types. Engineering control measures (ECMS) have a profound impact on reducing soil erosion; the soil erosion rates of cropland with and without ECMs differ more than five-fold. Over the past two decades, the cropland area in Yunnan has continued to decrease, with a net reduction of 7461.83 km2 and a ratio of −10.55%, causing a corresponding 0.32 × 108 t (12.12%) reduction in cropland soil loss. We also quantified the impact of different LUCC scenarios on cropland erosion, and extraordinarily high variability was found in soil loss in different basins and periods. Conversion from cropland to forest contributes the most to cropland erosion reduction, while conversion from grassland to cropland contributes 56.18% of the increase in soil erosion. Considering the current speed of cropland regulation, it is the sharp reduction in land area that leads to cropland erosion reduction rather than treatments. The choice between the Grain for Green Policy and Cropland Protecting Strategy in mountainous areas should be made carefully, with understanding and collaboration between different roles.
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 16
- Issue :
- 6
- Database :
- Directory of Open Access Journals
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.8be098a6c69d4846a3dd9bfc44cc3c76
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/rs16060977