1. Based on the thematic maps of land use, vegetation coverage and slope, the soil erosion intensity was classified according to the classification rules by using ArcGIS software. 2. The land use processing method is based on ecognition software platform, using the method of object-oriented computer automatic classification and manual visual interpretation to extract the annual land use data of the study area. Finally, three methods are used to verify the data accuracy: field sample point survey, high resolution image recognition and Google Earth sample point recognition. 3. The vegetation coverage processing method is based on remote sensing estimation, and the normalized vegetation index (NDVI) is used to estimate the vegetation coverage by using the pixel binary model method. Firstly, the NDVI of each pixel is calculated by using the near-infrared band and red band data of multispectral images, and then the vegetation coverage of the whole region is calculated by using the model, and the vegetation coverage is classified according to the classification rules. Finally, the land use type data obtained from remote sensing interpretation and the vegetation coverage data estimated based on remote sensing are used for superposition operation to obtain each pixel Vegetation coverage information of each pixel. 4. Slope data processing method is based on 1:50000 DEM extraction.

1. Based on the thematic maps of land use, vegetation coverage and slope, the soil erosion intensity was classified according to the classification rules by using ArcGIS software. 2. The land use processing method is based on ecognition software platform, using the method of object-oriented computer automatic classification and manual visual interpretation to extract the annual land use data of the study area. Finally, three methods are used to verify the data accuracy: field sample point survey, high resolution image recognition and Google Earth sample point recognition. 3. The vegetation coverage processing method is based on remote sensing estimation, and the normalized vegetation index (NDVI) is used to estimate the vegetation coverage by using the pixel binary model method. Firstly, the NDVI of each pixel is calculated by using the near-infrared band and red band data of multispectral images, and then the vegetation coverage of the whole region is calculated by using the model, and the vegetation coverage is classified according to the classification rules. Finally, the land use type data obtained from remote sensing interpretation and the vegetation coverage data estimated based on remote sensing are used for superposition operation to obtain each pixel Vegetation coverage information of each pixel. 4. Slope data processing method is based on 1:50000 DEM extraction.

<p>1. The remote sensing images are preprocessed by radiation correction, orthorectification, fusion and mosaic. 2. The actual surface area corresponding to the minimum patch area is not less than 0.1 Hm2, the polygon has no overlap, no gap, and the patch attribute has no vacancy or redundancy. 3. Before remote sensing image interpretation, remote sensing image, typical survey and field comparison were used to establish the remote sensing interpretation marks of forest and grass plot. 4. Based on the remote sensing image, combined with the interpretation signs, extract the land use types. 5. Review of interpretation results: extract no less than 5% of the total map spots for verification. 6. The number of field verification samples and results meet the requirements of technical specification for remote sensing monitoring of soil and water conservation (sl592-2012). For the verification map spots, 10% of the verification samples are selected for field verification. </p>