The vegetation cover data set of the national key prevention area of Altun Mountain in 2018 includes the statistical table of forest and grass vegetation cover in Ruoqiang county and Qiemo County of Xinjiang Uygur Autonomous Region in 2018, which is based on the processing of satellite remote sensing image with spatial resolution of 2m. The saved format is xlsx. The data name adopts the form of "key management area + year + vegetation coverage statistical table", such as“ ×× Key governance areas ×× Statistical table of annual vegetation coverage. The vegetation coverage is divided into five levels: high coverage, medium high coverage, medium coverage, medium low coverage and low coverage
The data sources are ZY-3 and Gao FEN-1 satellite images, which are mainly obtained from the information center of the Ministry of water resources
Based on the method of remote sensing estimation, the normalized vegetation index (NDVI) is used to estimate the vegetation coverage by using the pixel dichotomy model. The method is to first calculate the NDVI of each pixel using the near infrared band and red band data of multispectral images, and then use the model to calculate the vegetation coverage of the whole region. Then the land use type data from remote sensing interpretation and the vegetation coverage data from remote sensing estimation are superimposed to obtain the vegetation coverage information of each pixel. Finally, according to the classification rules, the vegetation coverage was classified, and the statistical table of forest and grass vegetation coverage was obtained
1. Remote sensing images are preprocessed by radiation correction, orthorectification, fusion and mosaic. 2. The actual surface area corresponding to the minimum spot area is not less than 0.1 h ^, the polygons have no overlap, no gap, and the spot attributes have no vacancy or redundancy. 3. Before the remote sensing image interpretation, the remote sensing image, typical investigation and field comparison methods are used to establish the remote sensing interpretation marks of forest and grass sample plots. 4. Based on remote sensing images, combined with interpretation marks, extract land use types. 5. Review of interpretation results: no less than 5% of the total map spots shall be selected for verification. 6. The number and results of field verification samples meet the requirements of technical specification for remote sensing monitoring of soil and water conservation (sl592-2012). For verification spots, 10% are selected as verification samples for field verification
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