The data set of soil erosion statistical tables in the upper reaches of Luohe River in Jingbei province include Wuqi County, Zhidan County, Pengyang County and Yuanzhou District in 2013, 2014, 2015, 2016 and 2017. The data set is based on the processing of satellite remote sensing images with spatial resolution of 2 meters, and the format is saved For xlsx, the data is named in the form of "key control area + administrative region + year + soil erosion statistical table", such as "soil erosion statistical table of ×× key treatment area ×× County ××". The soil erosion intensity can be divided into six grades: slight erosion, mild erosion, moderate erosion, strong erosion, extremely strong erosion and severe erosion.
| collect time | 2013/01/01 - 2017/12/31 |
|---|---|
| collect place | National key treatment area in the upper reaches of Luohe River in Hebei Province |
| Data time resolution | year |
1. The land use data sources are ZY-3 and GF-1 satellite images, which are mainly obtained from the information center of the Ministry of water resources. 2. Vegetation data sources are ZY-3 and GF-1 satellite images, which are mainly obtained from the information center of the Ministry of water resources. 3.1:50000 DEM is mainly obtained from the information center of the Ministry of water resources.
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. 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.
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
Ningxia Hui Autonomous Region Zhidan County Wuqi Pengyang Shaanxi Province Yuanzhou District
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©Copyright 2005-. Northwest Institute of Eco-Environment and Resources, CAS.
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