The data set of land use map in Sanmenxia reservoir area of Yiluo River includes the land use of Luoning County in Henan Province, Yuanqu County of Shanxi Province and Mianchi County of Henan Province in 2013, 2014, 2015, 2016 and 2017. The format of the data is xlsx. The data is named in the form of "key governance area + administrative region + year + land use statistical table", such as "×××" Statistical table of land use in key control area ×× County ×××. The classification system of land use includes 8 first class, 22 second class and 2 third class.
The main data from USGS and Landsat were, https://glovis.usgs.gov/ ）Access, a few from China geospatial data cloud（ http://www.gscloud.cn/ ）Get
Based on ecognition software platform, the method of combining object-oriented computer automatic classification with manual visual interpretation was used to extract the annual land use data of the study area. Then three methods are used to verify the accuracy of the data: field survey, high-resolution image recognition and Google Earth sample point recognition. Finally, according to the classification standard of land use, the statistical table of land use is obtained.
The remote sensing images are preprocessed by radiation correction, orthorectification, fusion and mosaic. 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. Before remote sensing image interpretation, remote sensing image, typical survey and field comparison were used to establish remote sensing interpretation marks of land use. Based on the remote sensing image, combined with the interpretation marks, the land use types are extracted. Reexamination of interpretation results: take no less than 5% of the total map spots for verification. 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 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).
CSTR:11738.11.ncdc.HHSTBC.2020.200
10.12072/ncdc.HHSTBC.db0030.2021
