A dataset of land use types in the Lijiang River Basin from 2016 to 2020

Since the Lijiang River Basin occupies two images, it is necessary to mosaic the two images in envi software, then cut the images according to the vector range of the Lijiang River Basin, and then fuse the green, blue and near-infrared bands into false color images. Based on the samples of the image interpretation, the training samples required for supervised classification are selected. After selecting the training samples, the maximum likelihood method is used for supervised classification, and the preliminary classification result map is obtained.

Because the preliminary classification result map has a certain "pepper and salt" phenomenon, it needs to be optimized in the later stage, that is, manually correct the pixels with large deviation, and finally use the cluster analysis method to remove the error pixels in a small range to get the final classification result map. The classification result data set is saved in a compressed package in TIF format, with names in the order of year and land_ Use as the file prefix.