Study on Land Use Classification of Weinan Based on Landsat8

Abstract

Rapid and accurate monitoring of the dynamic change of construction land is of great significance for strictly controlling the arbitrary growth of urban construction land and protecting agricultural and forestry land. In order to master the situation of land use change and conduct more efficient research on urban land use classification, this paper takes Weinan as the research object and uses Landsat8 data under the same classification conditions to analyze the image features of various land use types respectively by using minimum distance, maximum likelihood and random forest method, and carries out land use classification research. The research shows that for the selected research area, the maximum likelihood classification method has higher classification accuracy and time efficiency, while the minimum distance and random forest can not reflect its superior classification performance, and the overall accuracy is lower than the maximum likelihood classification method, and the maximum likelihood classification method has obvious advantages. Therefore, in the classification of remote sensing image, the maximum likelihood classification method is suitable when the data dimension is low.