Research Article
Land Cover Classification and Accuracy Evaluation Based on Object-Oriented Spatial Features of GF-2
@INPROCEEDINGS{10.1007/978-3-030-67720-6_21, author={Xiaomao Chen and Jiakun Li and Yuanfa Ji}, title={Land Cover Classification and Accuracy Evaluation Based on Object-Oriented Spatial Features of GF-2}, proceedings={Communications and Networking. 15th EAI International Conference, ChinaCom 2020, Shanghai, China, November 20-21, 2020, Proceedings}, proceedings_a={CHINACOM}, year={2021}, month={2}, keywords={FX GF-2 Land cover classification Accuracy evaluation Supervision classification}, doi={10.1007/978-3-030-67720-6_21} }- Xiaomao Chen
Jiakun Li
Yuanfa Ji
Year: 2021
Land Cover Classification and Accuracy Evaluation Based on Object-Oriented Spatial Features of GF-2
CHINACOM
Springer
DOI: 10.1007/978-3-030-67720-6_21
Abstract
The urbanization process has changed urban land, which has affected the environmental quality of urban residents. It is very important to obtain urban land cover information. In this paper, Yangshuo, a small country of Guilin City, is used as the research area, and the object-oriented spatial feature extraction module (Feature Extraction, hereinafter referred to as FX) is used to carry out experiments and accuracy evaluation of land cover classification in the research area. Extracting land cover information from the GF-2 remote sensing image, establishing a classification system sample based on the characteristic information of six land cover classification objects such as urban land, waterbody, woodland, farmland, road and other lands, and finally execute Supervising the classification and verify its accuracy. The results show that this method can recognize the land cover accurately and the total accuracy verified is as high as 97.41%.
