Object-oriented Method for Rural Residential Land Extraction in the Hilly Areas of Southern China Using RapidEye Data

  • 1 State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2 University of Chinese Academy of Sciences, Beijing 100049, China;
    3 Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China

Received date: 2016-03-14

  Online published: 2016-07-25

Supported by

National Natural Science Foundation of China (41301474); National Science & Technology Infrastructure Work Special Projects of China(2011FY110400, 2013FY114600) and the China Postdoctoral Science Foundation (2013M530708, 2014T70114)


The process of rapid urbanization in China features two opposing trends: declining rural population and increasing rural residential land, especially in southern hilly areas. The extraction and analysis of residential land in rural China represents an important application for remote sensing technology. The study aimed to discover rural residential land information using RapidEye satellite imagery, taking Taihe County as the research area in the hilly region of southern China. Based on multiple experiments, classification was conducted with an optimal image segmentation scale set to 200. The object-oriented classification rule set was constructed using the customized parameters NDVI, NDWI, brightness, and length/width. The areas of residential land and other land use types were interpreted by varying the parameter values for classification rule sets. Finally, validation and accuracy evaluations were carried out. The overall accuracy of residential land interpretation is 78.40%, and producer’s accuracy and user’s accuracy are 68.75% and 77.33%, respectively. The results indicate that RapidEye provides a suitable data source for extraction of rural residential land using an object-oriented approach. Compared with the second national land survey of China, the classification gave an absolute difference of 93.67 ha residential land within the study area. Recognition errors occurred mainly in regions adjacent to the boundaries between residential land and other types of land.

Cite this article

GAO Mengxu, WANG Juanle, BAI Zhongqiang . Object-oriented Method for Rural Residential Land Extraction in the Hilly Areas of Southern China Using RapidEye Data[J]. Journal of Resources and Ecology, 2016 , 7(4) : 291 -300 . DOI: 10.5814/j.issn.1674-764x.2016.04.008


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