Remote Sensing | |
Exploring the Use of Google Earth Imagery and Object-Based Methods in Land Use/Cover Mapping | |
Qiong Hu1  Wenbin Wu1  Tian Xia1  Qiangyi Yu1  Peng Yang1  Zhengguo Li1  | |
[1] Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing 100081, |
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关键词: Google Earth; QuickBird; land use/cover; object-based; classification; | |
DOI : 10.3390/rs5116026 | |
来源: mdpi | |
【 摘 要 】
Google Earth (GE) releases free images in high spatial resolution that may provide some potential for regional land use/cover mapping, especially for those regions with high heterogeneous landscapes. In order to test such practicability, the GE imagery was selected for a case study in Wuhan City to perform an object-based land use/cover classification. The classification accuracy was assessed by using 570 validation points generated by a random sampling scheme and compared with a parallel classification of QuickBird (QB) imagery based on an object-based classification method. The results showed that GE has an overall classification accuracy of 78.07%, which is slightly lower than that of QB. No significant difference was found between these two classification results by the adoption of
【 授权许可】
CC BY
© 2013 by the authors; licensee MDPI, Basel, Switzerland
【 预 览 】
Files | Size | Format | View |
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RO202003190031368ZK.pdf | 4631KB | download |