期刊
REMOTE SENSING
卷 5, 期 11, 页码 6026-6042出版社
MDPI
DOI: 10.3390/rs5116026
关键词
Google Earth; QuickBird; land use; cover; object-based; classification
类别
资金
- National High Technology Research and Development Programme of China [2012AA12A304]
- National Basic Research Program of China (973 Program) [2010CB951504]
- National Natural Science Foundation of China [41271112]
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 Z-test, which strongly proved the potentials of GE in land use/cover mapping. Moreover, GE has different discriminating capacity for specific land use/cover types. It possesses some advantages for mapping those types with good spatial characteristics in terms of geometric, shape and context. The object-based method is recommended for imagery classification when using GE imagery for mapping land use/cover. However, GE has some limitations for those types classified by using only spectral characteristics largely due to its poor spectral characteristics.
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