| Technology and Methodology |
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A Method for Object-oriented Automatic Extraction of Lakes in the Mountain Area from Remote Sensing Image |
| SHEN Jin-xiang1,2, YANG Liao1, CHEN Xi1, LI Jun-li1, PENG Qing-qing1,2, HU Ju1,2 |
1. Remote Sensing and GIS Application Laboratory, Xinjiang Ecology and Geography Institute, Chinese Academy of Science, Urumqi 830011, China;
2. Graduate University of Chinese Academy of Science, Beijing 100049, China |
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Abstract Traditional water-body information extraction is mainly based on the reflection and absorption spectral characteristics of the water body. By building and using all kinds of spectral index models which respond to the water spectral characteristics more obviously, the water body could be extracted in pixel-level. However, different types of water bodies have significantly different spectral and spatial patterns as well as spatial distributions. As for the mountain area image, the shadows of such objects as the mountain, snow, ice and bare rock make these global water spectral index models fail to get a satisfactory result. The object-oriented image analysis carries out remote sensing image segmentation first, and then analyzes the global and local characteristics of the water in such aspects as spectral and spatial patterns, spatial distribution, and spatial relationships so as to build the water extraction decision ruleset; finally, the water body information is extracted with the ruleset automatically. The Landsat TM image water extraction experiment in the eCognition software shows that the method can completely avoid the emergence of some errors of "sporadic water body" which often exist in the pixel-level threshold value extraction, and the mountain area lakes could be extracted automatically and efficiently, with the accuracy up to 95% or even higher in the cloud-free case.
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| Keywords
remote sensing
aquaculture
information extraction.
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Issue Date: 20 August 2012
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2012,
Vol. 24
