Research on Water Body Extraction Method Based on GF-2 High Resolution Remote Sensing Image
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摘要: 针对GF-2卫星影像数据的特点,利用单波段阈值法、多波段算法、归一化水体指数(NDWI)阈值法、单波段阈值法与阴影水体指数(SWI)相结合的决策树法对刘家峡地区的水体信息进行了提取,同时提出一种单波段阈值法与增强阴影水体指数(ESWI)相结合的决策树分类法,并对以上几种水体提取的效果进行比较分析,发现单波段阈值法与ESWI相结合的决策树分类法能够有效地消除绝大部分阴影的影响,且提取效果较SWI的效果要好,NDWI与多波段算法提取效果次之,单波段阈值法提取效果较差.Abstract: For the characteristics of GF-2 satellite image data, the water information in Liujiaxia area is extracted by singleband threshold method, multi-band algorithm, normalized difference water index threshold method(NDWI) and the decision tree method combining singleband threshold method with shadow water index(SWI). At the same time, a decision tree classification method combining single-band threshold method and enhanced shadow water index(ESWI) is proposed.The comparison of the effects of these water extraction method is carried out. It is found that the decision tree classification method combining single band threshold method with ESWI can effectively eliminate the influence of most shadows, and the extraction effect is better than that of SWI. NDWI and multiband algorithm has a second extraction effect.The single-band threshold method has a poor extraction effect.
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Key words:
- GF-2 /
- NDWI threshold method /
- water body information /
- ESWI /
- decision tree classification
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