在对M cfeeters提出的归一化差异水体指数(NDWI)分析的基础上,对构成该指数的波长组合进行了修改,提出了改进的归一化差异水体指数MNDWI(M odified NDWI),并分别将该指数在含不同水体类型的遥感影像进行了实验,大部分获得了比NDWI好的效果,特别是提取城镇范围内的水体。NDWI指数影像因往往混有城镇建筑用地信息而使得提取的水体范围和面积有所扩大。实验还发现MNDWI比NDWI更能够揭示水体微细特征,如悬浮沉积物的分布、水质的变化。另外,MNDWI可以很容易地区分阴影和水体,解决了水体提取中难于消除阴影的难题。

A modified normalized difference water index(MNDWI) has been proposed in this paper based on the normalized difference water index(NDWI) of Mcfeeters (1966), which uses MIR(TM5) instead of NIR(TM4) to construct the MNDWI. The MNDWI has been tested in the ocean, lake and river areas with the background of built-up lands and/or vegetated lands, and with both clean and polluted water bodies using Landsat TM/ETM imagery. This reveals that the MNDWI can significantly enhance the water information, especially in the area mainly with built-up land as background. The MNDWI can depress the built-up land information effectively while highlighting water information, and accurately extract the water body information from the study areas. While the enhanced water information using the NDWI always has been mixed with built-up land noise and the area of a water body extracted based on the index is thus overestimated. Therefore, the NDWI is not suitable for enhancing and extracting water information in built-up land-dominated areas. Furthermore, the MNDWI can reveal subtle features of water more efficiently than the NDWI or other visible spectral bands do due largely to its wider dynamic data range. The application of the MNDWI in the Xiamen image has achieved an excellent result. The MNDWI image successfully reveals significant non-point pollution of the water surrounding the Xiamen Island due to agricultural activities. In addition, taking the advantage of the ratio computation, the MNDWI can remove shadow noise from water information without using sophisticated procedures, which is otherwise difficult to be removed.