where GREEN is a green band such as TM2, and NIR is anear infrared band such as TM4. This index maximizes reflectance of water by using green light wavelengths and minimizes low reflectance of NIR by water features while taking advantage of the high reflectance of NIR by vegetation and soil features. As a result, water features are enhanced owing to having positive values and vegetation and soil are suppressed due to having zero or negative values. However, the applications of the NDWI in the water regions with built-up land background like the cases of Quanzhou and Fuzhou cities were not as successful as expectation. The extracted water information in these regions was often mixed up with built-up land noise because many
built-up lands also have positive values in the NDWI-derived image. The signature features of built-up land in green band (TM2) and NIR band (TM4) shown in Figure 3 are similar with those of water, i.e., they both reflect green light more than reflect near infrared light. Consequently, the computation of the NDWI also produces a positive value for built-up land just as for water. Table 3 shows that the built-up land class in both Quanzhou and Fuzhou images has positive mean values. To remedy this problem, Xu (2005) modified the NDWI by using a middle infrared (MIR) band such as TM5 to
substitute the NIR band in the NDWI. The modified NDWI (MNDWI) is expressed as follows: