A water index for rapid mapping of shoreline changes of five East African Rift Valley lakes: an empirical analysis using Landsat TM and ETM+ data

Abstract

Because of the complicated shorelines, inaccessibility and vast spread of some lakes, information on changing shorelines is difficult to acquire. A new water index (WI) has been applied to quantify changes in five saline and non-saline Rift Valley lakes in Kenya using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM + ) data. The WI is based on a logical combination of the Tasseled Cap Wetness (TCW) index and the Normalized Difference Water Index (NDWI). Using regression analysis with estimated shoreline coordinates, the WI detected the shorelines with an accuracy of 98.4%, which was 22.3% higher than the TCW, and 43.2% more accurate than the NDWI. Change detection was derived using image differencing followed by density slicing and unsupervised classification. The saline lakes (Bogoria, Nakuru and Elementaita) changed more with respect to the ratio of the change in the original surface areas than the non-saline lakes (Baringo and Naivasha)