Integrating Multiple Geospatial Datasets for Precise and Efficient Surface Water Extent Mapping in Malaysia

Abstract

Abstract Accurate mapping of surface water extent is essential for several applications, including water resources management, climate modelling, biodiversity conservation, agricultural irrigation, hydropower, and food security. Inland water management is critical in Malaysia due to dams, river basins, and heavy rainfall. In a tropical country, mapping surface water is challenging due to cloud cover and dense vegetation. This study proposes an approach that uses rule sets in ArcGIS Model Builder to automate the identification of water bodies. At the regional scale, the extent of surface waters can be mapped by integrating multiple geospatial datasets, including surface terrain, global surface water data, and synthetic aperture radar (SAR) imagery. Accuracy is calculated by comparing the results to high-resolution optical imagery via the SecureWatch® application. The accuracy of 200 stratified random points is 95%, with a kappa value of 0.90 for water body and land area classes. This study maps a 12,563.95 km2 study area covering several states in Malaysia. These results show that the integration of multiple geospatial datasets using rule sets and data modelling can map the extent of surface waters in Malaysia. The proposed approach could be applied in other tropical countries with similar topography.