Abstract:For the conservation and management of wetland resources, it is important to monitor wetlands on a regular basis. For these purposes remote sensing can be used as a powerful tool with several advantages. Continuous reduction of water level in wetlands is one of the main reasons that lead to the loss of many wetlands worldwide. To protect and provide proper management, there are many remote sensing based methods being used. Other than the most classical method i.e. land cover change detection, a new approach was investigated. The possibility of estimating the hydrological condition of emergent vegetation of a wetland area was explored with the help of remotely sensed biophysical variables, such as surface temperature and NDVI. Based on these two biophysical variables, a digital elevation model was derived from multispectral data set. An attempt was made to explore the relations among these variables in statistical analysis, where elevation and NDVI were used as an explanatory and temperature was used as a dependant variable. Using three regression models, a relationship between surface temperature and water stress was established. It was observed that the same vegetation cover at higher elevation area had a higher surface temperature because of water stress, while at the same elevation higher NDVI resulted in lower surface temperatures. The combination of elevation(water level) and NDVI determine the surface temperature, which suggests that temperature and NDVI reflect the water stress of the emergent vegetation.Key Words: wetland; remote sensing; water stress; soil moisture