Özet:

Nalsarovar Bird Sanctuary, a natural freshwater lake (a relict sea) that is the largest natural wetland in the Thar Desert Bio-geographic Province and represents a dynamic environment with salinity and depth varying depending on rainfall. For maintaining ecological balance in coastal and inland environments, wetlands play an important role and the changes in wetland environment can be monitored using satellite remote sensing technique. The present study was carried out using Landsat-7 TM (Feb-2002), Landsat-5 TM (Feb- 2009) and Sentinel-2 multi-spectral data (Feb-2018) covering Nalsarovar area in Ahmedabad district. The study area of Nalsarovar with 10 km buffer was extracted from the satellite digital data. Various spectral indices like Normalized difference Vegetation Index (NDVI), Normalized difference Water Index (NDWI) and Normalized difference Turbidity Index (NDTI) were generated for better identification and delineation of water body and aquatic vegetation in the Nalsarovar. The composite images of these indices were also generated to map and monitor changes in water spread and aquatic vegetation in the Nalsarovar. The water spread and aquatic vegetation in the Nalsarovar along with the land use classes were mapped using False Colour Composite (FCC) images of differed years. The result indicates that the water spread in Nalsarovar has changed from 2002, 2009 and 2018 depending on the monsoon pattern during these years. During drought year of 2002 total precipitation was very less resulting drastic reduction in the water spread in Nalsarovar. The aquatic vegetation has changed from 146.81 ha during 2002 to 510.93 ha during 2018. The land use change indicates that agriculture land, built-up, water body & wetland has increased and barren land, salt affected area has decreased. The aquatic vegetation in Nalsarovar was clearly visible on composite images generated using NDVI, NDWI and NDTI of different years. This study gives clear idea for land use change detection and water spread monitoring using two different techniques using Composite image of NDVI, NDWI and NDTI.

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