Spatio-Temporal Changes of Water Bodies using Spectral Indices in AABR, Chhattisgarh, Central India

The possibility of an ecological imbalance in forests has been pointed up because of the decreasing amount of water source in a forested area Central Indian land receives an abundant but uneven spatiotemporal distribution of rainfall and has evident seasonal water .shortages.Remote sensing and GIS techniques are employed for locating and monitoring water bodies, intended to highlight spatio-temporal change patterns of surface water bodies in the protected region of Achanakmar-Amarkantak Biosphere Reserve (AABR) from 2000 to 2020.However, Multi-temporal Landsat satellite data is thoroughly examined through the application of a spectral water indexing method.This method involves leveraging specific spectral bands Near infrared (NIR) and Shortwave infrared (SWIR) that are sensitive to the presence of water, allowing for the precise identification and mapping of water bodies over the study time periods.In study used water indices, Normalized Difference Water Index (NDWI), and Modified Normalized Difference Water Index (MNDWI) to provide significant results for extracting surface water bodies and finding out spatio-temporal changes patterns of the water bodies.The NDWI was employed for assessing the spatial extent of water bodies in the year 2000, revealing a water area of 7.0 km² during pre-monsoon and 32.4 km² for post-monsoon periods, while in 2020, the water area was measured at 22.0 km² in the pre-monsoon season and 50.9 km² in the post-monsoon season.Additionally, MNDWI) was utilized to estimate surface water body extent, indicating a water area of 8.3 km² in the pre-monsoon season and 42.1 km² in the post-monsoon season for the year 2000.In 2020, the water area was measured at 27.0 km² in the pre-monsoon season and 52.3 km² in the post-monsoon season.The monitoring of the AABR is imperative for detecting changes in the area of its surface water bodies that have transpired in recent years.This approach proves highly effective for monitoring and analyzing spatio-temporal variations in water bodies, significantly enhancing our comprehension of landscape dynamics and environmental changes.