Assessing Environmental Degradation of Achanakmar-Amarkantak Biosphere Reserve and Its Ecosystem Using Google Earth Engine and Machine Learning

Anil Kumar; Hari Shankar Kumar

Assessing Environmental Degradation of Achanakmar-Amarkantak Biosphere Reserve and Its Ecosystem Using Google Earth Engine and Machine Learning

Author(s)	Anil Kumar, Hari Shankar Kumar
Country	India
Abstract	Biosphere Reserve is a meso-type region of ecosystem; it represents the bio-geographic zones in the world. The Biosphere reserves suffer drastic environmental degradation, natural calamities, and anthropogenic activities, preventing ecological growth, shrinking, and exploiting the land due to extreme climatic conditions. In this study, the Achanakmar-Amarkantak Biosphere Reserve (AABR) area has been selected and represents a biodiversity-rich ecosystem in central India. It is a lush forest; however, it has seen large-scale devastation in the context of climate change, as evidenced by increasingly unpredictable rainfall and higher temperatures between 2002 and 2022. In this scenario, there is a need for the essential application of remote sensing and machine learning techniques to monitor environmental degradation and its ecosystem in AABR. This study explores the nature of environmental degradation and its ecosystem in the study area. Using machine learning and Google Earth Engine, image classification techniques can reliably classify and map forest cover, land uses, and their spatial distributions. It will provide the long-term monitoring system by following six major spectral indices such as Land use and land cover, Normalized Difference Vegetation Index, Normalized Difference Water Index, Leaf Area Index, Normalized Difference Built-up Index, Soil Adjustment Vegetation Index, and Land Surface Temperature were determined based on the annual average between 2002 to 2022. As observed in the LST, proportionate to built-up land increases rapidly, and water bodies and vegetation cover decrease during 2002-2022. Globally, this study presents a robust methodology that can be applied to other sub-tropical regions. This study suggests appropriate conservation, management, and policies by identifying degradation and monitoring over time. Land use and climate variability changes necessitate implementing and protecting the AABR without sacrificing the natural environment.
Keywords	Environmental Degradation; Google Earth Engine; Achanakmar Biosphere Reserve; Spectral Indices
Field	Sociology
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-06-30
Cite This	Assessing Environmental Degradation of Achanakmar-Amarkantak Biosphere Reserve and Its Ecosystem Using Google Earth Engine and Machine Learning - Anil Kumar, Hari Shankar Kumar - IJFMR Volume 6, Issue 3, May-June 2024.

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Assessing Environmental Degradation of Achanakmar-Amarkantak Biosphere Reserve and Its Ecosystem Using Google Earth Engine and Machine Learning

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