WETLAND HEALTH ASSESSMENT USING REMOTE SENSING: A CASE STUDY ON ASAN CONSERVATION RESERVE

Abstract

Wetlands are vital ecosystems that perform numerous ecological services, including water purification, flood control, carbon storage, and biodiversity conservation. This study focuses on the health assessment of the Asan Conservation Reserve, a Ramsar-listed wetland located at the confluence of the Asan and Yamuna rivers in Uttarakhand, India. Using advanced remote sensing and geospatial analysis techniques, this research evaluates the impact of environmental changes and human activities on the wetland over the past three decades. Key indices, such as the Normalized Difference Vegetation Index (NDVI) and Modified Normalized Difference Water Index (MNDWI), were employed to assess variations in vegetation health and water coverage. Additionally, rainfall data from 2001 to 2021, derived from the Indian Meteorological Department, and Land Use Land Cover (LULC) classifications from Landsat 7 and 8 imagery were incorporated to provide a comprehensive view of the wetland’s dynamic hydrological and ecological conditions. The analysis reveals significant fluctuations in water spread, vegetation density, and land use over time, highlighting the impacts of seasonal and annual rainfall variations as well as urban encroachment and resource exploitation. NDVI analysis demonstrates a positive trend in vegetation health, suggesting resilience in certain areas, whereas MNDWI data reflect substantial shifts in water coverage, indicating potential hydrological stress in low-rainfall years. LULC results reveal an expansion in built-up areas and a reduction in natural vegetation, emphasizing the ongoing pressures on wetland resources due to urbanization. By integrating machine learning techniques with long-term satellite data, this study establishes key indicators for wetland health and provides trend analysis that informs conservation and adaptive management strategies for the Asan Conservation Reserve.