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<p>In tropical regions, forested ecosystems face increasing threats from deforestation, illegal wildlife trade, climate change, invasive species, disease outbreaks, and land use changes. This study evaluates land use and land cover (LULC) changes from 1998 to 2020 in and around Mehao Wildlife Sanctuary (WLS), Arunachal Pradesh, with a focus on human-induced drivers such as habitat fragmentation, urbanization, and agricultural expansion. LULC maps were generated using Landsat-5 and Sentinel-2&#xa0;A imagery through supervised classification with the Maximum Likelihood Classifier (MLC). Eight major LULC classes were identified, including mixed forest, riverine forest, grassland, riverbed, barren land, built-up, and agricultural land. Change detection analysis and landscape metrics revealed a significant decline in mixed and riverine forests, alongside increased aggregation of built-up and agricultural areas. Other land cover classes showed fragmentation trends, reflecting structural changes in the landscape. These patterns indicate the influence of human activities on landscape dynamics and suggest the relevance of incorporating local knowledge into conservation planning.The Idu Mishmi community, with deep traditional knowledge and cultural taboos linked to forest and wildlife, plays a key role in supporting local conservation. The change detection outputs inform patterns and impacts of LULC change and support integrated conservation and management strategies for the Mehao region.</p>

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Spatio-Temporal Analysis of Land Use and Land Cover Changes in the Mishmi Hills, Eastern Himalaya

  • 期刊论文

  • 发表日期：

    2026年5月20日

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  • Arif Ahmad,
  • Govindan Veeraswami Gopi

摘要

In tropical regions, forested ecosystems face increasing threats from deforestation, illegal wildlife trade, climate change, invasive species, disease outbreaks, and land use changes. This study evaluates land use and land cover (LULC) changes from 1998 to 2020 in and around Mehao Wildlife Sanctuary (WLS), Arunachal Pradesh, with a focus on human-induced drivers such as habitat fragmentation, urbanization, and agricultural expansion. LULC maps were generated using Landsat-5 and Sentinel-2 A imagery through supervised classification with the Maximum Likelihood Classifier (MLC). Eight major LULC classes were identified, including mixed forest, riverine forest, grassland, riverbed, barren land, built-up, and agricultural land. Change detection analysis and landscape metrics revealed a significant decline in mixed and riverine forests, alongside increased aggregation of built-up and agricultural areas. Other land cover classes showed fragmentation trends, reflecting structural changes in the landscape. These patterns indicate the influence of human activities on landscape dynamics and suggest the relevance of incorporating local knowledge into conservation planning.The Idu Mishmi community, with deep traditional knowledge and cultural taboos linked to forest and wildlife, plays a key role in supporting local conservation. The change detection outputs inform patterns and impacts of LULC change and support integrated conservation and management strategies for the Mehao region.