Assessment of forest fragmentation in a traditional shifting agricultural landscape in Senapati District of Manipur, Northeast India

Ahanthem Rebika Devi (), C. Sudhakar Reddy () and Tuisem Shimrah ()
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Ahanthem Rebika Devi: GGSIP University
C. Sudhakar Reddy: Indian Space Research Organisation
Tuisem Shimrah: GGSIP University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2021, vol. 23, issue 7, No 33, 10344-10356

Abstract: Abstract Forest fragmentation is associated with the deterioration of the ecosystem’s integrity, has negative impacts on biodiversity, degradation of forest, and spatial pattern of the landscape, and become a global conservative issue. Due to advancements in technology such as remote sensing (RS) and geographic information system (GIS), there is a wider possibility of studying, monitoring, and reporting of essential biodiversity variances. The aim of the present study is to assess and quantify the extend and pattern of forest fragmentation over the time series of 2013 and 2017 in the traditional landscape area of Senapati district of Manipur, Northeast India using multi-temporal Landsat data. The Landscape Fragmentation tool has been used to categorize the forest area into four categories: patch, edge, perforated, and core forest by assigning an edge width of 100 m. The result of the study shows that area covered by patch forest has increased by 5.54%, whereas the total core forest area has decreased by 318.5 km2. The change matrix analysis showed the conversion of one category of the forest to another with the overall maximum changes is associated with degradation in the forest area. With the identification of such change using RS technology and GIS data, we could suggest immediate measures for reclamation and restoration of degraded forest areas to regain its original ecosystem integrity in terms of carbon storage, soil retention, water conservation, biodiversity conservation, and climate change mitigation.

Keywords: Traditional landscape; Remote sensing; GIS; Forest fragmentation (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10668-020-01059-4

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