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Landscape ecological modeling to identify ecologically significant regions in Tumkur district, Karnataka

Ramachandra, TV and Setturu, B and Bhatta, V (2022) Landscape ecological modeling to identify ecologically significant regions in Tumkur district, Karnataka. In: Physical Sciences Reviews .

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Official URL: https://doi.org/10.1515/psr-2022-0154


Temporal land use and land cover (LULC) information of a landscape provide an overview of the drivers of change, and impacts on the socio-ecological system. This necessitates organizing diverse data of a landscape, which provides insights into sustainable management. Spatial heterogeneity with landscape dynamics influences biotic and abiotic processes. The knowledge of LULC dynamics aids in assessing the feedback between socio-ecological systems across the urban and rural environments. Visualizing likely landscape changes through modeling help in the decision-making for sustainable landscape management. The current chapter accounts for changes in LULC patterns of the agrarian district Tumkur in Karnataka State, considering temporal remote sensing data of three decades, using geospatial techniques and modeling. Land use (LU) analyses indicate an increase in horticulture area from 0.94 (1989) to 1.02% (2019) due to an increase in commercial cropping. An upsurge of built-up cover from 0.02 to 2.11% (1989-2019) with the enhanced socio-economic activities with the industrialization and infrastructure development across the Tumkur to Bangalore highway. Spatial patterns of landscape dynamics assessed through spatial matrices highlight of increase in urbanization with land conversion from agriculture and forest cover in the outskirts of the Tumkur city center. Ecologically significant regions (ESR) were identified at disaggregated levels through aggregate metrics incorporating bio-geo-climatic, social, hydrological, and ecological aspects. The study region is divided into 9 × 9 km grids for computing metrics at disaggregated levels. ESR is delineated based on the composite metric of all variables, depicts 17 grids (11%) under ESR 1, indicating the highest sensitivity, 29% area (46 grids) as ESR 2 (higher sensitivity), 45% (70 grids) as ESR 3 (high sensitivity), and the rest is 15% (24 grids) in ESR 4 (moderate sensitivity). The outcome of the current research would provide critical management approaches required for managing natural resources and will be valuable for policy and planning purposes in pursuing Sustainable Development Goals (SDGs) at the regional scale.

Item Type: Journal Article
Publication: Physical Sciences Reviews
Publisher: De Gruyter Open Ltd
Additional Information: The copyright for this article belongs to De Gruyter Open Ltd.
Keywords: forest fragmentation; land use land cover (LULC); prediction; spatial matrices ESR
Department/Centre: Division of Interdisciplinary Sciences > Center for Infrastructure, Sustainable Transportation and Urban Planning (CiSTUP)
Date Deposited: 05 Jan 2023 07:04
Last Modified: 05 Jan 2023 07:04
URI: https://eprints.iisc.ac.in/id/eprint/78747

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