Pasha, SV and Kumari, K and Kripa, MK and Dadhwal, Vinay Kumar
(2025)
Vegetation indices and the changing landscape: a spatio-temporal study of vegetation composition and health.
In:
Forests for Inclusive and Sustainable Economic Growth edited by Purabi Saikia et.al.
Elsevier Inc, pp. 143-160.
ISBN 978-0-443-31406-3
Full text not available from this repository.
Abstract: |
Vegetation indices (VIs), derived from satellite remote sensing (RS) data, are crucial in assessing vegetation dynamics and health. This study applies various VIs to determine forest composition and health across contrasting landscapes: natural vegetation (mangroves and shola), managed ecosystems (rubber and tea), and crops (sugar cane and wheat). We track monthly vegetation fraction from 2019 to 2023, using both optical and microwave frequencies. Multisource and multitemporal satellite RS data from Sentinel-1 and Sentinel-2 are processed via the cloud computing platform Google Earth Engine and R-statistical software. By evaluating these indices across six diverse landscapes, we gain insights into spatio-temporal changes in vegetation health. Understanding the limitations and capabilities of multiple VIs is essential for effective remote sensing in vegetation research. |
Item Type: |
Book Chapter
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Subjects: |
School of Natural and Engineering Sciences > Environment |
Divisions: |
Schools > Natural Sciences and Engineering |
Date Deposited: |
05 Jun 2025 05:46 |
Last Modified: |
05 Jun 2025 05:46 |
Official URL: |
https://www.sciencedirect.com/science/article/abs/... |
Related URLs: |
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Funders: |
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Projects: |
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DOI: |
https://doi.org/10.1016/B978-0-443-31406-3.00011-4 |
URI: |
http://eprints.nias.res.in/id/eprint/2933 |
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