Disentangle the short-term forest degradation over most fire-affected parts of Western Himalaya, India
Disentangle the short-term forest degradation over most fire-affected parts of Western Himalaya, India
The tropical forest contributes around 5% to 15% of atmospheric carbon emissions, which are mostly anthropogenic. But there are large uncertainties in the quantification of these emissions from its sources. The remote-sensing data offers a practical opportunity to monitor and assess different forest disturbances. Western Himalayan forest is often affected by fire events, mostly during (pre-monsoon) dry and warm periods. In this study, we present a way to monitor the forest degradation condition using spectral mixture analysis (SMA) and surface reflectance of Landsat-8 data from 2014 to 2019. The Normalized Degradation Fraction Index (NDFI) has been performed by using spectral end member fractions of green vegetation (GV), non-photosynthetic vegetation (NPV), soil, and shade in the Google Earth Engine (GEE) cloud platform. The NDFI shows considerable spatial correspondences with clusters of fire spots during the pre-monsoon period. Around 3% to 9% of the forest burned area transformed to partially to highly degraded forest. The overall trend of degradation fraction (NDFI) over total forest cover shows a significant negative trend over a considerable area. Thus, Landsat-8-based SMA and NDFI demonstrate a potential way to identify forest degradation mediated by forest fires, although remote sensing-based approaches are limited in their capacity to accurately detect forest disturbances. Furthermore, field-based studies are needed to monitor the potentialities of the NDFI approach in forest degradation identification.
87-102
Bar, Somnath
1e199d14-4020-46ef-9dfa-733fe5fa6082
Parida, Bikash Ranjan
21c6f8e7-5d6c-4d46-86e3-4e7160b4d1b5
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
2 December 2022
Bar, Somnath
1e199d14-4020-46ef-9dfa-733fe5fa6082
Parida, Bikash Ranjan
21c6f8e7-5d6c-4d46-86e3-4e7160b4d1b5
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
Bar, Somnath, Parida, Bikash Ranjan and Dash, Jadunandan
(2022)
Disentangle the short-term forest degradation over most fire-affected parts of Western Himalaya, India.
In,
Parida, Bikash Ranjan, Pandey, Arvind Chandra, Behera, Mukunda Dev and Kumar, Navneet
(eds.)
Handbook of Himalayan Ecosystems and Sustainability: Spatio-Temporal Monitoring of Forests and Climate.
1st ed.
CRC Press, .
(doi:10.1201/9781003268383-7).
Record type:
Book Section
Abstract
The tropical forest contributes around 5% to 15% of atmospheric carbon emissions, which are mostly anthropogenic. But there are large uncertainties in the quantification of these emissions from its sources. The remote-sensing data offers a practical opportunity to monitor and assess different forest disturbances. Western Himalayan forest is often affected by fire events, mostly during (pre-monsoon) dry and warm periods. In this study, we present a way to monitor the forest degradation condition using spectral mixture analysis (SMA) and surface reflectance of Landsat-8 data from 2014 to 2019. The Normalized Degradation Fraction Index (NDFI) has been performed by using spectral end member fractions of green vegetation (GV), non-photosynthetic vegetation (NPV), soil, and shade in the Google Earth Engine (GEE) cloud platform. The NDFI shows considerable spatial correspondences with clusters of fire spots during the pre-monsoon period. Around 3% to 9% of the forest burned area transformed to partially to highly degraded forest. The overall trend of degradation fraction (NDFI) over total forest cover shows a significant negative trend over a considerable area. Thus, Landsat-8-based SMA and NDFI demonstrate a potential way to identify forest degradation mediated by forest fires, although remote sensing-based approaches are limited in their capacity to accurately detect forest disturbances. Furthermore, field-based studies are needed to monitor the potentialities of the NDFI approach in forest degradation identification.
This record has no associated files available for download.
More information
Published date: 2 December 2022
Identifiers
Local EPrints ID: 477958
URI: http://eprints.soton.ac.uk/id/eprint/477958
PURE UUID: 5a4607b6-5e2b-4776-a6f1-786d69b95792
Catalogue record
Date deposited: 16 Jun 2023 17:01
Last modified: 06 Jun 2024 02:18
Export record
Altmetrics
Contributors
Author:
Somnath Bar
Author:
Bikash Ranjan Parida
Editor:
Bikash Ranjan Parida
Editor:
Arvind Chandra Pandey
Editor:
Mukunda Dev Behera
Editor:
Navneet Kumar
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics