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Mapping seasonal variations of grazing land above-ground biomass with sentinel 2A satellite data

Seasonal variations have brought about significant changes in vegetation cover and spatial distribution in the past decade. Globally, grazing lands are experiencing a significant warming and drying process more especially the grazing lands in the Savannah and Sahel regions. This paper reports the st...

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Main Authors: Zumo, Isa Muhammad, Hashim, Mazlan
Format: Conference or Workshop Item
Language:English
Published: 2020
Subjects:
NA Architecture
T Technology (General)
Online Access:http://eprints.utm.my/id/eprint/90726/1/IsaMuhammadZumo2020_MappingSeasonalVariationsofGrazingLand.pdf
http://eprints.utm.my/id/eprint/90726/
http://dx.doi.org/10.1088/1755-1315/540/1/012061
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spelling my.utm.907262021-04-30T14:57:09Z http://eprints.utm.my/id/eprint/90726/ Mapping seasonal variations of grazing land above-ground biomass with sentinel 2A satellite data Zumo, Isa Muhammad Hashim, Mazlan NA Architecture T Technology (General) Seasonal variations have brought about significant changes in vegetation cover and spatial distribution in the past decade. Globally, grazing lands are experiencing a significant warming and drying process more especially the grazing lands in the Savannah and Sahel regions. This paper reports the study undertaken for mapping changes on the grass above ground biomass (GAB) due to these seasonal changes using Sentinel 2A Multispectral Instrument (MSI) data. Emphasising on the GAB, the main objective of this study is to map and model monthly GAB variations to their corresponding meteorological data. A set of selected widely used vegetation indices were applied to satellite data, and later were further regressed against corresponding in-situ GAB samples and weather data, hence, producing a predictor of GAB from satellite data. Sentinel 2A MSI data were acquired monthly from January to December 2018. Combined with precipitation and temperature data, the GAB variations on monthly scales were analysed. The results indicated that GAB determined and its seasonal variations shown good agreement (r = 0.8, p < 0.001) with corresponding in-situ verifications. Temperature was found inversely proportionally to GAB for the whole grazing calendar. Therefore, it was concluded that mapping GAB seasonal variations is achievable with Sentinel2 MSI, vast potential for input to grazing land management. 2020-08-04 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/90726/1/IsaMuhammadZumo2020_MappingSeasonalVariationsofGrazingLand.pdf Zumo, Isa Muhammad and Hashim, Mazlan (2020) Mapping seasonal variations of grazing land above-ground biomass with sentinel 2A satellite data. In: 10th IGRSM International Conference and Exhibition on Geospatial and Remote, IGRSM 2020, 20 October 2020 - 21 October 2020, Kuala Lumpur, Virtual, Malaysia. http://dx.doi.org/10.1088/1755-1315/540/1/012061
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic NA Architecture
T Technology (General)
spellingShingle NA Architecture
T Technology (General)
Zumo, Isa Muhammad
Hashim, Mazlan
Mapping seasonal variations of grazing land above-ground biomass with sentinel 2A satellite data
description Seasonal variations have brought about significant changes in vegetation cover and spatial distribution in the past decade. Globally, grazing lands are experiencing a significant warming and drying process more especially the grazing lands in the Savannah and Sahel regions. This paper reports the study undertaken for mapping changes on the grass above ground biomass (GAB) due to these seasonal changes using Sentinel 2A Multispectral Instrument (MSI) data. Emphasising on the GAB, the main objective of this study is to map and model monthly GAB variations to their corresponding meteorological data. A set of selected widely used vegetation indices were applied to satellite data, and later were further regressed against corresponding in-situ GAB samples and weather data, hence, producing a predictor of GAB from satellite data. Sentinel 2A MSI data were acquired monthly from January to December 2018. Combined with precipitation and temperature data, the GAB variations on monthly scales were analysed. The results indicated that GAB determined and its seasonal variations shown good agreement (r = 0.8, p < 0.001) with corresponding in-situ verifications. Temperature was found inversely proportionally to GAB for the whole grazing calendar. Therefore, it was concluded that mapping GAB seasonal variations is achievable with Sentinel2 MSI, vast potential for input to grazing land management.
format Conference or Workshop Item
author Zumo, Isa Muhammad
Hashim, Mazlan
author_facet Zumo, Isa Muhammad
Hashim, Mazlan
author_sort Zumo, Isa Muhammad
title Mapping seasonal variations of grazing land above-ground biomass with sentinel 2A satellite data
title_short Mapping seasonal variations of grazing land above-ground biomass with sentinel 2A satellite data
title_full Mapping seasonal variations of grazing land above-ground biomass with sentinel 2A satellite data
title_fullStr Mapping seasonal variations of grazing land above-ground biomass with sentinel 2A satellite data
title_full_unstemmed Mapping seasonal variations of grazing land above-ground biomass with sentinel 2A satellite data
title_sort mapping seasonal variations of grazing land above-ground biomass with sentinel 2a satellite data
publishDate 2020
url http://eprints.utm.my/id/eprint/90726/1/IsaMuhammadZumo2020_MappingSeasonalVariationsofGrazingLand.pdf
http://eprints.utm.my/id/eprint/90726/
http://dx.doi.org/10.1088/1755-1315/540/1/012061
_version_ 1698696976697131008
score 13.211869

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