Multi-sensor mapping and estimation of seagrass aboveground blue carbon stocks using Landsat OLI and ETM+ along merambong coastal water

Multi-sensor mapping and estimation of aboveground seagrass blue carbon stocks are essential to address the extreme deterioration of seagrass meadows. Resulting from climatic fluctuation and related anthropogenic activities throughout the globe. However, the critical role played by seagrass blue car...

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Main Authors: Sani, Aliyu Dalhatu, Hashim, Mazlan
Format: Conference or Workshop Item
Language:English
Published: 2020
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Online Access:http://eprints.utm.my/id/eprint/90869/1/AliyuDalhatuSani2020_MultiSensorMappingandEstimationofSeagrass.pdf
http://eprints.utm.my/id/eprint/90869/
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spelling my.utm.908692021-05-31T13:40:05Z http://eprints.utm.my/id/eprint/90869/ Multi-sensor mapping and estimation of seagrass aboveground blue carbon stocks using Landsat OLI and ETM+ along merambong coastal water Sani, Aliyu Dalhatu Hashim, Mazlan GB Physical geography TH434-437 Quantity surveying Multi-sensor mapping and estimation of aboveground seagrass blue carbon stocks are essential to address the extreme deterioration of seagrass meadows. Resulting from climatic fluctuation and related anthropogenic activities throughout the globe. However, the critical role played by seagrass blue carbon pool in the ocean carbon cycle makes it crucial in fast-tracking sustainable development goal (SDG) 14th. Therefore, this study used multi-spectral sensors of Landsat OLI and ETM+ to derive seagrass total aboveground carbon (STAGC) in seagrass meadows of Merambong coastal water along Peninsula Malaysia (PM). A logistic model was employed to establish a relationship between the bottom reflectance index (BRI) with in-situ of seagrass total aboveground biomass (STAGB). The revelation of this developed model proved an agreeable correlation (R2 0.96, p==0.001 and 0.60% STAGC per hectare (MtC/ha1)). Equally, accuracy assessment revealed an excellent RMSE +- 0.62 result. Hence, this study shall support the realisation of SDG 14th targets 14.2 and 14.5 established by United Nations (UN), to prompt the success of the 2020 agenda. 2020-06 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/90869/1/AliyuDalhatuSani2020_MultiSensorMappingandEstimationofSeagrass.pdf Sani, Aliyu Dalhatu and Hashim, Mazlan (2020) Multi-sensor mapping and estimation of seagrass aboveground blue carbon stocks using Landsat OLI and ETM+ along merambong coastal water. In: 40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019, 14 October 2019 - 18 October 2019, Daejeon Convention Center (DCC) Daejeon, South Korea.
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 GB Physical geography
TH434-437 Quantity surveying
spellingShingle GB Physical geography
TH434-437 Quantity surveying
Sani, Aliyu Dalhatu
Hashim, Mazlan
Multi-sensor mapping and estimation of seagrass aboveground blue carbon stocks using Landsat OLI and ETM+ along merambong coastal water
description Multi-sensor mapping and estimation of aboveground seagrass blue carbon stocks are essential to address the extreme deterioration of seagrass meadows. Resulting from climatic fluctuation and related anthropogenic activities throughout the globe. However, the critical role played by seagrass blue carbon pool in the ocean carbon cycle makes it crucial in fast-tracking sustainable development goal (SDG) 14th. Therefore, this study used multi-spectral sensors of Landsat OLI and ETM+ to derive seagrass total aboveground carbon (STAGC) in seagrass meadows of Merambong coastal water along Peninsula Malaysia (PM). A logistic model was employed to establish a relationship between the bottom reflectance index (BRI) with in-situ of seagrass total aboveground biomass (STAGB). The revelation of this developed model proved an agreeable correlation (R2 0.96, p==0.001 and 0.60% STAGC per hectare (MtC/ha1)). Equally, accuracy assessment revealed an excellent RMSE +- 0.62 result. Hence, this study shall support the realisation of SDG 14th targets 14.2 and 14.5 established by United Nations (UN), to prompt the success of the 2020 agenda.
format Conference or Workshop Item
author Sani, Aliyu Dalhatu
Hashim, Mazlan
author_facet Sani, Aliyu Dalhatu
Hashim, Mazlan
author_sort Sani, Aliyu Dalhatu
title Multi-sensor mapping and estimation of seagrass aboveground blue carbon stocks using Landsat OLI and ETM+ along merambong coastal water
title_short Multi-sensor mapping and estimation of seagrass aboveground blue carbon stocks using Landsat OLI and ETM+ along merambong coastal water
title_full Multi-sensor mapping and estimation of seagrass aboveground blue carbon stocks using Landsat OLI and ETM+ along merambong coastal water
title_fullStr Multi-sensor mapping and estimation of seagrass aboveground blue carbon stocks using Landsat OLI and ETM+ along merambong coastal water
title_full_unstemmed Multi-sensor mapping and estimation of seagrass aboveground blue carbon stocks using Landsat OLI and ETM+ along merambong coastal water
title_sort multi-sensor mapping and estimation of seagrass aboveground blue carbon stocks using landsat oli and etm+ along merambong coastal water
publishDate 2020
url http://eprints.utm.my/id/eprint/90869/1/AliyuDalhatuSani2020_MultiSensorMappingandEstimationofSeagrass.pdf
http://eprints.utm.my/id/eprint/90869/
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score 13.160551