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: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/90869/1/AliyuDalhatuSani2020_MultiSensorMappingandEstimationofSeagrass.pdf http://eprints.utm.my/id/eprint/90869/ |
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| Summary: | 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. |
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