Synergetic of PALSAR-2 and Sentinel-1A SAR Polarimetry for Retrieving Aboveground Biomass in Dipterocarp Forest of Malaysia
Space borne synthetic aperture radar (SAR) data have become one of the primary sources for aboveground biomass (AGB) estimation of forests. However, studies have indicated that limitations occur when a single sensor system is employed, especially in tropical forests. Hence, there is potential for im...
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doaj-d2bf9b6e408a48c8889a9135a7d510282020-11-24T21:25:58ZengMDPI AGApplied Sciences2076-34172017-06-017767510.3390/app7070675app7070675Synergetic of PALSAR-2 and Sentinel-1A SAR Polarimetry for Retrieving Aboveground Biomass in Dipterocarp Forest of MalaysiaHamdan Omar0Muhamad Afizzul Misman1Abd Rahman Kassim2Geoinformation Programme, Division of Forestry and Environment, Forest Research Institute Malaysia, Selangor 52109, MalaysiaGeoinformation Programme, Division of Forestry and Environment, Forest Research Institute Malaysia, Selangor 52109, MalaysiaGeoinformation Programme, Division of Forestry and Environment, Forest Research Institute Malaysia, Selangor 52109, MalaysiaSpace borne synthetic aperture radar (SAR) data have become one of the primary sources for aboveground biomass (AGB) estimation of forests. However, studies have indicated that limitations occur when a single sensor system is employed, especially in tropical forests. Hence, there is potential for improving estimates if two or more different sensor systems are used. Studies on integrating multiple sensor systems for estimation of AGB over Malaysia’s tropical forests are scarce. This study investigated the use of PALSAR-2 L-band and Sentinel-1A C-band SAR polarizations to estimates the AGB over 5.25 million ha of the lowland, hill, and upper hill forests in Peninsular Malaysia. Polarized images, i.e., HH–HV from PALSAR-2 and VV–VH from Sentinel-1A have been utilized to produce several variables for predictions of the AGB. Simple linear and multiple linear regression analysis was performed to identify the best predictor. The study concluded that although limitations exist in the estimates, the combination of all polarizations from both PALSAR-2 and Sentiel-1A SAR data able to increase the accuracy and reduced the root means square error (RMSE) up to 14 Mg ha−1 compared to the estimation resulted from single polarization. A spatially distributed map of AGB reported the total AGB within the study area was about 1.82 trillion Mg of the year 2016.http://www.mdpi.com/2076-3417/7/7/675aboveground biomasstropical forestmicrowave sensor system |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hamdan Omar Muhamad Afizzul Misman Abd Rahman Kassim |
spellingShingle |
Hamdan Omar Muhamad Afizzul Misman Abd Rahman Kassim Synergetic of PALSAR-2 and Sentinel-1A SAR Polarimetry for Retrieving Aboveground Biomass in Dipterocarp Forest of Malaysia Applied Sciences aboveground biomass tropical forest microwave sensor system |
author_facet |
Hamdan Omar Muhamad Afizzul Misman Abd Rahman Kassim |
author_sort |
Hamdan Omar |
title |
Synergetic of PALSAR-2 and Sentinel-1A SAR Polarimetry for Retrieving Aboveground Biomass in Dipterocarp Forest of Malaysia |
title_short |
Synergetic of PALSAR-2 and Sentinel-1A SAR Polarimetry for Retrieving Aboveground Biomass in Dipterocarp Forest of Malaysia |
title_full |
Synergetic of PALSAR-2 and Sentinel-1A SAR Polarimetry for Retrieving Aboveground Biomass in Dipterocarp Forest of Malaysia |
title_fullStr |
Synergetic of PALSAR-2 and Sentinel-1A SAR Polarimetry for Retrieving Aboveground Biomass in Dipterocarp Forest of Malaysia |
title_full_unstemmed |
Synergetic of PALSAR-2 and Sentinel-1A SAR Polarimetry for Retrieving Aboveground Biomass in Dipterocarp Forest of Malaysia |
title_sort |
synergetic of palsar-2 and sentinel-1a sar polarimetry for retrieving aboveground biomass in dipterocarp forest of malaysia |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2017-06-01 |
description |
Space borne synthetic aperture radar (SAR) data have become one of the primary sources for aboveground biomass (AGB) estimation of forests. However, studies have indicated that limitations occur when a single sensor system is employed, especially in tropical forests. Hence, there is potential for improving estimates if two or more different sensor systems are used. Studies on integrating multiple sensor systems for estimation of AGB over Malaysia’s tropical forests are scarce. This study investigated the use of PALSAR-2 L-band and Sentinel-1A C-band SAR polarizations to estimates the AGB over 5.25 million ha of the lowland, hill, and upper hill forests in Peninsular Malaysia. Polarized images, i.e., HH–HV from PALSAR-2 and VV–VH from Sentinel-1A have been utilized to produce several variables for predictions of the AGB. Simple linear and multiple linear regression analysis was performed to identify the best predictor. The study concluded that although limitations exist in the estimates, the combination of all polarizations from both PALSAR-2 and Sentiel-1A SAR data able to increase the accuracy and reduced the root means square error (RMSE) up to 14 Mg ha−1 compared to the estimation resulted from single polarization. A spatially distributed map of AGB reported the total AGB within the study area was about 1.82 trillion Mg of the year 2016. |
topic |
aboveground biomass tropical forest microwave sensor system |
url |
http://www.mdpi.com/2076-3417/7/7/675 |
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