Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI
Forest aboveground biomass (AGB) is integral to the global carbon cycle and climate change study. Local and regional AGB mapping is crucial for understanding global carbon stock dynamics. NASA’s global ecosystem dynamics investigation (GEDI) and combination of multi-source optical and synthetic aper...
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MDPI AG
2024-01-01
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author | Chu Wang Wangfei Zhang Yongjie Ji Armando Marino Chunmei Li Lu Wang Han Zhao Mengjin Wang |
author_facet | Chu Wang Wangfei Zhang Yongjie Ji Armando Marino Chunmei Li Lu Wang Han Zhao Mengjin Wang |
author_sort | Chu Wang |
collection | DOAJ |
description | Forest aboveground biomass (AGB) is integral to the global carbon cycle and climate change study. Local and regional AGB mapping is crucial for understanding global carbon stock dynamics. NASA’s global ecosystem dynamics investigation (GEDI) and combination of multi-source optical and synthetic aperture radar (SAR) datasets have great potential for local and regional AGB estimation and mapping. In this study, GEDI L4A AGB data and ground sample plots worked as true AGB values to explore their difference for estimating forest AGB using Sentinel-1 (S1), Sentinel-2 (S2), and ALOS PALSAR-2 (PALSAR) data, individually and in their different combinations. The effects of forest types and different true AGB values for validation were investigated in this study, as well. The combination of S1 and S2 performed best in forest AGB estimation with <i>R</i><sup>2</sup> ranging from 0.79 to 0.84 and <i>RMSE</i> ranging from 7.97 to 29.42 Mg/ha, with the ground sample plots used as ground truth data. While for GEDI L4A AGB product working as reference, <i>R</i><sup>2</sup> values range from 0.36 to 0.47 and <i>RMSE</i> values range from 31.41 to 37.50 Mg/ha. The difference between using GEDI L4A and ground sample plot as reference shows obvious dependence on forest types. In summary, optical dataset and its combination with SAR performed better in forest AGB estimation when the average AGB is less than 150 Mg/ha. The AGB predictions from GEDI L4A AGB product used as reference underperformed across the different forest types and study sites. However, GEDI can work as ground truth data source for forest AGB estimation in a certain level of estimation accuracy. |
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spelling | doaj.art-59106eb3a8b6439f8980d9963f5962022024-01-26T16:35:02ZengMDPI AGForests1999-49072024-01-0115121510.3390/f15010215Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDIChu Wang0Wangfei Zhang1Yongjie Ji2Armando Marino3Chunmei Li4Lu Wang5Han Zhao6Mengjin Wang7College of Forestry, Southwest Forestry University, Kunming 650224, ChinaCollege of Forestry, Southwest Forestry University, Kunming 650224, ChinaSchool of Geography and Ecotourism, Southwest Forestry University, Kunming 650224, ChinaBiological and Environmental Sciences, The University of Stirling, Stirling FK9 4LA, UKChina Spacesat Co., Ltd., Beijing 100081, ChinaSchool of Geography and Ecotourism, Southwest Forestry University, Kunming 650224, ChinaCollege of Forestry, Southwest Forestry University, Kunming 650224, ChinaCollege of Forestry, Southwest Forestry University, Kunming 650224, ChinaForest aboveground biomass (AGB) is integral to the global carbon cycle and climate change study. Local and regional AGB mapping is crucial for understanding global carbon stock dynamics. NASA’s global ecosystem dynamics investigation (GEDI) and combination of multi-source optical and synthetic aperture radar (SAR) datasets have great potential for local and regional AGB estimation and mapping. In this study, GEDI L4A AGB data and ground sample plots worked as true AGB values to explore their difference for estimating forest AGB using Sentinel-1 (S1), Sentinel-2 (S2), and ALOS PALSAR-2 (PALSAR) data, individually and in their different combinations. The effects of forest types and different true AGB values for validation were investigated in this study, as well. The combination of S1 and S2 performed best in forest AGB estimation with <i>R</i><sup>2</sup> ranging from 0.79 to 0.84 and <i>RMSE</i> ranging from 7.97 to 29.42 Mg/ha, with the ground sample plots used as ground truth data. While for GEDI L4A AGB product working as reference, <i>R</i><sup>2</sup> values range from 0.36 to 0.47 and <i>RMSE</i> values range from 31.41 to 37.50 Mg/ha. The difference between using GEDI L4A and ground sample plot as reference shows obvious dependence on forest types. In summary, optical dataset and its combination with SAR performed better in forest AGB estimation when the average AGB is less than 150 Mg/ha. The AGB predictions from GEDI L4A AGB product used as reference underperformed across the different forest types and study sites. However, GEDI can work as ground truth data source for forest AGB estimation in a certain level of estimation accuracy.https://www.mdpi.com/1999-4907/15/1/215GEDI L4A AGB productoptical datasetsSAR datasetsground sample plotsAGB estimationRF |
spellingShingle | Chu Wang Wangfei Zhang Yongjie Ji Armando Marino Chunmei Li Lu Wang Han Zhao Mengjin Wang Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI Forests GEDI L4A AGB product optical datasets SAR datasets ground sample plots AGB estimation RF |
title | Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI |
title_full | Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI |
title_fullStr | Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI |
title_full_unstemmed | Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI |
title_short | Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI |
title_sort | estimation of aboveground biomass for different forest types using data from sentinel 1 sentinel 2 alos palsar 2 and gedi |
topic | GEDI L4A AGB product optical datasets SAR datasets ground sample plots AGB estimation RF |
url | https://www.mdpi.com/1999-4907/15/1/215 |
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