Oliver Cartus, Maurizio Santoro, Carlos Jimenez, Catherine Prigent, Mike Schwank, Urs Wegmüller
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A physically-based model was adapted to relate brightness temperatures to the percent canopy cover and height available from space-borne optical and LiDAR missions and, via modelled relationships between canopy cover, height, and AGB, to AGB. An initial set of 36 global AGB maps was produced from 10-days composites of a polarimetric index calculated from H and V polarization SMOS and SMAP brightness temperatures acquired in 2016. When compared to an ESA Climate Change Initiative Biomass AGB map, the AGB estimates produced from SMOS and SMAP presented a reasonable agreement with low systematic biases and explained, dependent on the type of forest, between 30 % and 80 % of the AGB variability in the reference map. A comparison with AGB reference information derived from plot-level inventory data for a limited number of sites across the major forest biomes indicated the merit of the suggested retrieval approach but also revealed a need for improving the retrieval algorithm locally.","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"7 1","pages":""},"PeriodicalIF":11.1000,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A parametric approach for global estimation of forest above-ground biomass with SMOS and SMAP L-band radiometer data\",\"authors\":\"Oliver Cartus, Maurizio Santoro, Carlos Jimenez, Catherine Prigent, Mike Schwank, Urs Wegmüller\",\"doi\":\"10.1016/j.rse.2025.114601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"L-band radiometer data collected by the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions have shown potential for mapping the spatial distribution and temporal changes of the above-ground biomass (AGB) of forests. Most studies focussed on the relationships observed between AGB and estimates of the vegetation optical depth (VOD) derived from L-band radiometer data. We here present an approach for retrieving AGB from SMOS and SMAP brightness temperatures which builds upon existing AGB retrieval frameworks developed for active microwave data. A physically-based model was adapted to relate brightness temperatures to the percent canopy cover and height available from space-borne optical and LiDAR missions and, via modelled relationships between canopy cover, height, and AGB, to AGB. An initial set of 36 global AGB maps was produced from 10-days composites of a polarimetric index calculated from H and V polarization SMOS and SMAP brightness temperatures acquired in 2016. When compared to an ESA Climate Change Initiative Biomass AGB map, the AGB estimates produced from SMOS and SMAP presented a reasonable agreement with low systematic biases and explained, dependent on the type of forest, between 30 % and 80 % of the AGB variability in the reference map. A comparison with AGB reference information derived from plot-level inventory data for a limited number of sites across the major forest biomes indicated the merit of the suggested retrieval approach but also revealed a need for improving the retrieval algorithm locally.\",\"PeriodicalId\":417,\"journal\":{\"name\":\"Remote Sensing of Environment\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2025-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing of Environment\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1016/j.rse.2025.114601\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing of Environment","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1016/j.rse.2025.114601","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
A parametric approach for global estimation of forest above-ground biomass with SMOS and SMAP L-band radiometer data
L-band radiometer data collected by the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions have shown potential for mapping the spatial distribution and temporal changes of the above-ground biomass (AGB) of forests. Most studies focussed on the relationships observed between AGB and estimates of the vegetation optical depth (VOD) derived from L-band radiometer data. We here present an approach for retrieving AGB from SMOS and SMAP brightness temperatures which builds upon existing AGB retrieval frameworks developed for active microwave data. A physically-based model was adapted to relate brightness temperatures to the percent canopy cover and height available from space-borne optical and LiDAR missions and, via modelled relationships between canopy cover, height, and AGB, to AGB. An initial set of 36 global AGB maps was produced from 10-days composites of a polarimetric index calculated from H and V polarization SMOS and SMAP brightness temperatures acquired in 2016. When compared to an ESA Climate Change Initiative Biomass AGB map, the AGB estimates produced from SMOS and SMAP presented a reasonable agreement with low systematic biases and explained, dependent on the type of forest, between 30 % and 80 % of the AGB variability in the reference map. A comparison with AGB reference information derived from plot-level inventory data for a limited number of sites across the major forest biomes indicated the merit of the suggested retrieval approach but also revealed a need for improving the retrieval algorithm locally.
期刊介绍:
Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing.
The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques.
RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.