A parametric approach for global estimation of forest above-ground biomass with SMOS and SMAP L-band radiometer data

IF 11.1 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES Remote Sensing of Environment Pub Date : 2025-01-11 DOI:10.1016/j.rse.2025.114601
Oliver Cartus, Maurizio Santoro, Carlos Jimenez, Catherine Prigent, Mike Schwank, Urs Wegmüller
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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.
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基于SMOS和SMAP l波段辐射计数据估算全球森林地上生物量的参数化方法
土壤水分-海洋盐度(SMOS)和土壤水分主动-被动(SMAP)任务收集的l波段辐射计数据显示出绘制森林地上生物量(AGB)空间分布和时间变化的潜力。大多数研究集中于观测到的AGB与l波段辐射计数据估算的植被光深(VOD)之间的关系。本文提出了一种从SMOS和SMAP亮度温度中检索AGB的方法,该方法建立在为有源微波数据开发的现有AGB检索框架的基础上。采用基于物理的模型,将亮度温度与星载光学和激光雷达任务中可用的冠层覆盖率和高度百分比联系起来,并通过模拟冠层覆盖率、高度和AGB之间的关系,将其与AGB联系起来。根据2016年获得的H和V极化SMOS和SMAP亮度温度计算的极化指数,通过10天的合成,生成了36张全球AGB地图。与ESA气候变化倡议生物量AGB图相比,由SMOS和SMAP得出的AGB估计值具有较低的系统偏差,并解释了参考图中30%至80%的AGB变异性(取决于森林类型)。通过与主要森林生物群系有限地点的样地级清查数据所得的AGB参考信息的比较,表明了所建议的检索方法的优点,但也表明需要在局部改进检索算法。
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来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
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.
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