ASCAT IB: A radar-based vegetation optical depth retrieved from the ASCAT scatterometer satellite

REMOTE SENSING OF ENVIRONMENT

卷:264

Article

Liu, Xiangzhuo¹  Wigneron, Jean-Pierre¹  Fan, Lei²  Frappart, Frederic^1,3  Ciais, Philippe⁴  Baghdadi, Nicolas⁵  Zribi, Mehrez⁶  Jagdhuber, Thomas^7,8  Li, Xiaojun¹  Wang, Mengjia^1,9  Bai, Xiaojing¹⁰  Moisy, Christophe¹ 

[1] Univ Bordeaux, INRAE, UMR1391, ISPA, F-33140 Villenave Dornon, France

[2] Southwest Univ, Sch Geog Sci, Chongqing Jinfo Mt Karst Ecosyst Natl Observat &, Chongqing 400715, Peoples R China

[3] Lab Etud Geophys & Oceanog Spatiales LEGOS, F-31400 Toulouse, France

[4] Univ Paris Saclay, UVSQ, CEA, Lab Sci Climat Environm,CNRS, Gif Sur Yvette, France

[5] Univ Montpellier, UMR TETIS, INRAE, 500 Rue Francois Breton, F-34093 Montpellier 5, France

[6] Univ Toulouse, UPS, CNRS, CESBIO,IRD,CNES, 18 Av Edouard Belin,Bpi 2801, F-31401 Toulouse 9, France

[7] DLR Microwaves & Radar Inst, German Aerosp Ctr, POB 1116, D-82234 Wessling, Germany

[8] Univ Augsburg, Inst Geog, D-86159 Augsburg, Germany

[9] Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

[10] Nanjing Univ Informat Sci Technol, Sch Hydrol & Water Resources, Nanjing 210044, Peoples R China

关键词: VOD;    ASCAT;    Active microwave;    Africa;    Biomass;    Tree height;    NDVI;    EVI;    LAI;   

DOI  :  10.1016/j.rse.2021.112587

来源: Elsevier

【 摘 要 】

Vegetation optical depth (VOD), as a microwave-based vegetation index for vegetation water and biomass content, is increasingly used to study the impact of global climate and environmental changes on vegetation. Currently, VOD is mainly retrieved from passive microwave data and few studies focused on VOD retrievals from active microwave data. The Advanced SCATterometer (ASCAT) provides long-term C-band backscatter data at Vertical-Vertical (VV) polarization. In this study, a new ASCAT INRAE Bordeaux (IB) VOD (hereafter, IB VOD), was developed based on the Water Cloud Model (WCM) coupled with the Ulaby linear model for soil back scattering. The main features of IB VOD are that (i) the ERA5-Land soil moisture (SM) dataset was used as an auxiliary SM dataset in the retrievals, (ii) pixel-based soil model parameters were mapped using Random Forest (RF), and (iii) the vegetation model parameter was calibrated for each day. The IB VOD product was retrieved over Africa during 2015-2019, and its performances were evaluated in space and time by comparing with aboveground biomass (AGB), lidar tree height (TH), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and leaf area index (LAI). Results were inter-compared with three other VOD products at the same frequency. In terms of spatial correlation with AGB (R = 0.92) and TH (R = 0.89), IB VOD outperforms the other VOD products, suggesting IB VOD has a strong ability to capture spatial patterns of AGB and TH. By comparing all VOD products against NDVI, EVI and LAI, we found that the highest temporal correlation with NDVI (EVI, LAI) was obtained with IB VOD over 29.94% (36.65%, 30.19%) of the study region. Considering all three vegetations indices, highest temporal correlation values with IB VOD could be particularly noted for deciduous broadleaf forests, woody savannas and savannas.

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