GEOV2: Improved smoothed and gap filled time series of LAI, FAPAR and FCover 1 km Copernicus Global Land products

被引:5
|
作者
Verger, Aleixandre [1 ,2 ]
Sanchez-Zapero, Jorge
Weiss, Marie [4 ]
Descals, Adria [2 ]
Camacho, Fernando [3 ]
Lacaze, Roselyne [5 ]
Baret, Frederic
机构
[1] CSIC, CIDE, UV, GVA, Valencia 46113, Spain
[2] CREAF, Cerdanyola Del Valles 08193, Catalonia, Spain
[3] EOLAB, Paterna 46980, Valencia, Spain
[4] Avignon Univ, INRAE, UMR1114 EMMAH, F-84914 Avignon, France
[5] HYGEOS, F-59000 Lille, France
基金
欧盟第七框架计划;
关键词
Global vegetation monitoring; Leaf area index; Fraction of absorbed PAR; Green vegetation cover; SPOT/VGT; PROBA-V; ESSENTIAL CLIMATE VARIABLES; AREA INDEX PRODUCTS; LEAF-AREA; MODIS; VALIDATION; VEGETATION; PRINCIPLES; CYCLOPES; FPAR; PAR;
D O I
10.1016/j.jag.2023.103479
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Essential vegetation variables including leaf area index (LAI), fraction of absorbed photosynthetic active radiation (FAPAR) and fraction of green vegetation cover (FCover) are produced and distributed in the Copernicus Global Land Service. We describe here the algorithmic principles, consistency and improvements of GEOV2, Version 2 of LAI, FAPAR and FCover products derived from SPOT/VGT (1999-2013) and PROBA-V data (2014-2020) at 1 km resolution, as compared to the earlier version GEOV1. GEOV2 is based on neural networks first trained with CYCLOPES and MODIS products to estimate LAI, FAPAR and FCover from daily top of canopy reflectance. Temporal techniques are then applied to filter, smooth, fill gaps and get a composited value every 10 days. Results show that GEOV2 products keep a high consistency with GEOV1 (90% of residuals within +/- max (0.5, 20%) LAI, and 80% within +/- max(0.05, 10%) FAPAR / FCover) and improves in terms of product completeness (<1% of missing data), temporal consistency, consistency across variables and accuracy.
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页数:12
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