Vol. 8, No. 2, 180-186, 2009

Evaluation of an operational leaf area index retrieval approach using VEGETATION and MODIS data
Aleixandre Verger, Fernando Camacho, Javier García-Haro and Joaquín Meliá

An operational method has been proposed to estimate the leaf area index (LAI) from satellite imagery in the framework of EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA SAF). This study evaluates the performance of the LSA SAF LAI retrieval algorithm when prototyped to VEGETATION/CYCLOPES and MODIS reflectances over Europe for the 2000-2003 period. The results indicate that LSA SAF algorithm retrieves consistent LAI estimates from multiple remotely sensed imagery even when input reflectances present systematic differences. High spatial and temporal consistencies between LSA SAF prototyped LAI and CYCLOPES and MODIS products are found. Differences in LAI between CYCLOPES products and LSA SAF estimates are lower than 0.4 LAI units in terms of RMSE. Larger discrepancies are found when comparing LSA SAF prototyped estimates against MODIS products due, in part, to differences in products assumptions (RMSE ranging from 0.2 up to 0.8 with higher (lower) LSA SAF LAI values compared to MODIS for herbaceous (woody) biomes). Direct validation indicates that LSA SAF prototype estimates achieve similar performances (0.8 and 0.6, respectively) as CYCLOPES and MODIS LAI products. This study constitutes a step forward for the validation and consolidation of the LSA SAF LAI algorithm.

View Full Text (pdf file, 200 kB) previous page
Submitted: 14 July 2009
Revised: 30 Nov 2009
Accepted: 01 Dec 2009
Published: 18 Dec 2009
Responsible editor: Zbigniew Bochenek

Verger A, F Camacho, J García-Haro & J Meliá, 2009. Evaluation of an operational leaf area index retrieval approach using VEGETATION and MODIS data. EARSeL eProceedings, 8(2): 180-186


EARSeL European Association of Remote Sensing Laboratories, Strasbourg, France


BIS Library and Information System, Carl von Ossietzky University of Oldenburg


ISSN 1729-3782