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Proceedings Paper

Geostatistical regularization of inverse models for the retrieval of vegetation biophysical variables
Author(s): C. Atzberger; K. Richter
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Paper Abstract

The robust and accurate retrieval of vegetation biophysical variables using radiative transfer models (RTM) is seriously hampered by the ill-posedness of the inverse problem. With this research we further develop our previously published (object-based) inversion approach [Atzberger (2004)]. The object-based RTM inversion takes advantage of the geostatistical fact that the biophysical characteristics of nearby pixel are generally more similar than those at a larger distance. A two-step inversion based on PROSPECT+SAIL generated look-up-tables is presented that can be easily implemented and adapted to other radiative transfer models. The approach takes into account the spectral signatures of neighboring pixel and optimizes a common value of the average leaf angle (ALA) for all pixel of a given image object, such as an agricultural field. Using a large set of leaf area index (LAI) measurements (n = 58) acquired over six different crops of the Barrax test site (Spain), we demonstrate that the proposed geostatistical regularization yields in most cases more accurate and spatially consistent results compared to the traditional (pixel-based) inversion. Pros and cons of the approach are discussed and possible future extensions presented.

Paper Details

Date Published: 7 October 2009
PDF: 12 pages
Proc. SPIE 7478, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX, 74781O (7 October 2009); doi: 10.1117/12.830009
Show Author Affiliations
C. Atzberger, Joint Research Ctr. of the European Commission (Italy)
K. Richter, Univ. of Naples Federico II (Italy)

Published in SPIE Proceedings Vol. 7478:
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX
Ulrich Michel; Daniel L. Civco, Editor(s)

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