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Proceedings Paper

Contribution of radar images for grassland management identification
Author(s): P. Dusseux; X. Gong; T. Corpetti; L. Hubert-Moy; S. Corgne
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Paper Abstract

This paper is concerned with the identification of grassland management using both optical and radar data. In that context, grazing, mowing and a mix of these two managements are commonly used by the farmers on grassland fields. These practices and their intensity of use have different environmental impact. Thus, the objectives of this study are, firstly, to identify grassland management practices using a time series of optical and radar imagery at high spatial resolution and, secondly, to evaluate the contribution of radar data to improve identification of farming practices on grasslands. Because of cloud coverage and revisit frequency of satellite, the number of available optical data is limited during the vegetation period. Thus, radar data can be considered as an ideal complement. The present study is based on the use of SPOT, Landsat and RADARSAT-2 data, acquired in 2010 during the growing period. After a pre-processing step, several vegetation indices, biophysical variables, backscattering coefficients and polarimetric discriminators were computed on the data set. Then, with the help of some statistics, the most discriminating variables have been identified and used to classify grassland fields. In addition, to take into account the temporal variation of variables, dedicated indexes as first and second order derivatives were used. Classification process was based on training samples resulting from field campaigns and computed according six methods: Decision Trees, K-Nearest Neighbor, Neural Networks, Support Vector Machines, the Naive Bayes Classifier and Linear Discriminant Analysis. Results show that combined use of optical and radar remote sensing data is not more efficient for grassland management identification.

Paper Details

Date Published: 23 October 2012
PDF: 7 pages
Proc. SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 853104 (23 October 2012); doi: 10.1117/12.974547
Show Author Affiliations
P. Dusseux, COSTEL, CNRS, Univ. Rennes 2 (France)
LIAMA (China)
X. Gong, COSTEL, CNRS, Univ. Rennes 2 (France)
LIAMA (China)
T. Corpetti, LIAMA (China)
COSTEL, CNRS, Univ. Rennes 2 (France)
L. Hubert-Moy, COSTEL, CNRS, Univ. Rennes 2 (France)
S. Corgne, COSTEL, CNRS, Univ. Rennes 2 (France)

Published in SPIE Proceedings Vol. 8531:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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