Hadria R., Duchemin Benoît, Baup F., Le Toan T., Bouvet A., Dedieu G., Le Page M. (2009). Combined use of optical and radar satellite data for the detection of tillage and irrigation operations : case study in Central Morocco. Agricultural Water Management, 96 (7), p. 1120-1127. ISSN 0378-3774.
Titre du document
Combined use of optical and radar satellite data for the detection of tillage and irrigation operations : case study in Central Morocco
Année de publication
Hadria R., Duchemin Benoît, Baup F., Le Toan T., Bouvet A., Dedieu G., Le Page M.
Agricultural Water Management, 2009,
96 (7), p. 1120-1127 ISSN 0378-3774
The objective of this study is to present a new application of optical and radar remote sensing with high spatial (similar to 10 m) and temporal (a few days) resolutions for the detection of tillage and irrigation operations. The analysis was performed for irrigated wheat crops in the semi-arid Tensift/Marrakech plain (Central Morocco) using three FORMOSAT-2 images and two ASAR images acquired within one week at the beginning of the 2005/2006 agricultural season. The approach we developed uses simple mapping algorithms (band thresholding and decision tree) for the characterisation of soil surface states. The first images acquired by FORMOSAT and ASAR were processed to classify fields into three main categories: ploughed (in depth), prepared to be sown (harrowed), and not ploughed-not harrowed. This information was combined with a change detection analysis based on multitemporal images to identify harrowing and irrigation operations which occurred between two satellite observations. The performance of the algorithm was evaluated using data related to land use and agricultural practices collected on 124 fields. The analysis shows that drastic changes of surface states caused by ploughing or irrigation are detected without ambiguity (consistency index of 96%). This study provided evidence that optical and radar data contain complementary information for the detection of agricultural operations at the beginning of agricultural season. This information could be useful in regional decision support systems to refine crop calendars and to improve prediction of crop water needs over large areas.
Plan de classement
Fonds IRD [F B010046153]