
Proceedings Paper
Monitoring irrigation volumes using high-resolution NDVI image time series: calibration and validation in the Kairouan plain (Tunisia)Format | Member Price | Non-Member Price |
---|---|---|
$17.00 | $21.00 |
Paper Abstract
The increasing availability of high resolution high repetitively VIS-NIR remote sensing, like the forthcoming Sentinel-2 mission to be launched in 2015, offers unprecedented opportunity to improve agricultural monitoring. In this study, regional evapotranspiration and crop water consumption were estimated over an irrigated area located in the Kairouan plain (central Tunisia) using the FAO-56 dual crop coefficient water balance model combined with NDVI image time series providing estimates of the actual basal crop coefficient (Kcb) and vegetation fraction cover. Three time series of high-resolution SPOT5 images have been acquired for the 2008-2009, 2011-2012 and 2012-2013 hydrological years. We also benefited from a SPOT4 time series acquired in the frame of the SPOT4-Take5 experiment. The SPOT5 images were radiometrically corrected, first, using the SMAC6s Algorithm, and then improved using invariant objects located on the scene.
The method was first calibrated using ground measurements of evapotranspiration achieved using eddy-correlation devices installed on irrigated wheat and barley plots. For other crops for which no calibration data was available, parameters were taken from bibliography. Then, the model was run to spatialize irrigation over the whole area and a validation was done using cumulated seasonal water volumes obtained from ground survey for three irrigated perimeters. In a subsequent step, evapotranspiration estimates were obtained using a large aperture scintillometer and were used for an additional validation of the model outputs.
Paper Details
Date Published: 14 October 2015
PDF: 15 pages
Proc. SPIE 9637, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII, 963710 (14 October 2015); doi: 10.1117/12.2195183
Published in SPIE Proceedings Vol. 9637:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII
Christopher M. U. Neale; Antonino Maltese, Editor(s)
PDF: 15 pages
Proc. SPIE 9637, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII, 963710 (14 October 2015); doi: 10.1117/12.2195183
Show Author Affiliations
S. Saadi, Univ. de Carthage (Tunisia)
Ctr. d'Etudes Spatiales de la Biosphère (France)
V. Simonneaux, Ctr. d'Etudes Spatiales de la Biosphère (France)
G. Boulet, Ctr. d'Etudes Spatiales de la Biosphère (France)
Univ. de Carthage (Tunisia)
Ctr. d'Etudes Spatiales de la Biosphère (France)
V. Simonneaux, Ctr. d'Etudes Spatiales de la Biosphère (France)
G. Boulet, Ctr. d'Etudes Spatiales de la Biosphère (France)
Univ. de Carthage (Tunisia)
B. Mougenot, Ctr. d'Etudes Spatiales de la Biosphère (France)
Univ. de Carthage (Tunisia)
Z. Lili Chabaane, Univ. of Carthage (Tunisia)
Univ. de Carthage (Tunisia)
Z. Lili Chabaane, Univ. of Carthage (Tunisia)
Published in SPIE Proceedings Vol. 9637:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII
Christopher M. U. Neale; Antonino Maltese, Editor(s)
© SPIE. Terms of Use
