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Soil moisture mapping in a semiarid region, based on ASAR/Wide Swath satellite data
Author(s) -
Zribi M.,
Kotti F.,
Amri R.,
Wagner W.,
Shabou M.,
LiliChabaane Z.,
Baghdadi N.
Publication year - 2014
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2012wr013405
Subject(s) - normalized difference vegetation index , water content , environmental science , remote sensing , satellite , precipitation , moisture , vegetation (pathology) , geology , meteorology , climate change , geography , medicine , oceanography , geotechnical engineering , pathology , aerospace engineering , engineering
In this paper, an operational algorithm is proposed for the mapping of surface moisture over the northern and central parts of Tunisia, in North Africa. A change detection approach is applied, using 160 multiincidence Envisat ASAR Wide Swath images acquired in the horizontal polarization over a 7 year period. Parameterization of this algorithm is considered for three classes of vegetation cover density (NDVI < 0.25, 0.25 < NDVI < 0.5, and NDVI > 0.5), retrieved from SPOT‐VGT decadal images. A relative soil moisture index, ranging between 0 (for the driest surfaces) and 1 (for saturated soils), is proposed for each date, with a resolution of 1 km. The retrieved soil moistures are validated by means of ground measurements based on continuous thetaprobe measurements, as well as low‐resolution (25 km) ERS and ASCAT soil moisture products from the Vienna University of Technology (TU Wien). A qualitative relationship between spatiotemporal variations of moisture and precipitation is also discussed.