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Proceedings Paper

Soil moisture retrieval from SAR images as a calibration tool for soil moisture index derived from thermal inertia with MODIS images
Author(s): C. Notarnicola; B. Ventura; S. Pettinato; E. Santi; M. Zebisch
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Paper Abstract

This paper aims at identifying an operational methodology to derive soil moisture status from optical images by using soil moisture values derived from SAR images as a calibration tool . In the first part of the paper, an algorithm based on Bayesian techniques for the retrieval of soil moisture from C-band SAR images is presented. The algorithm is composed of two modules, one for bare soil and the other for vegetated soil which includes also the use of optical images in order to take into account the vegetation contribution. soil moisture values retrieved from images are then used as a calibration tool for a soil moisture index derived from MODIS images. In this case, the method to estimate soil moisture index from optical and thermal images is based on the calculation of the Apparent Thermal Inertia (ATI). ATI is considered as an approximate (apparent) value of the thermal inertia and is obtained from spectral measurements of the albedo and the diurnal temperature range. soil moisture estimated from SAR images and the ATI are compared in order to find a calibration curve which should cover the entire soil moisture values from saturation to residual moisture values. For the calibration experiment, three main sites were chosen which exhibit different landscape and climatic characteristics. The Basento basin is located in Southern Italy and is characterized by long period of droughts. The Scrivia valley is flat alluvial plain measuring situated close to the confluence of the Scrivia and Po rivers in Northern Italy. The Cordevole watershed, located at the foothill of Mount Sella in Northern Italy is mainly covered by grassland and it was selected because of its relatively smooth topography. The first results indicate a good correlation between ATI and the soil moisture values derived both from measurements and estimated from SAR images.

Paper Details

Date Published: 29 September 2009
PDF: 8 pages
Proc. SPIE 7477, Image and Signal Processing for Remote Sensing XV, 74771U (29 September 2009); doi: 10.1117/12.834922
Show Author Affiliations
C. Notarnicola, EURAC research (Italy)
B. Ventura, Univ. di Bari (Italy)
S. Pettinato, Istituto di Fisica Applicata Nello Carrara, CNR (Italy)
E. Santi, Istituto di Fisica Applicata Nello Carrara, CNR (Italy)
M. Zebisch, EURAC research (Italy)


Published in SPIE Proceedings Vol. 7477:
Image and Signal Processing for Remote Sensing XV
Lorenzo Bruzzone; Claudia Notarnicola; Francesco Posa, Editor(s)

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