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Proceedings Paper

High resolution mapping of soil moisture in agriculture based on Sentinel-1 interferometric data
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Paper Abstract

In this work we study the problem of mapping soil moisture by means of Synthetic Aperture Radar (SAR) images. A test site has been set in Companhia das Lezirias, close to Lisbon, Portugal. The main advantage of using SAR images is their capability to map soil moisture at a very high spatial resolution. This opens interesting perspectives for agricultural applications, where soil moisture can abruptly change across field boundaries depending on the agricultural practices. The study area is characterized by flat topography, large agricultural areas and sparse vegetation. Five sensors have been deployed in a test area to measure soil moisture with a sampling time of one hour for a period of seven months. In-situ measurements are compared with the results obtained by processing 33 C-band Sentinel-1 images using the SAR interferometry technique. The aim of the study is to analyze the relation between the interferometric phase and time varying soil moisture. The main advantage of SAR interferometry with respect to the use of radar cross-section is that the information about soil moisture can be recovered using a reduced number of in-situ measurements. In particular, we combine three interferograms obtained from three SAR images, acquired over the same area at different times, to derive maps of bi-coherence and phase triplet. This last quantity allows to disentangle the phase contribution due to soil moisture from those related to microwave propagation in atmosphere and terrain displacements. Results are compared to those obtained using the interferometric phase and coherence to emphasize the importance to split the effects due to propagation (e.g. atmosphere) from those related to volume scattering.

Paper Details

Date Published: 10 October 2018
PDF: 6 pages
Proc. SPIE 10783, Remote Sensing for Agriculture, Ecosystems, and Hydrology XX, 107831U (10 October 2018); doi: 10.1117/12.2325709
Show Author Affiliations
Vasco Conde, Univ. de Lisboa (Portugal)
João Catalão, Univ. de Lisboa (Portugal)
Giovanni Nico, Istituto per le Applicazioni del Calcolo "Mauro Picone" (Italy)
Pedro Benevides, Univ. de Lisboa (Portugal)


Published in SPIE Proceedings Vol. 10783:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XX
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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