Soil moisture estimation using synergy of optical, SAR, and topographic data with Gaussian Process Regression

J. Stamenkovic*, C. Notarnicola, N. Spindler, G. Cuozzo, G. Bertoldi, S. Della Chiesa, G. Niedrist, F. Greifeneder, D. Tuia, M. Borgeaud, J.Ph. Thiran

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

In this work we address the synergy of optical, SAR (Synthetic Aperture Radar) and topographic data in soil moisture retrieval over an Alpine area. As estimation technique, we consider Gaussian Process Regression (GPR). The test area is located in South Tyrol, Italy where the main land types are meadows and pastures. Time series of ASAR Wide Swath - SAR, optical, topographic and ancillary data (meteorological information and snow cover maps) acquired repetitively in 2010 were examined. Regarding optical data, we used both, daily MODIS reflectances, and daily NDVI, interpolated from the 16-day MODIS composite. Slope, elevation and aspect were extracted from a 2.5 m DEM (Digital Elevation Model) and resampled to 10 m. Daily soil moisture measurements were collected in the three fixed stations (two located in meadows and one located in pasture). The snow maps were used to mask the points covered by snow. The best performance was obtained by adding MODIS band 6 at 1640 nm to SAR and DEM features. The corresponding coefficient of determination, R2, was equal to 0.848, and the root mean square error, RMSE, to 5.4 % Vol. Compared to the case when no optical data were considered, there was an increase of ca. 0.05 in R2 and a decrease in RMSE of ca. 0.7 % Vol. This work showed that the joint use of NDVI or water absorption reflectance with SAR and topographic data can improve the estimation of soil moisture in specific Alpine area and that GPR is an effective method for estimation.

Original languageEnglish
Title of host publicationSAR Image Analysis, Modeling, and Techniques XIV
EditorsSimonetta Paloscia, Nazzareno Pierdicca, Claudia Notarnicola
PublisherSPIE
ISBN (Electronic)9781628413069
DOIs
Publication statusPublished - 21 Oct 2014
Externally publishedYes
EventSAR Image Analysis, Modeling, and Techniques XIV - Amsterdam, Netherlands
Duration: 24 Sep 201425 Sep 2014

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9243
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceSAR Image Analysis, Modeling, and Techniques XIV
CountryNetherlands
CityAmsterdam
Period24/09/1425/09/14

Keywords

  • Gaussian Proccess Regression
  • MODIS reactance
  • Soil moisture retrieval
  • Synthetic Aperture Radar (SAR)
  • Topographic features

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