Estimating Soil Moisture Using Optical and Radar Satellite Remote Sensing Data
The purpose of this work is to investigate the possible use of MODIS and ENVISAT-ASAR Data to extract soil moisture (SM) field and validate the developed systems by means of in situ measurements.
The main idea of this study concerns the advantages that could arise from a continuous and almost real time SM monitoring, permitted by wide-swath passive optical sensors that allow evaluating the dynamic evolution of different phenomena on a wide range of application fields: from hydrological monitoring and management to agricultural applications and so on. Observations provided by MODIS have no direct physical relation with soil water content. On the other hand, the relationship between Land Surface temperature (LST), NDVI and in situ measurements have shown many potentialities to indirectly retrieve SM information.
The use of SAR data for validation purposes is envisaged but not yet applied.
Calibration and validation phases are performed over a test site where in situ measurements are available.
KeywordsSoil moisture Thermal Inertia optical radar sensor SoA-TI MODIS ASAR
Unable to display preview. Download preview PDF.
- Bignami C., Pierdicca N., Pulvirenti L., Ticconi F. Risultati preliminari di campagne sperimentali sulla sensibilità dei dati Envisat-ASAR all'umidità del terreno, XV Riunione Nazionale di Elettromagnetismo RINEM2004, Cagliari, http://www.elettromagnetismo.it/ atti_rinem/2004S14A05.pdf
- Boisvert J. B., Crevier Y., Pultz T. J. 1996. Regional estimation of soil moisture using remote sensing, in Canadian Journal of Soil Science, n.76 (3): 325–334Google Scholar
- Cai G., Wu J., Xue J., Hu Y., Guo J., Tang J. 2005. Soil Moisture Retrieval from MODIS data in Northern China Plain Using Thermal Inertia Model (SoA-TI), 0-7803-9050-4/05 2005 IEEEGoogle Scholar
- Cravey R. L., Jackson T. J., Hsu Ann Y. 1998. ERS-2 SAR Backscattering Coefficient and Soil Moisture for the Southern Great Plains 1997 Hydrology Experiment. Retrieval of Bio- and Geo-Physical Parameters from SAR Data for Land Applications Workshop, ESTEC, 21–23, October 1998Google Scholar
- Glenn, N. F., Carr J. R. 2004. Establishing a relationship between soil moisture and RADARSAT-1 SAR data obtained over the Great Basin, Nevada, USA, in Canadian Journal of Remote Sensing, n.30 (2): 176–181Google Scholar
- Ma A., Xue Y. 1990. A study of remote sensing: information model of soil moisture, in Proceedings of the 11th Asian Conference on Remote Sensing, n.1, 11.1–11.5Google Scholar
- MEEO SOIL MAPPER TM Report description document 2007. Issue 3.7, Date: 12/03/2007, http://www.meeo.it/docs/SOIL_MAPPER_report.pdf
- Paloscia S., Pampaloni P., Pettinato S., Poggi P., Santi E. 2005. The retrieval of soil moisture from Envisat-ASAR data, in European Association of Remote Sensing Laboratories—EARSeL eProceedings, n.4 (1): 44–52, http://www.eproceedings.org/static/vol04_1/ 04_1_paloscia1.html
- Portmann F. 2000. The Land-SAF Soil Moisture Product of MIUB and BfG. Paper presented at the CM-SAF (EUMETSAT Climate Monitoring Satellite Application Facility) Training Workshop, Dresden, Germany, 20–22 November 2000, pp. 6Google Scholar
- Turner D. P., Ritts W. D., Cohen W. B., Maeirsperger T. K., Gower S., Kirschbaum A. A., Running S. W., Zhao M., Wofsy S. C., Dunn A. L., Law B. E., Campbell J. L., Oechel W. C., Kwon H. J., Meyers T. P., Small E. E., Kurc S. A., Gamon J. A. 2005. Site-level evaluation of satellite-based global terrestrial gross primary production and net primary production monitoring, in Global Change Biology, n.11: 666–684CrossRefGoogle Scholar
- Wan Z. 1999. MODIS Land-Surface Temperature Algorithm Theoretical Basis Document (LST ATBD). Institute for Computational Earth System Science University of California, Santa Barbara, Version 3.3, April 1999Google Scholar