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TitleQuantitative Soil Moisture Extraction from Airborne SAR Data
 
AuthorPultz, T J; Leconte, R; Brown, R J; Brisco, B
SourceCanadian Journal of Remote Sensing 16, 3, 1990 p. 56-62, https://doi.org/10.1080/07038992.1990.11487625
Year1990
Alt SeriesEarth Sciences Sector, Contribution Series 20040901
Alt SeriesRESORS 1078783
PublisherInforma UK Limited
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
Subjectsgeophysics; remote sensing
Released2015 09 02
AbstractKnowledge of the moisture content of soil is valuable for hydrology and climate studies, as well as for yield prediction or agricultural planning. As part of the long-term research plan at the Canada Centre for Remote Sensing (CCRS) to establish a relationship between radar backscatter and the spatial and temporal variations of soil moisture, a series of experiments were conducted in the Canadian prairies in 1988.

This paper examines radar backscatter as a function of soil moisture, plant type, and phenological development. Airborne data were acquired by the CCRS C-band SAR of a test site near Outlook, Saskatchewan, in June and August 1988. The digitally recorded and processed imagery were externally calibrated via point targets of known radar cross-section. Soil dielectric measurements were collected using a portable dielectric probe in fields with similar surface roughness characteristics. These measurements were used as input to a model developed by CCRS for estimating soil volumetric water content.

This paper describes the development of relationships between soil moisture under wheat and canola canopies and radar backscatter. The relationships were developed using the relatively calibrated SAR, the estimate of soil volumetric water content derived from soil dielectric measurements, plant type and phonological development. The analysis indicated a strong correlation between radar backscatter and volumetric soil moisture under both wheat and canola canopies and that the relationship is dependent on crop type and phonological development.
GEOSCAN ID217703

 
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