Publication Date:
2017-04-04
Description:
An algorithm for pre-operational high resolution soil
moisture mapping using Synthetic Aperture Radar (SAR) data is
presented. It has been conceived to be inserted in the operational
weather alert system of the Italian Department of Civil Protection.
The Maximum A Posteriori (MAP) probability criterion is
applied to retrieve soil moisture by inverting a forward backscattering
model, and ancillary data such as optical images and land
cover maps are also used to identify areas in which the retrieval
can be carried out. The well-established semiempirical water cloud
model is adopted to correct for the effect of vegetation on SAR data.
In anticipation of the use of the algorithm in an operational system,
in which the SAR-derived high resolution soil moisture product
can be assimilated within weather prediction models or hydrological
ones, an uncertainty index is associated to each estimate. The
algorithm has been tested on a dataset consisting of ground data
gathered for seven years (2003–2010) on an agricultural test site
in Northern Italy and radar data provided by the C-band ENVISAT/
ASAR instrument. A comparison, performed at field scale,
between estimated and in situ soil moisture data has shown that,
by discarding the estimates with the largest uncertainty, the correlation
coefficient can exceed 0.80 and the root mean square estimation
error is less than 0.05 m /m . Moreover, the uncertainty
index has turned out to be fairly correlated to the actual estimation
error.
Description:
Published
Description:
1199 - 1210
Description:
6A. Monitoraggio ambientale, sicurezza e territorio
Description:
JCR Journal
Description:
restricted
Keywords:
SAR
;
soil moisture
;
03. Hydrosphere::03.02. Hydrology::03.02.04. Measurements and monitoring
;
03. Hydrosphere::03.02. Hydrology::03.02.07. Instruments and techniques
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
article
