Estimation of the spatially distributed surface energy budget for AgriSAR 2006, part II : Integration of remote sensing and hydrologic modeling
In most hydrologic modeling studies, the hypothesis is made that an improvement in the modeled soil moisture leads to an improvement in the modeled surface energy balance. The objective of this paper is to assess whether this hypothesis is true. The study was performed over the winter wheat fields in the AgriSAR 2006 domain. Remotely sensed soil moisture values and latent heat fluxes were used, in combination with in situ observations. First, the land cover and saturated subsurface flow parameters were estimated using the in situ observations. A spatially distributed model simulation was then performed, for which the Brooks-Corey parameters were derived from a soil texture map, and of which…
On the use of multi-temporal series of COSMO-SkyMed data for LANDcover classification and surface parameter retrieval over agricultural sites
The objective of this paper is to report on the activities carried out during the first year of the Italian project “Use of COSMO-SkyMed data for LANDcover classification and surface parameters retrieval over agricultural sites” (COSMOLAND), funded by the Italian Space Agency. The project intends to contribute to the COSMO-SkyMed mission objectives in the agriculture and hydrology application domains.
Estimation of the spatially distributed surface energy budget for AgriSAR 2006, part I : remote sensing model intercomparison
A number of energy balance models of variable complexity that use remotely sensed boundary conditions for producing spatially distributed maps of surface fluxes have been proposed. Validation typically involves comparing model output to flux tower observations at a handful of sites, and hence there is no way of evaluating the reliability of model output for the remaining pixels comprising a scene. To assess the uncertainty in flux estimation over a remote sensing scene requires one to conduct pixel-by-pixel comparisons of the output. The objective of this paper is to assess whether the simplifications made in a simple model lead to erroneous predictions or deviations from a more complex mod…
Time series of Cosmo-SkyMed data for landcover classification and surface parameter retrieval over agricultural sites
This paper reports on the results of an Italian project aimed at investigating the use of X-band COSMO-SkyMed (CSK) SAR data for applications in agriculture and hydrology. Existing classification and retrieval algorithms have been tailored to CSK data and time series of crop, leaf area index and soil moisture maps have been retrieved and assessed through the comparison with in situ data collected over three agricultural sites. In addition, the CSK-derived surface parameters have been integrated into crop growth and hydrologic models and the resulting improvements have been assessed. Results indicate that multi-temporal dual-polarized CSK data are very well-suited for agricultural crop class…