Speaker
Prof.
Nazzareno Pierdicca
(Sapienza, University of Rome)
Description
Remote sensing represents a very useful tool to monitor volumetric Soil Moisture Content (SMC) at different temporal and spatial scale. Indeed, such measures present a direct sensitivity to SMC at microwave bands, where the soil electrical permittivity is influenced by the water content. However, the radar return is sensitive not only to soil moisture, but also to surface roughness and, in presence of vegetation, to biomass and other vegetation parameters, so that the retrieval process is quite challenging.
Synthetic Aperture Radar (SAR) systems are characterized by high spatial resolution, so that detailed soil moisture maps can be obtained. Nowadays, frequent coverage of SAR images are becoming feasible thanks to the launch of the ESA Sentinel 1 A and B satellites (C-band). The NASA Soil Moisture Active and Passive (SMAP) satellite (L-Band) was also conceived for this purpose, although unfortunately the radar failed after a short period of operation and only low resolution soil moisture map are produced from SMAP radiometer.
In this work, we test a multitemporal algorithm (MLTA) to retrieve soil moisture from L-band data, such as those produced by SMAP; the multitemporal algorithm has been originally developed for the 2-polarization radar images produced by Sentinel-1 at C-band1. The software has been updated to accommodate SMAP radar images, which are collected at L-Band and three polarizations (HH-VV and HV) within short revisit time. Such type of algorithm may deliver frequent and more accurate soil moisture maps mitigating the problems due to the roughness and vegetation changes, which can be assumed to occur at longer temporal scale respect to the changes of soil moisture. A dense time series of radar backscatter measurements are integrated within a multitemporal inversion scheme based on the Bayesian Maximum A Priori (MAP) criterion in order to invert a forward backscattering model, which relates the backscattering coefficient to the bare soil parameters (not only soil moisture, but also soil roughness) and includes also the contribution from vegetation.
A segmentation of the SMAP coverage has been carried out in order to minimize the revisit time of each area along the SMAP orbit precise cycle, by exploiting the superimposition of the radar field of view for different tracks. Moreover, it is analysed how working with the SMAP L1C sigma nought product at full resolution (1 km) may improve the estimates of soil moisture with respect to using the 3-km resolution sigma nought.
The data provided by the calibration and validation (CAL/VAL) campaign SMAP Validation Experiment 012 (SMAPVEX012) has been used to update the forward model for bare soil scattering at L-band with respect to the Oh and Sarabandi2 model previously used at C Band and, in a second step, to tune simple vegetation scattering models. SMAPVEX012 consists of in situ soil moisture and vegetation parameters measurements coincidently to L Band images collected by the UAVSAR sensor over several agricultural regions located South of Winnipeg, Manitoba (Canada), which includes a range of crop types, some permanent grasslands, wetlands and mixed forest cover.
The results of the inversion algorithm applied to the SMAPVEX012 data are presented and compared to ground truth, thus summarizing strength and weakness of the approach.
[1] N. Pierdicca, L. Pulvirenti, G. Pace: A Prototype Software Package to Retrieve Soil Moisture from Sentinel 1 Data by Using a Bayesian Multitemporal Algorithm. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 1, pp., 153-166, Jan. 2014.
[2] Y. Oh, K. Sarabandi, F. T. Ulaby: Semi-empiricalmodel of the ensemble-averaged differential Mueller matrix for microwave backscattering from bare soil surfaces. IEEE Trans. Geosci. Remote Sens., vol. 40, 1348–1355, 2002.
Primary author
Mr
Fabio Fascetti
(Sapienza, University of Rome)
Co-authors
Dr
Luca Pulvirenti
(CIMA Research Foundation)
Prof.
Nazzareno Pierdicca
(Sapienza, University of Rome)
