Shi 3/15/2001-3/14/2004 $150,241
National Aeronautics and Space Administration, NAG5-10671 (JSN03)
Estimate Soil Moisture Change Using Radarsat and its Application Hydrological modeling
Measuring spatially distributed soil moisture from space is a key component for improvement of our understanding of coupled atmosphere-surface processes. This study focuses on evaluating the utility of RADARSAT alone or with ERS-2 and JERS-1 derived soil moisture information, and implementing the information into a hydrological model. It is well known that SAR measurements are sensitive to soil moisture. However, an operational algorithm to derive soil moisture has not bee developed due to the difficulty in resolving roughness and vegetation effects, especially for single-polarization SAR. Rather than attempting to estimate an absolute soil moisture value, our technique is based on the change detection concept to derive the relative changes in soil moisture between the SAR data acquisitions. The estimated relative soil moisture change, then, will be used as an input or to be coupled with a hydrological model to improve the water and energy balance performance and thus its accuracy. This investigation will: 1) develop and verify an algorithm to estimate the relative change in surface soil moisture with Radarsat measurements; 2) evaluate the multi-SAR techniques (Radarsat, ERS, and JERS) in improving estimation accuracy, and 3) couple the SAR derived soil moisture change with the water and energy balance hydrologic models.
Jiancheng Shi 2/15/2002-2/14/2005 $282,330
National Aeronautics and Space Administration, NAG5-11709 (JSN04)
Multi-scale Convergence of Cold-land Process Representation in Land-surface Models, Microwave Remote Sensing, and Field Observations
This project aims to improve the synergism between land-surface models and microwave remote sensing for cold regions by improving the model representation of several cold-land processes, with explicit consideration of how these process representations relate to the process of remote sensing. At scales ranging from a small study plot to 25-km areas, we will use the land-surface models to force forward simulations of microwave emission and backscatter response to snow and soil characteristics, and compare these forward simulations to ground-and airborne-remote sensing observations. Beginning at the plot scale, we will quantify the "baseline" uncertainty associated with forward estimation of microwave-response under ideal circumstances. Then, as we advance in scale and more surface heterogeneity is introduced, we will develop and improved understanding of specific deficiencies in the land-surface models, and the discrepancies these cause with respect to remotely sensed microwave observations. We can then work to improve these deficiencies to improve agreement with the remotely sensed measurements.
Jiancheng Shi 12/14/2002-1/31/2004 $35,000
Jet Propulsion Laboratory, 1247720 (JSP01)
HYDROS Project Risk Mitigation Task Plan
This project contributes to the HYDROS risk mitigation task through two complementary efforts:
1) participating with
other HYDROS team members in an end-to-end observing simulation study and error
analysis of HYDROS soil moisture data products. Specifically, providing computer
simulations of the HYDROS backscatter and brightness temperature response to a
geophysical scene typical of that to be observed by HYDROS. The parameter
database comprising the geophysical scene will be provided to UCSB at the
inception of the study. The backscatter and brightness temperature simulations
will include effects of soil and vegetation, and noise and calibration error
characteristics typical of those expected for HYDROS. The output of the
simulations will be a database that will be made available to other members of
the HYDROS team. Retrievals will be performed on this database to assess the
ability to recover soil moisture in the presence of vegetation and other
instrument and geophysical noise.
2) Contributing to a HYDROS soil moisture algorithm development and assessment study using SMEX02 and SGP99 field experiment data. Data acquired during the SGP99 and SMEX02 field experiments using the JPL Passive and Active L- and S-band (PALS) sensor and the JPL Airborne Synthetic Aperture Radar (AirSAR) will be used for the study. The data will be aggregated to resolution scales that simulate the HYDROS passive and active footprints and HYDROS retrieval algorithms will be applied to these data to illustrate the algorithm performance and heterogeneity effects at these scales.
Jiancheng Shi 6/1/2004-6/1/2005 $20,000
Jet Propulsion Laboratory, 1262093 (JSP02)
HYDROS Project Risk Mitigation Task Plan
This project involves participation with other HYDROS team members in developing and evaluating retrieval algorithms for HYDROS soil moisture data products. UCSB is providing research, analysis, and computer simulations of the HYDROS backscatter response to geophysical scenes typically of those to be observed by HUDROS. The backscatter and brightness temperature simulations will include effects of soil and vegetation, and noise and calibration error characteristics typical of those expected of HYDROS. Additionally, HYDROS soil moisture algorithm development and assessment studies using SMEX02 and SMEX03 field experiment data will be completed. Data acquired during previous field experiments (JPL Passive and Active L- and S-band (PALS) and the JPL Airborne Synthetic Aperture Radar (AirSAR)) will be used to supplement the simulations (above) in verifying and validating the performance of the HYDROS soil moisture algorithms.