Remote Sensing, Hydrology, and Field Experiments I
Presiding: M H Cosh, USDA/ARS Hydrology and Remote Sensing Laboratory; J Jacobs, University of New Hampshire
H33C-01 13:30h
Soil Moisture Experiments 2004 and 2005 Results and Plans
The Soil Moisture Experiments (SMEX) series of field campaigns was designed to address research priorities of several programs involving satellite remote sensing of surface soil moisture. These include the Advanced Scanning Microwave Radiometer (AMSR) on Aqua, the Windsat on Coriolis, and future missions that include NASAs Hydros, the European Space Agency Soil Moisture Ocean Salinity (SMOS) mission and NPOESS. Algorithms, scaling, technology and land-atmosphere studies have all been addressed in each experiment. Scaling is a key aspect of experiment design because of the spatial differences between ground point observations and satellite footprints. In all of the campaigns aircraft sensors have provided the critical link between these. Different geographic domains have been used to provide diverse conditions for algorithm development and validation and a variety of aircraft instruments have been used to support specific objectives. SMEX04 was conducted in August 2004 in the southwestern U.S. and northern Mexico. It was designed to address satellite footprint heterogeneity. The region has the diverse topography, vegetation and rainfall patterns necessary to address this issue. In addition, SMEX04 was timed to coincide with North American Monsoon Experiment (NAME). A working hypothesis of NAME is that among the land surface antecedent boundary conditions that control the onset and intensity of the precipitation is soil moisture. Surface soil moisture can change dramatically after rain events. A review of SMEX04 and preliminary results will be presented. SMEX05 is being planned to understand what contributions to soil moisture retrieval and mapping may be achieved by using fully polarimetric passive microwave observations. This has not been a focus of land parameter investigations in the past. The Windsat instrument provides these measurements at several frequencies. For SMEX05 an aircraft simulator of Windsat will also be employed. The field campaign will be conducted for several weeks in the June/July period near Ames, Iowa. This region includes corn and soybean crop cover. The experiment design will be reviewed.
H33C-02 13:45h
Analysis of PSR Microwave Observations during SMEX04
The Polarimetric Scanning Radiometer (PSR/CX) was flown on a P-3B aircraft as part of SMEX04. PSR/CX has been successfully operated during several previous airborne campaigns. The primary objectives of PSR/CX during SMEX04 are: 1) Contribute to the calibration and validation of AMSR observations over different parts of the globe and to check for the presence of Radio Frequency Interference (RFI), 2) Explore the potential for the development of soil moisture retrieval algorithms using C-band imagery in diverse landscapes (Arizona and Sonora, Mexico), and 3) to develop retrieval algorithms to estimate soil moisture over areas of topographic variability and vegetation. The dominant landuse classes in the different SMEX04 domains are: 1) Arizona - semi-arid climate with sparse vegetation and moderate topography, and 2) Sonora, Mexico - moderate vegetation with strong topographic gradients. SMEX04 consisted of about 84 flightlines at high altitude resulting in 21 mapping domains flown during August, 2004 (11 over Arizona and 10 over Sonora). Each mapping domain is about 75 km x 50 km, providing an excellent area for calibration and validation of AMSR-E observations. Some areas of the SMEX04 domain received heavy localized precipitation as a result of convective activity during the experiment. These resulted in interesting brightness temperature patterns with strong brightness temperature gradients. The presence of these diverse conditions will help address questions relating to scaling of spaceborne microwave observations. Results of comparison between PSR and AMSR and the use of microwave remote sensing to estimate soil moisture over wide range of vegetation and soil moisture conditions are also presented.
H33C-03 14:00h
Validation of Retrieved Soil Moisture From AMSR-E Brightness Temperatures Over the SMEX02 Domain
A coupled hydrologic/radiobrightness model (H/RM) is utilized to estimate brightness temperatures at C and X bands and associated soil moisture for validation of soil moisture retrieved from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). This study is focused on the SMEX02 study area in central Iowa. The oversampling of the AMSR-E instrument is exploited in an optimization algorithm to deconvolve the brightness temperature observations for each EASEgrid cell. In so doing, the influence from adjacent grid cells is much less than with conventional spatial analysis schemes. The high spatial and temporal resolution of H/RM modeling relative to AMSR-E observations permits a statistical assessment of subgrid-scale characteristics. These results are combined with a sensitivity study of parameters used in the radiobrightness model to derive error statistics for the AMSR-E retrievals. In addition, we examine other sources of operational validation errors, such as, a) the errors associated with using limited gravimetric soil moisture data or point-scale measurements of soil moisture from network stations to estimate footprint-scale mean soil moisture, b) the errors associated with asynchronous sampling times, and c) the relationship between surface moisture (~1 cm) and profile moisture. These analyses are necessary to characterize the accuracy of the AMSR data products at EASE-grid scale. Although AMSR-E C band brightness temperatures are contaminated with radio frequency interference over the continental U.S., H/RM-estimated C and X band brightness temperatures are examined comparatively to reevaluate the value of C band retrievals elsewhere.
H33C-04 14:15h
Impedance probe calibration and large scale soil moisture estimation during the SMEX experiments
Large-scale soil moisture estimates are important for hydrologic modeling and agricultural remote sensing applications. For soil moisture monitoring, gravimetric soil moisture sampling is reliable; however, it requires a significant investment to gather and process samples. Portable impedance probes serve as a valuable alternative to destructive gravimetric sampling. These probes measure the dielectric properties of the soil-water-air mixture from which the volumetric soil moisture can be inferred. As part of recent large-scale experiments in the summers of 2002, 2003, and 2004, three different methods for calibrating impedance probes were investigated with the support of coincident gravimetric samples. Field specific calibration improved the accuracy of the probe from greater than ± 5% volumetric soil moisture to less than ± 4%. In addition, a significant amount of bias was eliminated, sometimes greater than 8% in an individual field of study. It was also concluded field specific calibration removes a bias due to bulk density variations. Based upon these results it was determined that the generalized calibration is adequate for estimation of diverse conditions when considering large-scale phenomenon. For studies with more stringent accuracy requirements, however, field specific calibrations is necessary because of the reduction in bias and error.
H33C-05 INVITED 14:30h
Evaluating MODIS Vegetation Indices as Ancillary Data in the Retrieval of Soil Moisture from Microwave Data
One approach to soil moisture retrieval from remotely sensed microwave data uses single frequency H polarization brightness temperature measurements. This algorithm requires ancillary information to estimate the effective temperature of the surface and the attenuation of the microwave signal by vegetation. When applied on a global basis using spaceborne microwave observations, such as AMSR-E, it is most efficient if the ancillary vegetation information is also based on satellite observations. At the present time, the best source of information on the spatial and temporal variations of vegetation biophysical properties is the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites. The MODIS land discipline group provides two types of vegetation indices (VI), the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). The first index normalizes the difference between the near infrared and red bands by their sum that cancels out a large proportion of signal variations attributed to calibration, noise and changing irradiance and atmospheric conditions. However, the NDVI can quickly saturate at high leaf biomass and is influenced by the properties of the soil background under sparse vegetation. The second index (EVI) was developed to optimize the vegetation signal while minimizing aerosol and canopy soil background sources of uncertainty. It is the vegetation water content (VWC) of the canopy that attenuates the microwave signal. Therefore, it is necessary to establish a relationship between the VIs and VWC. In limited tests, using AMSR-E 10 GHz H polarization data and one of the MODIS VIs (either NDVI or EVI) to estimate vegetation effect, the soil moisture retrieval results were mixed. Therefore, more specific studies were conducted to understand how NDVI or EVI are related to VWC under different vegetation biophysical conditions and to define the best choice of the VI for certain conditions. In this study, data collected for SMEX02 in Iowa, SMEX03 in Oklahoma, and SMEX04 in Arizona, representing densely, moderately and sparsely vegetated surface, will be used to evaluate MODIS VIs for their appropriateness in soil moisture retrieval from AMSR-E data.
H33C-06 14:45h
Incorporation of Soil Moisture into Real-Time Hydrologic Simulation
Soil moisture data collected from an in situ network and from satellite measurements were used to enhance estimates of streamflow for the Suwannee River Basin in the Southeastern U.S. Coastal Plain. Soil Moisture data collected from the AMSR-E instrument as well as the in situ data were used. The Soil Water Assessment Tool (SWAT) was used for the hydrologic simulations. Simulated stream-flow characteristics were compared to observed data from the Basin. Simulations using the observed soil moisture data were compared to those obtained without the soil moisture observations. Improvements obtained through incorporation of the observed soil moisture, based upon peak flow and volume estimates, were quantified. If successful, the real time estimates will be used to improve drought, flood, and agronomic production forecasts.
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