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Title:   Author  item
                                            Jackson, Thomasitem
                                            Cosh, Michaelitem
                                            BINDLISH, R - Science Systems, Incitem
                                            YUEH, S - Jet Propulsion Laboratoryitem
                                            DINARDO, S - Jet Propulsion Laboratoryitem
                                            O'NEILL, P - National Aeronautics And Space Administration (NASA)
  Submitted to: Meeting Abstract
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 9/5/2009
                                    Publication  Date: 11/9/2009
                                    Citation: Jackson, T.J., Cosh, M.H., Bindlish, R., Yueh, S., Dinardo, S., O'Neill, P. 2009. Soil Moisture Active Passive Validation Experiment 2008 [abstract]. The 3rd Annual Advanced Land Observing Satellite Joint Principal Investigators Symposium. 2009 CDROM.Interpretive Summary:
                                Technical Abstract: Soil Moisture Active Passive Validation Experiment 2008 (SMAPVEX08) was conducted to address specific issues identified by the SMAP satellite mission (launch 2013). SMAP is currently addressing issues related to the development and selection of retrieval algorithms as well as refining the mission design and instruments. Some of these require resolution as soon as possible. Several forums had identified specific questions that required supporting field experiments. Experiments incorporated into SMAPVEX08 included evaluation of how well new alternative radio frequency interference (RFI) suppression techniques under consideration for SMAP work over RFI contaminated land areas, providing more robust sets of concurrent passive and active L-band observational data including temporal change for algorithm development and validation, evaluating the impact of azimuthal orientation on alternative radar retrieval algorithms, understanding the scaling of high resolution synthetic aperture radar (SAR) to lower resolution radar data of SMAP, and a more thorough evaluation of less studied land covers such as urban and forest. A series of aircraft-based flights was conducted on the Eastern Shore of Maryland and Delaware in the fall of 2008. The study site selected consisted of a mix of mostly senescent/harvested crops and mostly deciduous forest. Two aircraft (a Twin Otter and a P-3B) carrying prototypes of the SMAP instrumentation (combined active and passive microwave) were flown concurrent with ground sampling. A ground based active-passive instrument (ComRad) was also deployed for the campaign. The Twin Otter supported the Passive Active L-Band System (PALS) instrument that provides fully polarimetric radar/radiometer data for a single fixed incidence angle footprint (40 degrees backward looking). For most of the flights the ground resolution of the sensor was 1000 m. It is well known that high resolution SAR is highly responsive to surface structural features, in addition to soil moisture. The variations of these parameters in most landscapes has made it difficult to develop robust soil moisture retrieval methods. On the other hand, lower resolution radar data exhibits more synoptic patterns. The ALOS PALSAR can be a valuable resource in pre-launch SMAP research and post launch validation. Understanding how to scale PALSAR to SMAP is critical to its exploitation. Data acquisitions with the ALOS PALSAR were requested to cover the entire growing season and to include concurrent coverage during the aircraft campaign. SMAPVEX08 began following an extended rainfall event that was followed a few days later by another large event. Following this there was no rainfall, however, cloud cover and cool temperatures resulted in a relatively slow but consistent drydown. A series of seven aircraft flights was conducted over ten days that tracked this drying. A review of the preliminary radiometer data from PALS reflected the geophysical features and meteorological trends. The resulting data set will be a valuable addition to the few active-passive data sets that exist.


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