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Wetlands cover less than 5% of Earth's ice-free land surface but exert major impacts on global biogeochemistry, hydrology, and biological diversity. The extent and seasonal, interannual, and decadal variation of inundated wetland area play key roles in ecosystem dynamics. Despite the importance of these environments in the global cycling of carbon and water, there is a scarcity of suitable regional-to-global remote-sensing data for characterizing their distribution and dynamics. Through a current NASA MEaSUREs project, we are assembling a global-scale Earth System Data Record of natural Inundated Wetlands (ESDR-IW) to facilitate investigations on their role in climate, biogeochemistry, hydrology, and biodiversity (McDonald, PI; Chapman, Hess, Kimball, Moghaddam, Co-Is). The ESDR comprises (1) Fine-resolution (100 meter) maps, delineating wetland extent, vegetation type, and seasonal inundation dynamics for regional to continental-scale areas covering crucial wetland regions, and (2) global multi-temporal 25 km mappings of inundated area fraction (Fw) across multiple years. The fine-scale ESDR component is constructed from synthetic aperture radar (SAR) data from JAXA's JERS satellite and from their Phased Array L-Band SAR (PALSAR) on-board the Advanced Land Observing Satellite (ALOS). The global maps of inundated area fraction are derived at 25 km scale from remote sensing observations from active/passive microwave instruments. We have identified key issues which contribute to uncertainty in the ESDR data sets. Error sources include radiometric inconsistency of the remote sensing data sources, paucity of ground validation datasets available for implementation of classification algorithms, temporal undersampling relative to hydrologic variability, and ambiguities associated with implementation of coarse-resolution mixture models. We propose to conduct systematic analysis of error sources related to all aspects of ESDR-IW assembly, including uncertainties associated with remote sensing and ground training and validation data sets employed, algorithms applied, and cross-product harmonization. To accomplish this, we will (1)Estimate error sources associated with derivation of SAR-based wetlands maps, analyzing uncertainty associated with JERS and PALSAR radiometric attributes, data set compositing times, training data used in implementing retrieval algorithms, accuracy of retrieval algorithms, and application of those algorithms across broad landscape regions where ground-based measurements are not available for training and validation.(2)Assess error sources associated with generation of the 25 km global inundation data sets, analyzing uncertainties associated with the multi-platform remote sensing time series that support generation of the long-term global data record, with the temporal compositing employed in generating the time series data record, with calculation of Fw through mixture model and radiometric retrievals, and with atmospheric effects and radio frequency interference.(3)Employ the single normal equation simulation (SNESIM), a state-of-the-art geostatistical method for sub-pixel mapping, to quantify in a spatially explicit manner the uncertainty in our global coarse-resolution inundation area fraction retrievals. (4)Evaluate consistency of our products with similar global products over globally representative locations and periods. This work will create an enhanced ESDR of inundated wetlands with statistically robust uncertainty estimates. The ESDR documentation will include a detailed breakdown of error sources and associated uncertainties within the data record. This effort will ensure that the ESDR-IW inundation products will be the best available data sets for global-scale modeling that involves a surface water component. The ESDR data sets will also benefit preparation for NASA Decadal Survey missions including Soil Moisture Active-Passive (SMAP) and Surface Water Ocean Topography (SWOT).

Project PI: Kyle McDonald/Jet Propulsion Laboratory

Jet Propulsion Laboratory M/S 300-233 4800 Oak Grove Drive Pasadena, CA 91109

Phone: (818) 354-3263

Fax: (818) 354-9476

Email: Kyle.C.Mcdonald@jpl.nasa.gov

http://science.jpl.nasa.gov/people/McDonald/

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Started: Apr 01, 2011

Last Activity: Apr 01, 2011

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