2012 AGU Chapman Conference on Remote Sensing of the ...

land subsidence monitoring, DEM generation, andearthquake impact assessment. Recent research hasdemonstrated the potential to apply this technique to waterlevel estimation in wetlands with suitable vegetation andhydrologic characteristics. This is particularly true forwetlands with stable double bounce scattering from areas offlooded vegetation. This presentation will review the wetlandand hydrologic characteristics that lead to suitablecoherence from Lake Clear watershed which is a mixed forestsite in Ontario and the Everglades National Park in Florida.The approach will be demonstrated with a number ofexamples using RADARSAT and Terra-SAR data from boththese sites for a variety of wetland types including mangrovemarshes, cattail and bulrush marshes, as well as saw-grassand mixed forest swamps. The processing methodology toproduce the coherence and the interferograms will beoutlined as well as the wetland characteristics resulting inhigh coherence for the two study sites. On-going researchactivities which are working towards bringing this approachto an operational status will be described including the useof in-situ corner reflectors for phase calibration.Brisco, BrianMapping Surface Water and Flooded Vegetationusing SAR Remote Sensing for Critical Ecosystemsin North AmericaKaya, Shannon 1 ; Brisco, Brian 1 ; White, Lori 1 ; Gallant, Alisa 2 ;Sadinski, Walt 3 ; Thompson, Dean 41. Natural Resources Canada, Canada Centre for RemoteSensing, Ottawa, ON, Canada2. United States Geological Survey, Earth ResourcesObservation and Science (EROS) Center, Sioux Falls, SD,USA3. United States Geological Survey, Upper MidwestEnvironmental Sciences Center, La Crosse, WI, USA4. Natural Resources Canada, Canadian Forest Service,Sault St. Marie, ON, CanadaSurface water constitutes a considerable proportion offreshwater sources in North America. Global change,however, is resulting in modifications to hydrologic systemswhich are impacting the landscape characteristics of wetlandecosystems on both an inter-seasonal and annual basis. Thedeterioration of water quality, overexploitation of freshwaterresources, hydrological hazards and adverse effects oflandscape degradation have an effect on the functioning ofcritical ecosystems and their suitability as cohesivelandscapes for several species at risk. The Terrestrial WetlandGlobal Change Research Network (TWGCRN), led by theUnited States Geological Survey, is studying landscaperesponses to climate/global change across a vital portion ofNorth America in the United States and Canada using anintegrated approach which includes the use of multiplesources of geospatial information to understand thedynamic conditions at specific network study sites.Assessments of landscape conditions are being conducted ona range of variables measured in situ and via airborne andspace-borne sensors, including SAR systems. Over the past 3seasons (2009, 2010, 2011), the Canada Centre for RemoteSensing has collected a comprehensive set of RADARSAT-2data over key TWGCRN study sites in Canada and theUnited States. For each site, RADARSAT-2 Fine Quad-Polmode multi-temporal data were acquired to satisfy the needfor identifying surface water extent and temporal/seasonalchange, as well as flooded vegetation extent and changeassociated with wetland landscape features. Semi-automatedmodels were developed to extract surface water informationfor each acquisition using a magnitude thresholdingapproach. The single-look complex polarimetric data wassubsequently processed using the Freeman-Durdendecomposition algorithm to identify areas associated withthe double bounce scattering mechanism. The modelsdeveloped, validated, and explained in this paper show greatpromise towards operational characterization of bothsurface water and flooded vegetation changes over time, asassociated with critical wetland areas. Results to date showthat SAR remote sensing can help provide a betterunderstanding of surface water extent and temporal change.Derived products will serve as important inputs tounderstanding hydrological dynamics within criticalecosystems.Brubaker, Kristen M.Multi-scale lidar greatly improve characterizationof forested headwater streams in centralPennsylvaniaBrubaker, Kristen M. 1, 2 ; Boyer, Elizabeth 21. Center for Sustainability Education, Dickinson College,Carlisle, PA, USA2. School of Forest Resources, The Pennsylvania StateUniversity, University Park, PA, USAMost current hydrographic data used in GeographicInformation Systems (GIS) have been derived by digitizingblue line streams from USGS topographic maps or bymodeling streams using traditional digital elevations models(DEMs) in GIS. Both methods produce stream models thatlack detail and accuracy, particularly in headwater streams.In addition to channel network delineation, anotherhydrologic attribute that is of interest to hydrologists,modelers, and ecologists, is topographic index (TI) asmeasured by the formula ln(a/tan). This metric and itsdistribution is an important component to the hydrologicmodel TOPMODEL and other hydrologic models, but is alsoused extensively to represent soil moisture in fields ofecology, forestry, and soil science. Newly available lidar dataavailable statewide in Pennsylvania can produce DEMs withan accuracy and resolution that far exceed previouslyavailable elevation data. In this study, streams were modeledusing lidar-derived DEMs of 1 m, 3 m, and 10 m resolutionsusing existing GIS software programs and compared to bothactual streams and streams modeled using a 10 meterNational Elevation Dataset (NED) DEM. Results showedthat the most accurate stream locations could be modeledusing a lidar-derived DEM thinned to 3m resolution orsmoothed using a mean smoothing filter. Also, when a 10 m43