02267naa a2200253 a 450000100080000000500110000800800410001902200140006010000170007424501040009126000090019552015870020465000130179165000130180465300160181765300170183365300200185065300190187065300150188970000140190470000170191870000180193577300600195319909162015-02-11       2014    bl uuuu     u00u1 u    #d  a0034-42571 aEVANS, T. L.  aLarge-scale habitat mapping of the Brazilian Pantanal wetlandbA synthetic aperture radar approach.  c2014  aThis study uses 50 m spatial resolution, dual-season, HH and HV L-band ALOS/PALSAR, and HH and HV C-band RADARSAT-2 data, as well as a comprehensive set of ground reference points, to map the diverse habitats of the hydrologically variant subregions of the Pantanal by using a hierarchical object based image analysis approach. First, mean and standard deviation values of image object training sites were evaluated, and used as the basis for forming preliminary land cover class thresholds for each subregion. Then, acombination of additional refined thresholds, hierarchical rules, and a supervised nearest neighbor algorithm (eCognition Feature Space Optimization) employing several features as primary inputs (mean, standard deviation, seasonal change detection, brightness, maximum difference, area, roundness, brightness, compactness, shape index, and length/ width)wasutilized,resultinginthede finitionandclassificationoftenhabitatclasses:Forest/Woodland,Riparian Forest, Open Wood Savanna, Open Wood Savanna subject to prolonged flooding, Open Grass Savanna, Agriculture, Swampy Grassland, Swampy Mixed Savanna, Vazantes, and Water. This classification was achieved with an overall accuracy of 80% for the entire Pantanal. The produced habitat spatial distribution maps will provide vital information for determining refuge zones for terrestrial species, and connectivity of aquatic habitats during the dry season, as well as providing crucial baseline data to aid in monitoring changes in the region, and to help de fine conservation strategies for habitat in this wetland.  aPantanal  awetlands  aALOS/PALSAR  aENVISAT/ASAR  aHabitat mapping  aK&C Initiative  aRADARSAT-21 aCOSTA, M.1 aTOMAS, W. M.1 aCAMILO, A. R.  tRemote Sensing of Environmentgv. 155, p. 89-108, 2014.