IEEE Transactions on Geoscience and Remote Sensing · 1987 · 86 citations · 13 references
Natural SciencesForestryGeoinformaticsForest BiometricsForest ManagementRemote SensingLand Cover MappingRadar Signal ProcessingRemote Sensing ImageryVegetation Cover AssessmentVegetation IndicesVegetation MonitoringCross-polarizationFeature DelineationMedian FilteringPolarizationSpeckle Noise ReductionSurface FeaturesSynthetic Aperture RadarSynthetic Aperture Radar Imaging
This paper presents the utility of multipolarization Synthetic Aperture Radar (SAR) data for surface feature delineation and forest vegetation characterization. Three channels of ratioed data (VV/HH, VH/HH, and VH/VV) are generated from the HH, VV, and VH polarization data (V = vertical, H = horizontal). The ratioed data are linearly stretched to yield a digital number within a range of 0 to 255. The techniques for reducing SAR speckle noise and for measuring the degree of separation are discussed. For surface feature delineation, the results indicate that cross polarization as well as cross polarization ratioed data better delineate those surface features that are difficult to separate by like polarization data. The results suggest using a median value filtering technique to reduce within-plot data fluctuation to increase the separability measure. For forest vegetation characterization, the results indicate that multipolarization SAR data may be used to estimate forest properties such as total-tree biomass, basal area, and tree height.
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