Showing papers by "Brian Brisco published in 2011"

Evaluation of C-band polarization diversity and polarimetry for wetland mapping

Abstract: Wetlands provide important ecological benefits at both local and regional scales, thus wetland conservation and effective management are goals at many levels of government. Radar systems are a useful data source for providing information about wetlands and thus play a complementary role to optical data in wetland mapping and monitoring applications. This paper explores the use of polarization diversity and polarimetry for wetland classification and mapping using airborne CV-580 C-band synthetic aperture radar (SAR) data. The results show that dual polarization with an HH polarized component is superior to single polarization but does not contain as much information for wetland classification as full polarimetry. However, polarization ratios using HH are adequate for mapping water and flooded and nonflooded vegetation for a generalized land-cover map. The implications of this research are discussed with respect to wetland classification and land cover information needs for waterfowl-productivity estimates ...

Crop-type identification potential of Radarsat-2 and MODIS images for the Canadian prairies

Abstract: Owing to their high-frequency revisit and weather independence with high image resolution, Moderate Resolution Imaging Spectroradiometer (MODIS) and Radarsat-2 SAR (ScanSAR (synthetic aperture radar)), respectively, provide data suitable for regional-level crop-type identification in the Canadian prairies. The challenge remains in optimally combining data from the two sources, to identify crop types in individual fields. This study investigated an approach based on image fusion and a specially designed classification to obtain a result with the high spatial detail of ScanSAR and the spectral information from MODIS. The methodology employs a wavelet-IHS (intensity, hue, and saturation) combined image fusion method to enhance the spatial resolution of the MODIS data using ScanSAR data, followed by a multiresolution segmentation process supported by a road network database to generate the final classification. The fusion-classification approach yielded a result suitable for both visual and digital analysis. ...

Use of Radarsat-2 ultra-fine images in horticulture–intensive farming: land use detection and crop discrimination

Abstract: Horticulture is the study of herbaceous plants destined for human consumption that can be consumed with or without industrial processes. Because of the growing pattern of horticulture crops, remote sensing is a useful tool to monitor their seasonal production. The use of all-weather synthetic aperture radar (SAR) images allows global monitoring of these crops. Radar high-resolution satellite imagery is preferred because it is less expensive and more convenient than airborne imagery. The new Radarsat-2 platform with an ultra-fine beam 3 m resolution mode offers new possibilities in land use detection and land cover crop discrimination for plots of one acre or less. This study reviews the use of Radarsat-2 images and compares ultra-fine beam and quad-polarized Radarsat-2 imagery to evaluate the effectiveness of the ultra-fine mode versus the quad-polarized mode for small-plot crop discrimination.