Multitemporal Radarsat-2 Polarimetric Sar Data for Urban Land-cover Mapping
نویسنده
چکیده
The objective of this research is to evaluate multi-temporal RADARSAT-2 polarimetric SAR data for urban land-cover classification using a novel classification scheme. Six-date RADARSAT-2 Polarimetric SAR data in both ascending and descending orbits were acquired during June to September 2008 in the rural-urban fringe of the Greater Toronto Area. The major land-cover types are builtup areas, roads, golf courses, forest, water and several types of agricultural crops. In this research, the different urban land-cover types and their corresponding polarimetric behaviors were studied. The polarimetric signatures of the various urban land-cover types were extracted from the RADARSAT-2 SAR images and analyzed using a new hierarchical multitemporal classification method. The results showed that the new classification method yielded high classification accuracy, with overall accuracy of 82.1% and Kappa coefficient 0.80 for the major 11 land-cover classes. The classification scheme can effectively extract the urban structures by mapping urban related classes such as streets and major roads with the higher user’s accuracy, which is difficult to achieve using a single-date data.
منابع مشابه
RADARSAT-2 Polarimetric SAR Data for Urban Land Cover Classification: A Multitemporal Dual-Orbit Approach
This research investigates multitemporal dual-orbit RADARSAT-2 polarimetric SAR data for urban land cover classification using an object-based support vector machine (SVM). Sixdate RADARSAT-2 high-resolution SAR data in both ascending and descending orbits were acquired in the rural-urban fringe of the Greater Toronto Area during the summer of 2008. The major landuse/land-cover classes include ...
متن کاملMultitemporal Space- borne Polarimetric SAR Data for Urban Land Cover Mapping
Urban represents one of the most dynamic areas in the global change context. To support rational policies for sustainable urban development, remote sensing technologies such as Synthetic Aperture Radar (SAR) enjoy increasing popularity for collecting up-to-date and reliable information such as urban land cover/land-use. With the launch of advanced spaceborne SAR sensors such as RADARSAT-2, mult...
متن کاملMultitemporal RADARSAT-2 Polarimetric SAR Data for Urban Land Cover Classification Using Support Vector Machine
This research investigates the various RADARSAT-2 polarimetric SAR features for urban land cover classification using object-based method combining with support vector machine (SVM) and ruled-based approach. Six-dates of RADARSAT-2 fine-beam polarimetric SAR data were acquired in the rural-urban fringe of Greater Toronto Area during June to September, 2008. The major landuse/land-cover classes ...
متن کاملUrban Mapping Using Multitemporal Very High Resolution Sar Data by a Knowledge-based Sem Algorithm
The objective of this research is to assess the multitemporal very high resolution single polarization SAR data for urban land cover/land-use mapping using a novel knowledge-based SEM algorithm. Three-date RADARSAT-2 ultra-fine beam SAR data were collected over the rural-urban fringe of Greater Toronto Area. A modified Stochastic Expectation-Maximization (SEM) algorithm which employs an adaptiv...
متن کامل