Digitizing road maps manually is an expensive and time-consuming task. Several methods that intend to develop fully or semi-automated systems have been proposed. In this work we introduce a method, based on the Radon ...Digitizing road maps manually is an expensive and time-consuming task. Several methods that intend to develop fully or semi-automated systems have been proposed. In this work we introduce a method, based on the Radon transform and optimal algorithms, which extracts automatically roads on images of rural areas, images that were acquired by digital cameras and airborne laser scanners. The proposed method detects linear segments iteratively and starting from this it generates the centerlines of the roads. The method is based on an objective function which depends on three parameters related to the correlation between the cross-sections, spectral similarity and directions of the segments. Different tests were performed using aerial photos, Ikonos images and laser scanner data of an area located in the state of Parana (Brazil) and their results are presented and discussed. The quality of the detection of the roads centerlines was computed using several indexes - completeness, correctness and RMS. The values obtained reveal the good performance of the proposed methodology.展开更多
Volcanic ash cloud has serious impacts on aviation.With volcanic ash dispersion,it also has a profound and long-term impact on climate and the environment.A new volcanic ash cloud detecting method (SWIR-TIR Volcanic A...Volcanic ash cloud has serious impacts on aviation.With volcanic ash dispersion,it also has a profound and long-term impact on climate and the environment.A new volcanic ash cloud detecting method (SWIR-TIR Volcanic Ash method,STVA) is presented that uses satellite images of Medium Resolution Spectral Imager (MERSI) and Visible and Infrared Radiometer (VIRR) on board the second generation Polar-Orbiting meteorological satellite of China (FY-3A).STVA is applied in detecting Iceland's Eyjafjallajokull volcano eruption.Compared with the traditional Split Window Temperature Difference method (SWTD),the results show that STVA is more sensitive to volcanic ash cloud than SWTD and can fairly extract volcanic ash information from the background of meteorological cloud and the ocean.Ash Radiance Index (ARI) and Absorbing Aerosol Index (AAI) derived from Metop-A satellite images are used to validate the performance of STVA.It is shown that STVA provides similar results with ARI and AAI.FY-3A/MERSI,VIRR and Terra /MODIS data are used to test STVA and SWTD.It is demonstrated that STVA derived from FY-3A satellite data is more effective in complicated meteorological conditions.This study shows great potential of using China's own new generation satellite data in future global volcanic ash cloud monitoring operation.展开更多
文摘Digitizing road maps manually is an expensive and time-consuming task. Several methods that intend to develop fully or semi-automated systems have been proposed. In this work we introduce a method, based on the Radon transform and optimal algorithms, which extracts automatically roads on images of rural areas, images that were acquired by digital cameras and airborne laser scanners. The proposed method detects linear segments iteratively and starting from this it generates the centerlines of the roads. The method is based on an objective function which depends on three parameters related to the correlation between the cross-sections, spectral similarity and directions of the segments. Different tests were performed using aerial photos, Ikonos images and laser scanner data of an area located in the state of Parana (Brazil) and their results are presented and discussed. The quality of the detection of the roads centerlines was computed using several indexes - completeness, correctness and RMS. The values obtained reveal the good performance of the proposed methodology.
基金supported by National Basic Research Program of China (Grant No. 2010CB950700)
文摘Volcanic ash cloud has serious impacts on aviation.With volcanic ash dispersion,it also has a profound and long-term impact on climate and the environment.A new volcanic ash cloud detecting method (SWIR-TIR Volcanic Ash method,STVA) is presented that uses satellite images of Medium Resolution Spectral Imager (MERSI) and Visible and Infrared Radiometer (VIRR) on board the second generation Polar-Orbiting meteorological satellite of China (FY-3A).STVA is applied in detecting Iceland's Eyjafjallajokull volcano eruption.Compared with the traditional Split Window Temperature Difference method (SWTD),the results show that STVA is more sensitive to volcanic ash cloud than SWTD and can fairly extract volcanic ash information from the background of meteorological cloud and the ocean.Ash Radiance Index (ARI) and Absorbing Aerosol Index (AAI) derived from Metop-A satellite images are used to validate the performance of STVA.It is shown that STVA provides similar results with ARI and AAI.FY-3A/MERSI,VIRR and Terra /MODIS data are used to test STVA and SWTD.It is demonstrated that STVA derived from FY-3A satellite data is more effective in complicated meteorological conditions.This study shows great potential of using China's own new generation satellite data in future global volcanic ash cloud monitoring operation.