Remote Sensing
mohammad sharifikia; jalal karami; Ehsan Falahati
Abstract
Optical Remote Sensing is a low-cost and efficient method to alteration zone detection. However in the area that have been covered by vegetation or alluvial, the identification of these areas is not very accurate with optical images. In this study fusion and integrating of ALOS-PALSAR L-band and ASTER ...
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Optical Remote Sensing is a low-cost and efficient method to alteration zone detection. However in the area that have been covered by vegetation or alluvial, the identification of these areas is not very accurate with optical images. In this study fusion and integrating of ALOS-PALSAR L-band and ASTER data by HSV, HSL, Maximum Likelihood and Artificial Neural Network has been done to discover and enhance the Argilic and Propylitic Alteration zones over the west part of Qazvin province in IRAN. For this purpose, Argilic and Propylitic alterations were primary identified unseeing ASTER image. Then based on geological data and field study, some areas with alterations covered by quaternary sediments, not detectable by ASTER images, were identified. In the following, the integration of the ALOS PALSAR L-band data and the ASTER SWIR bands with HSV, HLS, Maximum Likelihood and Artificial Neural Network were performed. The results of this study showed that the radar and optics data fusion, using HSV and HLS methods, increases the enhancement of visible argillic alteration zones in the study area. Also, the integration of radar and optics data with the Maximum Likelihood and the Artificial Neural Network methods,
M. Dehghani; M. J. Valadan Zouj; A. Mansourian
Abstract
study several 2D and 3D math models have been tested in order to correct slant range SAR data geometrically. Some of these models consider the imaging geometry at the time of imaging while the others relate the ground space to the image one by mathematical polynomials. The images used here are 3 ENVISAT ...
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study several 2D and 3D math models have been tested in order to correct slant range SAR data geometrically. Some of these models consider the imaging geometry at the time of imaging while the others relate the ground space to the image one by mathematical polynomials. The images used here are 3 ENVISAT ones of Bam area. In order to extract the 3D GCPs, a topographic map with a scale of 1:25000 and SRTM DEM were used. The 2D math models used in this study include Global polynomial, Point wise, Piece wise and Projective while the 3D models are DLT and Rigorous SAR model. Since the images used in this study were originally ordered for interferometry studies, their baseline is so small that the precision of 3D coordinates extraction is not satisfactory enough. However, the results of 2D models are much better.
