In recent times remote sensing data have become more and more popular for geomorphological investigations because of their increasing level of detail and wide accessibility. In this context, the present work aims to provide a time-saving and effective method for the detection of meso to macro-scale karst depressions, as well as classification and mapping of karst features in extensive study areas. This semi-automatic approach has recourse to Image Sharpening merging techniques of any software apt to the visualization, analysis, and processing of all types of digital imagery. These tools permit to automatically merge a low-resolution color, multi-, or hyper-spectral image with a high-resolution gray scale image (with resampling to the high-resolution pixel size). Our aim was to improve the spatial resolution of very high resolution color orthophotos with the Landsat 7 ETM+ 2000 imagery, in order to get best enhanced merged aerial imagery for the visual interpretation of karst depressions of Sierra de Líbar study area, in the Betic Ranges. This zone, mostly located in Malaga province (Andalucıa, Southern Spain), is mainly formed of Jurassic dolomites and limestones, and Cretaceous marls and marly limestones. Jurassic rocks form a large anticline, whereas Cretaceous rocks fill the synclines and tectonic grabens. The lithology and geological setting contribute to shape a peculiar landscape characterized by steep slopes and plateau-shaped mountain ridges. Besides, a large variety of well-developed karst landforms, including karrenfields, vertical shafts, cave systems and poljes (developed in the synclines) can be recognized. Performing Principal Component Analysis (PCA) and Brovey Transform as merging techniques we were eventually able to get high spectral and spatial resolution imagery of the study zone. Band ratioing (VNIR B3/B1 and SWIR B5/B4, B5/B7) in the higher resolution imagery was then applied in order to detect, locate and finally mapping karst depressions filled by residual sediments rich in iron oxides and hydroxides.
Detection and mapping of karst depressions through remote sensing approach: an example from Sierra de Libar (Malaga, SW Spain)
SUMA, Andrea;DE COSMO, Pietro Domenico
2010
Abstract
In recent times remote sensing data have become more and more popular for geomorphological investigations because of their increasing level of detail and wide accessibility. In this context, the present work aims to provide a time-saving and effective method for the detection of meso to macro-scale karst depressions, as well as classification and mapping of karst features in extensive study areas. This semi-automatic approach has recourse to Image Sharpening merging techniques of any software apt to the visualization, analysis, and processing of all types of digital imagery. These tools permit to automatically merge a low-resolution color, multi-, or hyper-spectral image with a high-resolution gray scale image (with resampling to the high-resolution pixel size). Our aim was to improve the spatial resolution of very high resolution color orthophotos with the Landsat 7 ETM+ 2000 imagery, in order to get best enhanced merged aerial imagery for the visual interpretation of karst depressions of Sierra de Líbar study area, in the Betic Ranges. This zone, mostly located in Malaga province (Andalucıa, Southern Spain), is mainly formed of Jurassic dolomites and limestones, and Cretaceous marls and marly limestones. Jurassic rocks form a large anticline, whereas Cretaceous rocks fill the synclines and tectonic grabens. The lithology and geological setting contribute to shape a peculiar landscape characterized by steep slopes and plateau-shaped mountain ridges. Besides, a large variety of well-developed karst landforms, including karrenfields, vertical shafts, cave systems and poljes (developed in the synclines) can be recognized. Performing Principal Component Analysis (PCA) and Brovey Transform as merging techniques we were eventually able to get high spectral and spatial resolution imagery of the study zone. Band ratioing (VNIR B3/B1 and SWIR B5/B4, B5/B7) in the higher resolution imagery was then applied in order to detect, locate and finally mapping karst depressions filled by residual sediments rich in iron oxides and hydroxides.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
