| This study identified lineaments from satellite images and Digital Elevation Models (DEMs) utilizing image processing techniques that enhance variations in spectral and spatial reflectivity and topography. In flat-lying sedimentary sequences Lineaments are commonly surface expressions of tectonic fractures and faults in the bedrock, emphasized on the surface by topography, drainage, and vegetation - many can be identified by remotely sensed data. Knowledge of fault locations can prevent unsuitable site selection for CO2 sequestration where CO2 could migrate up fault systems. Lineament patterns also give insight into the fracture fabric of the region- an important consideration for CO2 sequestration. Various data sets, including multispectral satellite imagery (Landsat and ASTER) and DEMs, as well as geological data describing fractures, faults, and hydrology, were used to map and validate the lineament distribution in the study area. Linear features were enhanced with tonal, topographic and textural changes by digital image processing of the satellite imagery and DEMs. Lineaments were then extracted manually using ArcMap (ArcGIS 9.2 -- ESRI). Lineaments longer than 1 km were identified, digitized and stored in a geo-database together with attributes describing their length, orientation and other characteristics. Lineament categories included vegetation, drainage, and topography. Rose diagrams and statistics of length and number of lineaments in each 100 orientation bin were used to characterize the lineament distribution in each remotely sensed data set. The primary lineament orientations from both ASTER imagery and topography trended northeast and northwest in the study area of central New York State. These trends agreed with some of the EarthSat (1997) lineament sets from Landsat images and also corresponded to some published fracture and fault systems but do not reflect the most abundant sets. |
