An Approach to Lineament Analysis for Groundwater Exploration in Nicaragua
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An Approach to Lineament Analysis for Groundwater Exploration in Nicaragua Jill N. Bruning, John S. Gierke, and Ann L. Maclean Abstract 2004; Hung et al., 2005; Murphy and Burgess, 2005; Wells in bedrock aquifers tend to yield more water where Khan and Glenn, 2006; Meijerink et al., 2007). There is no they intersect fracture networks. Lineament analysis using well-accepted or proven protocol for mapping lineaments, nor satellite imagery was employed to identify surface expres- have different approaches been compared in non-ideal sions of subsurface fracturing for possible new well loca- regions. The technical aim of this work brings together tions. An imagery integration approach was developed to different data-processing tools, such as ERDAS Imagine® and evaluate satellite imagery for lineament analysis in terrain ArcMAP®, in conjunction with a variety of satellite images where the influences of human development and vegetation (QuickBird, Landsat-7 ETMϩ, ASTER, and RADARSAT-1), field confound lineament interpretation. Four satellite sensors observations, geological and topographic maps, and a DEM in (ASTER, Landsat-7 ETMϩ, QuickBird, RADARSAT-1) and a DEM order to compare lineament interpretations derived from were used for lineament mapping a volcanic region of multiple sources in a rural municipality location in Nicaragua. Image processing and interpretations obtained 12 Nicaragua. complementary products, which were synthesized into a raster image of lineament-zone coincidence for creating a Previous Work lineament delineation map. Nine of the 11 previously Lineament identification was first performed with aerial mapped faults were identified from the coincidence-based photography and first generation satellite imagery using map along with 26 new lineaments. The locations of ten stereo pairs, light tables, and transparencies (Gupta, 2003). new lineaments were confirmed by field observation. Optical sensors of moderate spatial resolutions have only RADARSAT-1 products were best for minimizing anthro- recently been used extensively for lineament analysis pogenic features but not able to identify all the geological (Loizzo et al., 1994; Drury and Andrews, 2002; Lee and lineaments. Moon 2002; Ricchetti, 2002; Inzana et al., 2003; Hung et al., 2005; Ricchetti and Palombella, 2005; Arellano-Baezo et al., 2006; Khan and Glenn, 2006, Meijerink et al., 2007; Sander, Introduction 2007; Mutiti et al., 2010). Certain bands of ASTER and Lineament analysis in hard-rock terrains has been performed Landsat were specifically designed to detect geological widely as a means for groundwater exploration. Using structure (Drury and Andrews, 2002). Khan and Glenn satellite imagery, lineaments are detected by surface feature (2006) mapped a remote area of northern Pakistan using patterns such as vegetation, drainage, outcrop truncations, ASTER imagery and discovered two active strike-slip faults soil moisture, and topography. Such lineaments are indica- previously unmapped. tive of secondary porosity in the form of fractures, and if A few studies have employed imagery from multiple intersected by a well have the potential to supply large and sensors for lineament detection (Akman and Tüfeçi, 2004; reliable quantities of water (Mabee et al., 1994; Kresic, 1995; Hung et al., 2005; Murphy and Burgess, 2005). Hung et al. Sander et al., 1997; Edet et al., 1998; Magowe and Carr, (2005) compared lineament interpretations from Landsat-7 1999; Mabee, 1999; Park et al., 2000). ETMϩ and ASTER imagery and observed fewer erroneous A variety of lineament analysis techniques using results from ASTER derived lineaments compared with remotely sensed data exist and have been developed in near Landsat-7 ETMϩ derived lineaments. They attributed the ideal settings where influences of anthropology and climatic difference to the higher spatial resolution of ASTER data. situations are minimal and vegetation, if any, is in a natural Satellite imagery with finer spatial resolution has not been state (Boeckh, 1992; Krishnamurthy, 1992; Mabee et al., 1994; commonly employed in lineament studies for groundwater Henderson et al., 1996; Mahmood, 1996; Edet et al. 1998; exploration primarily due to cost and limited spectral resolu- Mabee, 1999; Magowe and Carr, 1999; Robinson et al., 1999; tion (Sander, 2007). However, water-resource studies have Abouma-Simba, 2003; Paganelli et al., 2003; Glenn and Carr, used high spatial resolution sensors such as QuickBird and Ikonos to monitor land-use and land-cover Sawaya et al. (2003). Although shadows from tall objects affected classifica- tion results, these types imagery have great potential for water studies at local scales (Sawaya et al., 2003). This was further Jill N. Bruning is a Consultant, Chester, VT 05143. demonstrated by Loveless et al. (2005) who utilized Ikonos John S. Gierke is with the Department of Geological and Mining Engineering and Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931 Photogrammetric Engineering & Remote Sensing ([email protected]). Vol. 77, No. 5, May 2011, pp. 509–519. Ann L. Maclean is with the School of Forestry and 0099-1112/11/7705–0509/$3.00/0 Environmental Sciences, Michigan Technological University, © 2011 American Society for Photogrammetry 1400 Townsend Drive, Houghton, MI 49931. and Remote Sensing PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING May 2011 509 data to map surface expressions of geological “cracks” associ- provide structural information for geological mapping in ated with the tectonic setting in coastal Chile. These cracks northern Alberta, Canada. Lineament interpretations were range in aperture from a few centimeters to 2.5 m and were calibrated using several detailed, reputable structural studies. easily observable due to the hyper-arid climate of the region Their study showed principal components 2 and 3 preserved and the sensor’s 1 m spatial resolution (Loveless et al., 2005). topographic information, such as pattern and texture, A variety of image processing techniques have been necessary to interpret bedrock structures. RADARSAT has also utilized to enhance linear features in optical imagery been used to delineate geomorphic features using change (Krishnamurthy et al., 1992; Ricchetti and Palombella, 2005; detection between two scenes acquired at different times of Khan and Glenn, 2006). Khan and Glenn (2006) employed the year (Radarsat Geology Handbook, 1996; Glenn and Carr, decorrelation stretches and principal components analysis 2004) due to differences in surface moisture. High reflectivity (PCA) to aid in geological mapping. Offsets of rock types values in radar imagery can be caused by increased moisture were apparent using these techniques as they exploit the content in both soils and vegetation and have been shown to unique spectral signatures of each lithological formation. enhance linear topographic features (Glenn and Carr, 2003). Krishnamurthy et al. (1992) explored a variety of digital DEMs have also been shown to be useful for detecting image processing techniques for groundwater investigations lineaments because they can eliminate bias caused by using a Landsat TM image of Karnataka, India. Their research inherent east-west sun illumination (Henderson et al., 1996; resulted in 13 output products, which were assessed to Yun and Moon, 2001). Studies that detect lineaments solely delineating geologic and geomorphic features. A qualitative from DEMs rely on the assumption that the majority of assessment of the maps was made and the images were lineaments in a given study area are geomorphic rather than ranked as good, moderate, or poor. tonal and this assumption is valid for most regions as valley Active radar sensors, such as RADARSAT-1 and JERS-1 SAR, and cliff orientations are typically controlled by faulting employ longer wave lengths and complement optical sensors direction (Yun and Moon, 2001). for lineament detection. Radar sensors respond to surface topography, roughness, and dielectric properties; optical sensors respond to optical and thermal attributes Study Area (Mahmood, 1996; Radarsat Geology Handbook, 1996). Thus, This research was conducted in and around Boaco, radar images contain less anthropogenic and vegetation Nicaragua, a rural municipality in need of additional information and exhibit more topographic information drinking water wells located in the interior highlands, (Mahmood, 1996). roughly 100 km northeast of Managua (Figure 1). Nicaragua’s Radar has also proven to be advantageous for mapping population is highly dependent upon groundwater resources in vegetated regions (Paradella et al. 1998, Abouma-Simba with 95 percent of people relying on groundwater (Bund- et al., 2003). Natural variations in vegetation cover are often schuh and Alvarado, 2007). Nicaragua’s groundwater closely linked to geology and are sometimes detectable using dependency is significantly higher than the rest of the RADARSAT-1/Landsat TM integrated products (Paradella et al., world, where only about 30 percent to 50 percent of the 1998) due to the differences in incidence angles of the two global population relies on groundwater (Bundschuh and types of imagery. Paradella et al. (1998) produced a geologi- Alvarado, 2007). Groundwater resources of Nicaragua are cal map of their study area from RADARSAT-1/Landsat TM naturally high quality and are reliable throughout the year imagery and mapped five geological units and two primary (Bundschuh and Alvarado, 2007). Conversely, surface waters lineament systems. Digital image processing