IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
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Integrating Gravity Data With Remotely Sensed Data for Structural Investigation of the Aynak-Logar Valley, Eastern Afghanistan, and the Surrounding Area
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Masood Azizi and Hakim Saibi
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Abstract—This study integrates gravity data with interpreted lineaments from remotely sensed images and geological fault in an effort to understand the geological structure of the Aynak-Logar Valley (ALV) and its surrounding area in eastern Afghanistan. Integrated analysis of Landsat Enhanced Thematic Mapper Plus (ETM+), Shuttle Radar Topography Mission (SRTM), and Digital Elevation Model (DEM) data was applied for lithological mapping and extraction of geological lineaments and landforms. Gravity data were used to delineate a detailed picture of the subsurface structure. Several gravity interpretation techniques such as horizontal gradient (HG), tilt derivative (TD), and analytic signal (AS) were applied to the gravity data with the objective of making geological features such as faults and contacts more visible, and also a three-dimensional (3-D) inversion model of gravity data was developed to show the density distributions in the study area. The combination of these geoscience data provides information about the subsurface structure of ALV. The interpreted faults from remote sensing are striking NE-SW. The faults and contacts from geological map and gravity data analysis are striking mainly in NNE-SSW, which is the direction of the Kabul block trending fault structure.
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Index Terms—Afghanistan, analytic signal, aynak-Logar valley, gravity data, horizontal gradient, integration, remote sensing, structure, three-dimensional (3-D) gravity inversion, tilt derivative.
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I. I NTRODUCTION
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the structural features in the study area. Many scientists applied this integration approach, such as: Rabie and Amar [44] in Egypt; Kamel and Elsirafe [23] in Egypt; Lunden et al. [33] in Sweden; Lamontagne et al. [28] in Canada; Chen and Zhou [7] in China; Yassaghi [66] in Iran; Saadi et al. [48], [49] in Libya; and Khamies and El-Tarras [25] in Egypt. In this study, the combination of the three types of data (geology, remote sensing, and geophysics) is processed using geospatial methods in geographic information system (GIS) using ArcGIS Ver. 10, ER Mapper Ver. 7.0, and ENVI Ver. 4.7. The gravity data have been processed using Geosoft Oasis Montaj Ver. 8.1. GIS and remote-sensing-based methods were used to integrate all raster and vector results extracted from different data types. The manual extraction criteria for the lineaments were based on photographic characteristics, including shape and geomorphologic features [31]. The gravity method is a geophysical technique that measures variations in the earth’s gravitational field at specific locations and has many applications in geology [18]. This method depends mainly on the density contrast of the rocks. The gravity method can image subsurface structures and density distributions by applying gravity field interpretation techniques such as horizontal gradient (HG), tilt derivative (TD), and analytic signal (AS) and three-dimensional (3-D) inversion modeling, respectively. The aim of this study is the integration of multiple available geoscientific datasets of ALV to delineate and enhance the subsurface structure of the study area.
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II. G EOGRAPHICAL L OCATION AND G EOLOGICAL S ETTING
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The ALV is situated approximately 30 km south of Kabul, the capital city of Afghanistan (Fig. 1). The study area is rich in many minerals, including copper, cobalt, and chromium. The deposit occurs in the Aynak intermountain depression, which has a diameter of 15–18 km and a mean altitude of 2275–2675 m. The depression is surrounded by mountains up to 3450 m high. The Aynak subarea consists of the Kelaghy-Kakhay, Bakhel-Charwaz, Yugha-Darra, Gul-Darra, and Kharuti Dawrankhel areas.
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HIS STUDY integrates several analyses with image processing to improve the visual interpretation of subsurface structure, discrimination among various lithological units, and the extraction of structural features in the area surrounding the Aynak-Logar Valley (ALV). An integrated analysis of Landsat Enhanced Thematic Mapper Plus (ETM+) and Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) data was applied for lithological mapping and extraction of geological lineaments and landforms. The integration of the remote sensing and geophysical data aids in the detection and geological interpretation of Manuscript received March 26, 2014; revised June 23, 2014; accepted August 07, 2014. The authors are with the Department of Earth Resources Engineering, Faculty of Engineering, Kyushu University, Fukuoka 819-0395, Japan (e-mail:
[email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JSTARS.2014.2347375
1939-1404 © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications standards/publications/rights/index.html for more information.
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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
Fig. 1. (a) Location of the study area in Afghanistan. (b) DEM of the study area from the Shuttle Radar Topographic Mission, including names of various subareas of interest.
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Fig. 2. Geological map of the study area and the locations of geological faults (modified from [1], [14], [62]), overlaid on the SRTM map.
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Regionally, ALV is located in the center of Kabul block, which is an NNE-trending fault-bounded terrane 200 km long × 50 km wide. The oldest rocks exposed in the study area belong to the metavolcanic Welayati Formation, which is composed of gneiss and amphibolites, and are exposed in the core of the anticline. This formation is overlain by the thick metasedimentary sequence of the Loy Khwar Formation, which is a cyclical sequence of dolomite marble, carbonaceous quartz schist, and quartz-biotite-dolomite schist, and hosts the copper mineralization. The Loy Khwar Formation is post-dated by basaltic to dacitic metavolcanic rocks of the Gulkhamid Formation, which are also of Vendian–Cambrian age. Ages of metavolcanic and metasedimentary rocks in the ALV area are early to late Proterozoic and the sedimentary rocks in the area are Paleozoic, Triassic, Paleocene, Quaternary, and Recent age [1], [14]. The Logar Valley area contains large
bodies of ultramafic rock of Eocene age. The far western part of the study area, a region of early to middle Proterozoic rock, contains the Paghman metasedimentary and intrusive terrane, which is another highly faulted crustal block containing Proterozoic and Paleozoic rocks [6], [64]. The geology of Aynak subarea (Fig. 2) shows nonintrusive rocks with ages of Proterozoic, Cambrian, Late Permian, Pliocene, and Quaternary. The Welayati (Neoproterozoic), Loy Khwar (Neoproterozoic or Cambrian), and Gulkhamid (Cambrian) Formations of metamorphosed sedimentary and igneous rocks cover this area extensively (Vendian complexCambrian unit). Abdullah and Chmyriov [1] and Wittekindt and Weippert [65] mapped ultramafic rocks of dunite, peridotite, and serpentinite in many places in the ALV. They are located in western and southern parts of Logar Valley and south of Aynak (Fig. 2).
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Fig. 3. SRTM+ETM+847−45 map of the study area provides elevation data. The combination of ETM+ and SRTM data was performed in ArcGIS and shows the topography of the study area. Vegetation is indicated in green.
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According to [67], Aynak area is dominated by the Aynak anticline. The axis of the anticline mainly strikes north-east. The structure is approximately 4 km in long × 2.5 km wide. The high density rocks in the ALV, such as: 1) the ultramafic rocks from Eocene composed mainly of dunite, peridotite, and serpentinite located in Logar Valley and western parts of Aynak; and 2) the basic intrusions of Proterozoic age composed of gabbro and mafic metavolcanic, amphibolite, and diorite located near Aynak were delineated and overlaid on the geophysical data to facilitate the interpretation.
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III. R EMOTE S ENSING DATA
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Remote sensing data and digital geological fault were combined to investigate the structural setting of the ALV and its surrounding area. The sensors onboard remote sensing satellites are able to resolve and detect geological features through their spatial and spectral resolution [2], [4], [22], [32], [35], [42], [47], [56]. GIS and remote-sensing-based methods were used to integrate all raster and vector results extracted from different data types. Landsat ETM+ and SRTM images were processed and interpreted to identify geological features and produce a regional distribution of geological formations in the study area. The ETM+ image is produced from the Landsat-7 satellite, which is an eight-band multispectral scanning radiometer capable of providing high-resolution images of the earth’s surface. The SRTM obtained elevation data on a near-global scale to generate the most complete high-resolution digital topographic database of the Earth. In this study, the 90-m resolution SRTM data were used to derive the topographic features of the study area. A series of landform interpretation experiments was conducted on the ETM+ images using contrast stretching methods and Hue–Intensity–Saturation transformation [36]. The ETM+ was overlaid on the SRTM map (Fig. 3).
A kernel density algorithm [55] was preferred in the calculations of the lineaments density map. The resulting density surfaces having a resolution of 1 km indicate the spread of the lineaments over the study area. The lineament density map (Fig. 4) shows the number of lineaments per unit area and indicates areas of potentially increased basement fracturing. It facilitates the identification of regions with high lineament density and areas lacking lineaments. To obtain a density map, a grid structure is defined and each lineament that is at least partially within a grid cell is counted toward the total number of lineaments in that grid cell. The density map for the ALV and its surrounding area was compiled from the lineaments extracted from the Landsat imagery and from the shaded relief DEM. The density map was computed from all lineaments as well as by selecting lineaments within the specific orientation groups determined in each section. The high lineaments densities are located mainly in the western part of the ALV and south of Aynak.
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IV. G RAVITY DATA A NALYSIS
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Gravity dataset comprises ground gravity data collected during 1966 and 1967 by Afghanistan Water and Soil Survey Authority [37] and airborne gravity data collected by USGS in 2006 and 2008 [59], [60]. The airborne gravity data were carried out at 7000 m above ground. The ground gravity data was upwarded (upward continuation filter) 7000 m above ground. Both data were combined in Geosoft software to form the complete Bouguer gravity map of ALV [Fig. 6(a)]. The grid space of the combined gravity data is 1000 m. The observed gravity data were corrected and merged with higher resolution existing data by [59], [60]. Many gravity data interpretation methods have been developed since the last three decades to determine the location of the gravity source, which helps in geological interpretation.
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Fig. 4. Lineament density map extracted from the shaded maps based on 30-m DEM data and natural-color Landsat imagery in the ALV and its surrounding area.
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The gravity interpretation methods we use here are: HG, AS, and TD methods. Finally, the results of the three methods were interpreted. A 3-D inversion of gravity data was also performed in order to show the underground density distributions in the study area. The location of geological fault structures and interpreted faults from remote sensed maps was superposed on the gravity maps. The derivative filters (HG, AS, and TD) are powerful in studying the gravity anomaly field and identifying source configuration [18]. These gravity methods are illustrated in Fig. 5 and briefly described below.
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A. Horizontal Gradient
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The HG method was used extensively to locate the boundaries of density contrast from gravity data or pseudogravity data [16], [17]. The method contends that the HG of the gravity anomaly caused by a tabular body tends to overlie the edges of the body if the edges are vertical and well separated from each other [11], [12]. Maxima of the HG indicate the location of faults or contacts. The greatest advantage of the HG method is that it is least susceptible to noise in the data because it requires only the calculation of the two first-order horizontal derivatives of the field [43]. The method is also robust in delineating both shallow and deep sources. The amplitude of the HG [11] is expressed as !" # " #2 2 ∂g ∂g HG = + (1) ∂x ∂y
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∂g ∂g where g is the gravity field observed at (x, y), ∂x and ∂y are the two horizontal derivatives of the gravity field in the x- and y-directions.
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B. Analytic Signal
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The AS method [40] has been the subject of continuing investigation and improvements since it was first applied (e.g. [13],
Fig. 5. Gravity anomaly (mGal) over one block of density contrast of F5:1 −1 g/cm3 delimited by vertical faults. BG: Bouguer gravity; VD: vertical F5:2 F5:3 derivative; HG: horizontal gradient; AS: analytic signal; TD: tilt derivative.
[19], [20], [24], [34], [39], [41], [45]). AS was successfully 210 applied for the measured gravity field data from Obama area 211 (SW Japan) and yielded the precise locations of the faults [50]. 212
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Fig. 6. (a) Bouguer gravity data from the Aynak-Logar Valley, Afghanistan. (b) HG of the data from (a).The rectangle shows the location of the intrusive shallow body. The white dashed line shows the interpreted fault. (c) AS of the data from (a). The white dashed line shows the interpreted fault. (d) TD of the data from (a). The zero value is overlain as a white dashed line and interpreted as contact. Black contour lines show the ultramafic rocks from Eocene mainly dunite, peridotite, and serpentinite located in Logar Valley and western parts of Aynak. Red contour lines show the basic intrusions of Proterozoic age mainly gabbro and mafic metavolcanic, amphibolite, and diorite located near Aynak.
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The AS is peaked over the location of the top of the contact or fault. The general equation for a 3-D gravity source [26] is !" # " #2 " #2 2 ∂g ∂g ∂g |As (x, y)| = + + (2) ∂x ∂y ∂z
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the AS at (x, y),%g is where |As (x, y)| is the amplitude of $ ∂g ∂g the gravity field observed at (x, y), and ∂x , ∂y , and ∂g ∂z are the two horizontal and vertical derivatives of the gravity field, respectively.
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C. Tilt Derivative
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The TD method was used to enhance and sharpen the potential field anomalies. The zero value of the TD delineates the source edges. The TD [38] is defined as T D = tan−1 &$
∂g ∂x
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% $ ∂g ∂g , ∂y , and ∂g g is the gravity field observed at (x, y) and ∂x ∂z are the two horizontal and vertical derivatives of the potential field, respectively. Several applications and developments of the TD are discussed by [5], [8]–[10], [15], [27], [51]–[53], [63], [68]. This method is becoming very popular among geoscientists for interpreting potential field data [46].
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D. 3-D Inversion
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Potential-field inversions are commonly used for mineral and structural investigations. Many 3-D gravity inversion computer programs have been developed in the last two decades with the development of computer performance and data collection [29], [30], [61]. A 3-D inversion model of the gravity data was constructed using VOXI earth modeling tool in Geosoft Oasis Montaj Ver. 8.1. The model covers 3825 km2 (75 km in x-direction and 51 km in y-direction) with 50 grid blocks in the x-direction and 34 grid-blocks in y-direction. Vertically, the model extends
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Fig. 7. (a) 3-D inversion of gravity data from the ALV. Red lines show the geological faults. (b) 3-D gravity inversion showing the intrusions of ultramafic rocks and the observed gravity data.
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Fig. 8. Lineaments and rose diagrams extracted from geological map, gravity data analysis, and shaded maps of the study area.
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from the ground surface to 6.75 km below the surface, including nine grid-blocks (cell-size = 0.75 km). The results of the 3-D gravity inversion [Fig. 7(a)] show intrusion of highdensity rocks in the western part of ALV and northern of Aynak [Fig. 7(b)]. The produced density model from 3-D gravity inversion is consistent with the geology. The highdensity zones correlate with the outcrops of ultramafic rocks. A low-to-medium density anomaly is observed in the western part of ALV elongating in the NE-SW direction. The
boundaries between high and low densities are believed to be 250 fault zones. 251 V. D ISCUSSION AND C ONCLUSION
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The integration of geological data, remote sensing images, digital elevation models, and gravity data can reduce the ambiguity of geological interpretations in various geological settings. The GIS- and remote-sensing-based methods are
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significant in their integration of all raster and vector results extracted from multiple data sources. The ultimate application of the data integration technique provides valuable new information and gives insight into the geomorphology, lithology, and structure of the study area. Fig. 6(a) shows the Bouguer gravity map of the study area and ranging between −235 and −204 mGal and increasing in the Aynak Logar-Valley subarea. This could be related to intrusions of high-density rocks in this region [Fig. 7(b)]. The amplitude of the HG in the ALV is illustrated in Fig. 6(b). A high anomaly [Fig. 6(b)] is detected in the western part of ALV and correlates well with location of the ultramafic Eocene intrusion rocks (density around 3.3 g/cm3 ). The western boundary of this anomaly is bordered by a geological fault. Also, a fault striking NE-SW of 40 km length located at the maxima of the HG was delineated in the western edge of Fig. 6(b). The maxima of AS map are observed mainly in the western part of ALV [Fig. 6(c)], indicating that this region has significant density contrasts that produce identifiable signature on the map. The high values are well correlated with the location of the intrusive rocks of Eocene age. A NE-SW fault was also detected by AS method similar to HG method. AS and HG methods are both useful for delineating shallow intrusions but not deeper bodies [3]. Fig. 6(d) shows the TD of the gravity data. Compared with the original Bouguer data image, it has enhanced the small amplitude anomalies in the north and south of the data considerably. The location of the contact is the location of the zero value of tilt (which is just the zero value of dG/dz). These contours are overlain on the TD map. The contacts detected by TD could be the limits of deep high-density intrusion body in the ALV subarea and north of Aynak. This method also detected the NE-SW fault similar to HG and AS methods. The lineaments usually appear in satellite images as edges with tonal differences. According to [21], [54], there are two common methods for the extraction of lineaments from satellite images: 1) visual extraction, in which the user first makes edge enhancements using directional and nondirectional filters, such as the Laplacian and Sobel image processing techniques, and then manually digitizes the lineaments; and 2) automatic (or digital) extraction, for which various computer-aided methods for lineament extraction have been proposed. Most methods are based on edge-filtering techniques. Fig. 8 shows the fault/contact maps extracted from remote sensing, gravity and geological studies and their respective rose diagrams. The lineaments shown in Fig. 8 were delineated visually. The main direction of geological faults is NNE-SSW, while the main direction of the remote sensing faults is NE-SW. The western part of the map shows good agreement between the two types of faults (geologically identified faults and those identified by remote sensing); however, in the eastern part (the Logar Valley), some additional faults were detected from the remote sensing images. In conclusion, the main findings of the current study can be summarized as follows.
1) The remote sensing images aided detection of faults in the ALV; these faults broadly agree with geologically identified faults in the western part of the study area. The direction of the faults interpreted by remote sensing is NE-SW, while the direction of the geologically and geophysically identified faults is NNE-SSW, which is the direction of the Kabul block trending fault resulted from the indention of the Indian plate [57], [58]. 2) The gravity high in the Logar Valley subarea can be explained by the intrusion of ultramafic rocks of the Welayati Formation (Eocene) detected by the 3-D gravity inversion modeling. 3) A good correlation is observed between the location of the ultramafic intrusive rocks and gravity derivative results especially with HG and AS methods. The TD method could detect the location of deep intrusive bodies. 4) Integration of geology with remote sensed and geophysical data can help us to enhance the subsurface structure of the study area. 5) Geological field investigations are recommended to confirm the interpreted remote sensing lineaments and gravity contacts and their relation to geology.
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Masood Azizi received the B.S. degree in mining geology from Balkh University, Balkh Province, Afghanistan, in 2008. He is currently pursuing the Master degree at the Laboratory of Exploration Geophysics, Kyushu University, Japan. His research interests include remote sensing, GIS, gravity, and magnetic. Mr. Azizi was awarded a scholarship from Japan International Cooperation Agency (JICA) in 2011.
Hakim Saibi received the B.S. and M.S. degrees in hydrogeology from the University of Science and Technology Houari Boumediene (USTHB), Algiers, Algeria, in 2000 and 2003, respectively, and the Ph.D. degree in engineering from Kyushu University, Fukuoka, Japan, in 2007. From 2007 to 2009, he was a Postdoctoral Fellow at Geothermics Laboratory. He is currently an Associate Professor with the Faculty of Engineering, Kyushu University, Fukuoka. He also serves as an Associate Editor of the ASEAN Engineering Journal since October 2013. He has published more than 40 peer-reviewed articles in international journals, including Geothermics, Journal of Volcanology and Geothermal Research, Earth Planets and Space, International Journal of Digital Earth, Journal of African Earth Sciences, Journal of Asian Earth Sciences, Pure and Applied Geophysics, Acta Geophysica, Arabian Journal of Geosciences, and Computational Geosciences. He has frequently served as a referee for many international journals for geosciences and geophysics. His research interests include time-lapse monitoring using gravity, 3-D inversion of gravity, remote sensing, geothermal reservoir engineering, and hydrogeology. Dr. Saibi is a member of the American Geophysical Union, the Society of Exploration Geophysicists, and the Geothermal Research Society of Japan.
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