Identification_Information: Citation: Citation_Information: Originator: Hubbard, Bernard Originator: Mack, Thomas J. Originator: Thompson, Allyson Publication_Date: 2012 Title: Lineament Analysis of Mineral Areas of Interest in Afghanistan: Automatically delineated lineaments using 30-m TM imagery Geospatial_Data_Presentation_Form: vector digital data Series_Information: Series_Name: U.S. Geological Survey Open-File Report Issue_Identification: 2012-1048 Publication_Information: Publication_Place: Reston, VA Publisher: U.S. Geological Survey Larger_Work_Citation: Citation_Information: Originator: Hubbard Bernard Originator: Mack, Thomas J. Originator: Thompson, Allyson Publication_Date: 2012 Title: Lineament Analysis of Mineral Areas of Interest in Afghanistan Geospatial_Data_Presentation_Form: vector digital data Series_Information: Series_Name: Open File Report Issue_Identification: 2012-1048 Publication_Information: Publication_Place: Reston, VA Publisher: U.S. Geological Survey Online_Linkage: http://pubs.usgs.gov/of/2012/1048/ Description: Abstract: This coverage presents the results of an automated lineament mapping routines for indicating potential water-bearing bedrock fracture zones. The lineaments were derived using cloud-free 30-m resolution multispectral bands of Landsat-7 ETM+ data coverage, compiled and described by Davis (2006), for the entire country of Afghanistan. Lineaments are defined as "mappable linear or curvilinear features of a surface whose parts align in a straight or slightly curving relationship that may be the expression of a fault or other linear zones of weakness" (Sabins, 2007). Lineaments represent potential water-filled fracture zones and should be verified with additional data and field assessments. Purpose: Water wells in bedrock aquifers tend to be most productive in areas where fractures intersect to form fracture networks. Lineaments represent possible expressions of fracture zones at the land surface. Mapped lineaments may serve as indications of structurally trending mineralized areas, or surface vegetation growth near groundwater- filled fracture zones or locations of near-surface water resources. The purpose of this coverage is to map the distribution of lineaments useful for both locating potential groundwater resources in Afghanistan and for interpreting (possible) structural controls on mineralized areas mapped using a variety of other remote-sensing datasets. Mapped lineaments range in length from greater than 0.3 km to less than 37 km, with features less than 0.1 km excluded from the trend analysis included in the accompanying report. Approximately 82 percent of Afghanistan was mapped, covering all 24 mineralized areas of interest (AOIs) highlighted by Peters and others (2007; 2011). These data were compiled for inclusion in "Bidding Packages" developed for the Task Force for Business and Stability Operations (TFBSO) of the Department of Defense in an interagency agreement with the U.S. Geological Survey of the Department of the Interior. It can be used by potential investors, along with other information, in assessing mineral and hydrologic resources at areas of interest identified by the TFBSO and the Government of Afghanistan, Afghanistan Geological Survey of the Afghanistan Ministry of Mines. Supplemental_Information: The following references provide background information on the study and its methodology: Abdullah Anwar, Akhir, J.M., and Abdullah Ibrahim, 2009, A comparison of Landsat TM and SPOT data for lineament mapping in Hulu Lepar area, Pahang, Malaysia: European Journal of Scientific Research, v. 34, no. 3, p. 406-415. Davis P.A., 2006, Calibrated Landsat ETM+ nonthermal-band image mosaics of Afghanistan: U. S. Geological Survey, Open-File Report 2006-1345, 18 p. Hooper, D.M., Bursik, M.I., and Webb, F.H., 2003, Application of high- resolution, interferometric DEMs to geomorphic studies of fault scarps, Fish Lake Valley, Nevada-California, USA: Remote Sensing of Environment, v. 84, p. 255-267. Hung L.Q., Batelaan, Okke, and De Smedt, Florimond, 2005, Lineament extraction and analysis, comparison of Landsat ETM and ASTER imagery; Case study: Suoimuo tropical karst catchment, Vietnam, in Ehlers, Manfred, and Michel, Ulrich, eds., Remote Sensing for Environmental Monitoring, GIS Applications, and Geology, v. V: Proceedings of SPIE, v. 5983, 12 p. Jayko A.S., Menges C.M., and Thompson, R.A., 2005, Digital method for regional mapping of surficial basin deposits in arid regions; Example from Central Death Valley, Inyo County, California: U.S. Geological Survey, Open-File Report 2005-1445, 43 p. Mars, J.C., and Rowan L.C., 2007, Mapping phyllic and argillic-altered rocks in southeastern Afghanistan using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data: U.S. Geological Survey, Open-File Report 2007-1006, single-page online poster format. Peters, S.G., Ludington, S.D., Orris, G.J., Sutphin, D.M., Bliss, J. D., and Rytuba, J.J., 2007, Preliminary non-fuel mineral assessment of Afghanistan: U.S. Geological Survey Open-File Report 2007-1214, p. 810. Peters, S.G., and others, 2011, Summaries of important areas for mineral investment and production opportunities of nonfuel minerals in Afghanistan: U.S. Geological Survey Open-File Report 2011-1204, 1,810 p. (Also available at http://pubs.usgs.gov/of/2011/1204/.) Sabins, F.F., 2007, Remote Sensing: Principles and Interpretation (3d ed.): Long Grove, IL, Waveland Press, Inc., 494 p. Smith M.J., and Wise S.M., 2007, Problems of bias in mapping linear landforms from satellite imagery: International Journal of Applied Earth Observation and Geoinformation, v. 9, p. 65-78. Walsh, S.J., and Mynar, Frank, 1986, Landsat digital enhancements for lineament detection: Environmental Geology and Water Science, Springer-Verlag, v. 8, no. 3, p. 123-128. Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 19990816 Ending_Date: 20011005 Currentness_Reference: ground condition Status: Progress: Complete Maintenance_and_Update_Frequency: As needed Spatial_Domain: Bounding_Coordinates: West_Bounding_Coordinate: 59.547469 East_Bounding_Coordinate: 72.368338 North_Bounding_Coordinate: 38.498943 South_Bounding_Coordinate: 28.880402 Keywords: Theme: Theme_Keyword_Thesaurus: Sabins (2007) Theme_Keyword: lineaments Theme_Keyword: faults Theme_Keyword: fractures Theme_Keyword: groundwater Theme_Keyword: mineralization Theme_Keyword: vegetation Place: Place_Keyword_Thesaurus: none Place_Keyword: Afghanistan Access_Constraints: none Use_Constraints: none Point_of_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U. S. Geological Survey Contact_Person: Bernard E. Hubbard Contact_Position: Research Geologist Contact_Address: Address_Type: mailing and physical address Address: 12201 Sunrise Valley Drive MS 954 City: Reston State_or_Province: VA Postal_Code: 20192 Country: USA Contact_Voice_Telephone: (703) 648-6155 Contact_Facsimile_Telephone: (703) 648-6252 Contact_Electronic_Mail_Address: bhubbard@usgs.gov Native_Data_Set_Environment: Microsoft Windows XP Version 5.1 (Build 2600)Service Pack 3; ESRI ArcCatalog 9.3.1.1850 Cross_Reference: Citation_Information: Originator: Edited by Peters, Stephen G. Originator: Ludington, Stephen D. Originator: Orris, Greta J. Originator: Sutphin, David M. Originator: Bliss, James D. Originator: Rytuba, James J. Publication_Date: 2007 Title: Preliminary Non-Fuel Mineral Resource Assessment of Afghanistan 2007 Series_Information: Series_Name: Open-File Report Issue_Identification: 2007-1214 Publication_Information: Publication_Place: Reston, Virginia Publisher: U.S. Geological Survey Other_Citation_Details: Shapefile boundaries of 24 mineralized areas of interest (AOI) of Peters and others (2007; 2011) Online_Linkage: http://pubs.usgs.gov/of/2007/1214/ Online_Linkage: http://afghanistan.cr.usgs.gov/ Online_Linkage: http://mapdss2.er.usgs.gov Data_Quality_Information: Attribute_Accuracy: Attribute_Accuracy_Report: The mapped lineaments have no important attributes other than their geospatial position and intersections to help identify potential groundwater resources. Logical_Consistency_Report: The process used to identify lineaments here was applied uniformly throughout the study area. Completeness_Report: Lineaments presented here were observed only within the mineral areas of interest defined by a previous study; their extent within Afghanistan outside these areas of interest was not determined as part of this study. Positional_Accuracy: Horizontal_Positional_Accuracy: Horizontal_Positional_Accuracy_Report: Horizontal accuracy is based on the the Landsat ETM+ base images from which the lineament maps were derived. No attempt was made to either orthorectify or radiometrically correct the base ETM+ images or use such products thereof which was compiled by Davis (2006). The original, uncorrected Landsat scenes were used. Also, no attempt was made to compare horizontal map accuracy with those of published maps and (or) orthorectified base imagery from other sources. Lineage: Source_Information: Source_Citation: Citation_Information: Originator: Davis, Philip A. Publication_Date: 2006 Title: Calibrated Landsat ETM+ Nonthermal-Band Image Mosaics of Afghanistan Geospatial_Data_Presentation_Form: remote-sensing image Series_Information: Series_Name: U.S. Geological Survey Open-File Report Issue_Identification: 2006-1345 Publication_Information: Publication_Place: Reston, VA Publisher: U.S. Geological Survey Online_Linkage: http://pubs.usgs.gov/of/2006/1345/ Type_of_Source_Media: Digital imagery Source_Time_Period_of_Content: Time_Period_Information: Single_Date/Time: Calendar_Date: 2006 Source_Currentness_Reference: publication date Source_Citation_Abbreviation: Davis, 2006 Source_Contribution: The following 27 Landsat-7 ETM+ scenes were used for mapping much of the country within and overlapping the 24 regions of interest for which mineral resource-related and supporting GIS data are being compiled: >elp151r036_7t20010928 >elp152r034_7t20010802 >elp152r035_7t20010802 >elp152r036_7t20011005 >elp152r037_7t20001018 >elp153r034_7t20010708 >elp153r035_7t20010708 >elp153r036_7t19991007 >elp153r037_7t20001025 >elp154r035_7t20010629 >elp154r036_7t20010629 >elp154r037_7t20000525 >elp154r038_7t20010629 >elp155r036_7t20010503 >elp155r037_7t20010503 >elp155r038_7t20010503 >elp155r039_7t20010503 >elp155r040_7t20010503 >elp156r036_7t20010627 >elp156r037_7t20010627 >elp156r038_7t20010510 >elp156r039_7t20010510 >elp157r036_7t19990816 >elp157r037_7t20010517 >elp158r035_7t20010711 >elp158r036_7t20000708 >elp158r037_7t20010625 Additional metadata and description of these scenes (including sun- angle information) are provided by Davis (2006) and tabulated based on scene path and row ID order. For example, all of the 27 scenes used here were acquired either during latest spring(May), summer (June through August), or earliest fall (September), with high sun angles greater than 55-60°. Although high sun-angle scenes are preferable for spectral classification methods used to derive mineral and lithologic maps (for example, Mars and Rowan, 2007), low sun-angle scenes (for example, latest fall, winter, and earliest spring) are preferable for lineament mapping (Sabins, 2007). In this case, other than scene-edge boundaries, no attempt was made to correct lineament errors, such as mapped ridgeline and catchment boundaries, which are usually enhanced under high sun-angle lighting conditions (for example, Hung and others, 2005). Process_Step: Process_Description: The "Lineament Extraction" (LINE) algorithm of PCI Geomatica software was used to automatically extract lineaments from the 30-m resolution Landsat-7 ETM+ multispectral data. Although several methods of preprocessing and image enhancements have been applied to multispectral data, such as Landsat and ASTER, for enhancing geomorphic and tonal contrast related to lineaments [for example, principal components analysis, histogram-based stretch tools, band averages, and numerous filters (Walsh and Mynar, 1986)], the most effective method was found to be simple band average of all radiance values stretched to an 8-bit gray-scale range (Walsh and Mynar, 1986). Notably, band ratios were not used here because they tend to highlight spectral contrast at the expense of geomorphic and topographic contrast (Sabins, 2007). The following input parameters were used and are documented in both the software user's manual and recent supporting application references, such as Hung and others(2005) and Abdullah and others (2009); they successfully used the same PCI Geomatica software: >RADI = 24 >GTHR = 94 >LTHR = 50 >FTHR = 7 >ATHR = 40 >DTHR = 30 These input parameters were based on initial lineament mapping results applied on a trial-by-error basis to match the patterns of linearly trending vegetation, phyllic-mineralized areas, and mapped faults using the same ASTER scene covering parts of the Argandab igneous intrusive complex of Afghanistan as rendered by Mars and Rowan (2007). These same input parameters were tested on ASTER scenes covering portions of the Dushar-Shaida copper and tin AOI and "tourmaline tin"-bearing AOI, both south of Herat. The resulting maps of lineament and vegetation features were field checked and verified in both the overhead aerial flybys and on the ground by Thomas Mack during field reconnaissance on 08/06/2010. Hung and others (2005) tested the PCI algorithm using both Landsat ETM and ASTER imagery; they found that ASTER 15-m resolution visible and near-infrared (VNIR) bands produced less noisy and more accurate lineament patterns than the equivalent Landsat 30-m resolution bands. Despite their lower 30-m resolution, the ASTER shortwave infrared (SWIR) bands still have great potential for mapping linearly trending spectral-tonal contrast differences related to mineral alteration (for example, Mars and Rowan, 2007). In evaluating the spectral-tonal and geomorphic contrast characteristics of each of the six reflective bands of Landsat, Abdullah and others (2009) found that Landsat TM band 4 (as well as SPOT band 3) yields the highest number of lineaments, which is not surprising, because it overlaps with the spectral range of the near infrared (NIR) reflective peak of vegetation. Also, Smith and Wise (2007) compare and document the enhanced number and increasing accuracy of lineaments mapped when using the higher spatial resolution panchromatic bands (15 m for ETM+) compared to preprocessed gray-scale versions of the lower spatial resolution multispectral bands (30 m for ETM+). Lineament mapping results using both sets of bands were generated, although the results derived from the 30-m resolution multispectral imagery are contained in this coverage being described and documented by this metadata file. A separate and accompanying coverage was produced that contains lineament mapping results derived from the 30-m panchromatic Landsat bands for all 27 scenes. Both results were compared to the preliminary field-checked ASTER mapping results obtained for the Dusar-Shaida area, and the results derived from the 15-m panchromatic Landsat data seem to best match based on visual inspection) the pattern and density of lineaments mapped using 15-m ASTER VNIR and SWIR bands preprocessed to single monochrome images. The most glaring caveat in this approach to parameterization and thresholding is that lineament mapping results are being compared between two different multispectral-image data types with differing spectral and spatial-resolution characteristics, acquired at two completely different times (05/17/2001 for the ASTER imagery covering Dusar-Shaida and 07/20/2001 for the Landsat ETM+ imagery covering part of the same area). However, the consistency in the results between both individual sensors and bands of varying resolutions within sensors is also notable and justifies such extrapolation. Because of its limited swath-width (60 km) compared to that of Landsat (185 km) and variable off-nadir pointing, which produces inconsistent overlap between successive orbital swaths, use of ASTER for country-scale mapping of Afghanistan was considered impractical. Instead, both the 30-m resolution multispectral bands (preprocessed to single monochrome-base gray-scale images) and 15-m resolution panchromatic band (no preprocessing, other than Gaussian stretch to fill the entire 8-bit gray-scale display range) were used here for deriving country-scale lineament map coverages. However, more consistent usage of low sun-angle Landsat (5 and 7) scenes from the EROS Data Center archives was also considered impractical due to time constraints on necessary image-quality checks, and snow-cover and cloud-cover considerations. The final seamless country-wide coverage was produced by (1) removing redundant overlapping areas between successive Landsat orbital paths and successive rows within individual orbital swaths, and (2) removing flat-basin and valley-fill areas representing slope angles less than 2° (for example, Jayko and others, 2005) as derived from ~90-m resolution Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) and all other areas outside those overlapping the SRTM coverage. This was done by first acquiring "hydrologic shapefiles," in this case representing overlapping areas from the 30-m multispectral Landsat images. New boundary shapefiles were then digitized; they defaulted to overlapping areas trending towards the north and east as opposed to those trending south and west. As a result, each separate shapefile boundary corresponds to one hydrologic shapefile. Each boundary shapefile was then used to clip their corresponding "hydrologic shapefile" in order to create new coverages that did not overlap. Using the resulting clipped coverages, the merge tool was then used to create the semifinal shapefile representing the 30-m multispectral-derived lineaments coverage. The areas representing flat-basin and valley-fill deposits (slope angles less than 2°) were smoothed to a polygon coverage using a median filter with a seven SRTM pixel kernel. The 30-m multispectral- derived lineament coverage was clipped using the coverage representing flat-basin and valley-fill areas to produce a lineament coverage representative of higher slope (greater than 2°) bedrock areas. The latter includes alluvial fans and pediments, which can also exhibit surface expression of deeper seated faulting (for example, Hooper and others, 2003) and perhaps related buried acquifers. Process_Date: 201012 - 201103 Process_Contact: Contact_Information: Contact_Person_Primary: Contact_Person: Bernard E. Hubbard Contact_Organization: U.S. Geological Survey Contact_Position: Research Geologist Contact_Address: Address_Type: mailing address Address: 12201 Sunrise Valley Drive MS 954 City: Reston State_or_Province: VA Postal_Code: 20192 Country: USA Contact_Voice_Telephone: (703) 648-6155 Contact_Facsimile_Telephone: (703) 648-6252 Contact_Electronic_Mail_Address: bhubbard@usgs.gov Cloud_Cover: 0% except for small cloud near SE portion of scene p155r040_7t20010503 Spatial_Data_Organization_Information: Direct_Spatial_Reference_Method: Vector Point_and_Vector_Object_Information: SDTS_Terms_Description: SDTS_Point_and_Vector_Object_Type: String Point_and_Vector_Object_Count: 94282 Spatial_Reference_Information: Horizontal_Coordinate_System_Definition: Planar: Map_Projection: Map_Projection_Name: Transverse Mercator Transverse_Mercator: Scale_Factor_at_Central_Meridian: 0.999600 Longitude_of_Central_Meridian: 66.000000 Latitude_of_Projection_Origin: 34.000000 False_Easting: 0.000000 False_Northing: 0.000000 Planar_Coordinate_Information: Planar_Coordinate_Encoding_Method: coordinate pair Coordinate_Representation: Abscissa_Resolution: 30 Ordinate_Resolution: 30 Planar_Distance_Units: meters Geodetic_Model: Horizontal_Datum_Name: D_WGS_1984 Ellipsoid_Name: WGS_1984 Semi-major_Axis: 6378137.000000 Denominator_of_Flattening_Ratio: 298.257224 Entity_and_Attribute_Information: Overview_Description: Entity_and_Attribute_Overview: This line-vector coverage has no important attributes other than the spatial position and intersection of lineaments for targetted groundwater resource potential assessment. Entity_and_Attribute_Detail_Citation: Further notes on the procedure may be obtained at http://pubs.usgs.gov/of/2012/1048/ Distribution_Information: Distributor: Contact_Information: Contact_Organization_Primary: Contact_Organization: USGS Information Services Contact_Address: Address_Type: mailing Address: Box 25286, Denver Federal Center City: Denver State_or_Province: Colorado Postal_Code: 80255-0046 Country: USA Contact_Voice_Telephone: 1-888-ASK-USGS Contact_Facsimile_Telephone: 1-303-202-4695 Contact_Electronic_Mail_Address: infoservices@usgs.gov Resource_Description: USGS Open-File Report 2012-1048 Distribution_Liability: This report is preliminary and has not been reviewed for conformity with U.S. Geological Survey editorial standards (or with the North American Stratigraphic Code). Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Standard_Order_Process: Digital_Form: Digital_Transfer_Information: Format_Name: Shapefile Format_Version_Number: 1.0 File_Decompression_Technique: no compression applied Transfer_Size: 0.982 Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: http://pubs.usgs.gov/of/2012/1048/ Fees: none Metadata_Reference_Information: Metadata_Date: 20110919 Metadata_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Bernard E. Hubbard Contact_Position: Research Geologist Contact_Address: Address_Type: mailing and physical address Address: 12201 Sunrise Valley Drive City: Reston State_or_Province: VA Postal_Code: 20192 Country: USA Contact_Voice_Telephone: (703) 648-6155 Metadata_Standard_Name: Content Standard for Digital Geospatial Metadata Metadata_Standard_Version: FGDC-STD-001-1998