Chapter 22B. Analysis of Imaging Spectrometer Data for the 

Kunduz Area of Interest

By Raymond F. Kokaly and Stuart A. Giles

Abstract

Imaging spectrometer data collected over the southern part of the Kunduz area of interest (AOI) 

in northeastern Afghanistan were analyzed with spectroscopic methods to identify the occurrence of 

selected materials at the surface. Absorption features in the spectra of HyMap data were compared to a 

reference library of spectra of known materials. Green and dry vegetation cover most of the surface of 

the Kunduz AOI. In the areas with exposed rocks and soils, carbonate minerals are the most abundant.

Associations of hematite with clays are consistent with the red clays in the early Miocene sedimentary 

rocks in the area. The known Kunduz celestite deposit was not covered by the airborne survey.

22B.1 Introduction

Past studies of geologic data of Afghanistan revealed numerous areas with indications of 

potential mineral resources of various types (Peters and others, 2007; Abdullah and others, 1977).

Several of these areas were selected for follow-on studies using imaging spectroscopy to characterize 

surface materials. Imaging spectroscopy is an advanced type of remote sensing, which is also known as 

hyperspectral remote sensing. One of the selected areas is the Kunduz area of interest (AOI) in 

northeastern Afghanistan, which is approximately 200 km north of Kabul (fig. 22B–1). The area may

have potential for the presence of celestite minerals. To help assess these potential resources, 

high-resolution imaging spectrometer data were analyzed to detect the presence of selected minerals that 

may be indicative of past mineralization processes and the accumulation of potential economic mineral 

concentrations. This report contains the results of the spectroscopic data analyses.

22B.2 Data Collection and Processing

In 2007, imaging spectrometer data were acquired over most of Afghanistan as part of the 

U.S. Geological Survey (USGS) project "Oil and Gas Resources Assessment of the Katawaz and 

Helmand Basins.” These data were collected to characterize surface materials in support of assessments 

of resources (coal, water, minerals, and oil and gas) and earthquake hazards in Afghanistan (King and 

others, 2010). Imaging spectrometers measure the reflectance of visible and near-infrared light from the 

Earth’s surface in many narrow channels, producing a reflectance spectrum for each image pixel. These 

reflectance spectra can be interpreted to identify absorption features that arise from specific chemical 

transitions and molecular bonds that provide compositional information about surface materials.

Imaging spectrometer data can only be used to characterize the upper surface materials and not 

subsurface composition or structure. However, subsurface processes can be indicated by the distribution 

of surface materials that can be detected using imaging spectroscopy data.

22B.2.1 Collection of Imaging Spectrometer Data

The HyMap imaging spectrometer (Cocks and others, 1998) was flown over Afghanistan from 

August 22 to October 2, 2007 (Kokaly and others, 2008). HyMap has 512 cross-track pixels and covers 

the wavelength range 0.43 to 2.48 microns (μm) in 128 channels. The imaging spectrometer was flown 

on a WB-57 high-altitude aircraft at 50,000 ft. There were 207 standard data flight lines and 11 cross-
1536 Summaries of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan

cutting calibration lines collected over Afghanistan for a total of 218 flight lines, covering a surface area 

of 438,012 km2 (Kokaly and others, 2008). Data were received in scaled radiance form (calibrated to 

National Institute of Standards and Technology reference materials). Before processing, four channels 

that had low signal-to-noise ratios and (or) were in wavelength regions overlapped by adjacent detectors 

were removed from the HyMap data. Each flight line was georeferenced to Landsat base imagery in 

UTM projection (Davis, 2007). 

Figure 22B–1. Index map of the Kunduz area of interest, northeast Afghanistan.

22B.2.2 Calibration

HyMap data were converted from radiance to reflectance using a multi-step calibration process. 

This process removed the influence of the solar irradiance function, atmospheric absorptions, and 

residual instrument artifacts, resulting in reflectance spectra that have spectral features that arise from 

the material composition of the surface. Because of the extreme topographic relief and restricted access 

to ground-calibration sites, modifications to the standard USGS calibration procedures were required to 

calibrate the 2007 Afghanistan HyMap dataset (Hoefen and others, 2010). In the first step of the 

calibration process, the radiance data were converted to apparent surface reflectance using the radiative 

transfer correction program Atmospheric CORrection Now (ACORN; ImSpec LLC, Palmdale, Calif.).

ACORN was run multiple times for each flight line, using average elevations in 100-m increments, 

covering the range of minimum to maximum elevation within the flight line. A single atmospherically 
Chapter 22B. Analysis of Imaging Spectrometer Data for the Kunduz Area of Interest 1537

corrected image was assembled from these elevation-incremented ACORN results. This was done by 

determining the elevation of each HyMap pixel and selecting the atmospherically corrected pixel from 

the 100-m increment closest to that elevation. 

Each assembled atmospherically corrected image was further empirically adjusted using groundbased reflectance measurements from a ground-calibration site. Five ground-calibration spectra were 

collected in Afghanistan: Kandahar Air Field, Bagram Air Base, and Mazar-e-Sharif Airport, as well as, 

soil samples from two fallow fields in Kabul. At each site, the average field spectrum of the ground 

target was used to calculate an empirical correction factor using the pixels of atmospherically corrected 

HyMap data in the flight lines that passed over the site. Subsequently, each of the HyMap flight lines 

was ground-calibrated using the empirical correction from the closest calibration site. 

To further improve the data quality, an additional calibration step was taken to address the 

atmospheric differences caused, in part, by the large distances between the calibration sites and the 

survey areas. The large distances were a result of the lack of safe access to ground-calibration sites. The 

duration of the airborne survey and variation in time of day during which flight lines were acquired also 

resulted in differences in atmospheric conditions between standard flight lines and lines over groundcalibration sites, which were used to derive the empirical correction factors. Over the course of the data 

collection, the sun angle, atmospheric water vapor, and atmospheric scattering differed for each flight 

line. To compensate for this, cross-cutting calibration flight lines over the ground-calibration areas were 

acquired (Kokaly and others, 2008) and used to refine the reflectance calculation for standard data lines. 

A multiplier correction for standard data lines, typically oriented as north-south flight lines, was derived 

using the pixels of overlap with the well-calibrated cross-cutting lines, subject to slope, vegetation 

cover, and other restrictions on pixel selection (Hoefen and others, 2010). As a result, the localized 

cross-calibration multiplier, derived from the overlap region, reduced residual atmospheric 

contamination in the imaging spectrometer data that may have been present after the ground-calibration 

step. 

After undergoing the above calibration process, the georeferenced and calibrated reflectance data 

were processed. The reflectance spectrum of each pixel of HyMap data was compared to the spectral 

features of reference entries in a spectral library of minerals, vegetation, water, and other materials 

(King and others, 2011; Kokaly and others, 2011). The best spectral matches were determined for each 

pixel, and the results were clustered into classes of materials discussed below. 

HyMap reflectance data were processed using MICA (Material Identification and 

Characterization Algorithm), an Interactive Data Language (IDL) module of the U.S. Geological Survey 

PRISM (Processing Routines in IDL for Spectroscopic Measurements) software (Kokaly, 2011). The 

MICA analysis compared the reflectance spectrum of each pixel of HyMap data to entries in a reference 

spectral library of minerals, vegetation, water, and other materials. The HyMap data were compared to 

97 reference spectra of well-characterized mineral and material standards. The resulting maps of 

material distribution, resampled to 23 × 23 meter square pixel grid, were mosaicked to create thematic 

maps of surface mineral occurrences over the full dataset covering Afghanistan. 

MICA was applied to HyMap data twice to present the distribution of two categories of minerals 

that are naturally separated in the wavelength regions of their primary absorption features. MICA was 

applied using the subset of minerals with absorption features in the visible and near-infrared wavelength 

region, producing a 1-μm map of iron-bearing minerals and other materials (King and others, 2011), and 

again using the subset of minerals with absorption features in the shortwave infrared, producing a 2-μm 

map of carbonates, phyllosilicates, sulfates, altered minerals, and other materials (Kokaly and others, 

2011). For clarity of presentation, some individual classes in these two maps were bundled by 

combining selected mineral types (for example, all montmorillonites or all kaolinites) and representing 

them with the same color in order to reduce the number of mineral classes. The iron-bearing minerals 

map has 28 classes. Iron-bearing minerals with different mineral compositions but similar broad spectral 

features are difficult to classify as specific mineral species. Thus, generic spectral classes, including 

several minerals with similar absorption features, such as Fe3+ Type 1 and Fe3+ Type 2, are depicted on 
1538 Summaries of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan

the map. The carbonates, phyllosilicates, sulfates, and altered minerals map has 32 classes. Minerals 

with slightly different compositions but similar spectral features are less easily discriminated, thus, some 

identified classes consist of several minerals with similar spectra, such as the chlorite or epidote class. 

When comparisons with reference spectra provided no viable match, a designation of “not classified” 

was assigned to a pixel.

22B.3 Geologic Setting of the Kunduz Area of Interest

The Kunduz AOI is mainly within the Kunduz Province in northeastern Afghanistan, but the 

southern part is in the Baghlan Province. The contrast-enhanced natural-color composite of Landsat 

Thematic Mapper bands in figure 22B–2 provides a general overview of the Kunduz AOI terrain and is 

useful for understanding the general characteristics and distribution of surficial material including rocks 

and soil, unconsolidated sediments, vegetation, and hydrologic features.

Figure 22B–2. Contrast-enhanced Landsat Thematic Mapper natural-color image of the Kunduz area of interest. 

Geologic contacts and faults from Doebrich and others (2006).

22B.3.1 Topography

Elevations in the Kunduz AOI range between 329 and 1,683 m (fig. 22B–3). The highest areas 

are in the southern part of the Kunduz AOI in well-defined ranges and foothills. The low areas include 

large agricultural areas in the south and along the eastern edge of the AOI.
Chapter 22B. Analysis of Imaging Spectrometer Data for the Kunduz Area of Interest 1539

Figure 22B–3. Topography and range of elevations in the Kunduz area of interest. 

22B.3.2 Lithology and Structure

The oldest rocks in the AOI are Early Cretaceous red sandstones, siltstones, conglomerates, 

gypsums, and clays exposed in the south-central portion of the area (fig. 22B–4; Doebrich and others, 

2006; Abdullah and Chmyriov, 1977). Eocene and Miocene sedimentary rocks also crop out in the area, 

including a conspicuous unit of Early Miocene red clay. The lower elevations, which make up the 

majority of the Kunduz AOI, are covered by Quaternary and Recent surficial deposits.

22B.3.3 Known Mineralization

Figure 22B–5 shows one location where a potential for celestite mineral resource development 

may exist (Peters and others, 2007). Celestite in the Kunduz deposit occurs in the Paleogene Suzuksk 

and Buhkharsk Formations, which are overlain by unconsolidated Quaternary sediments (Abdullah and 

others, 1977). Celestite-bearing beds as much as 1,400 m long and 0.9 to 1.5 m thick have been reported 

(Abdullah and others, 1977). Unfortunately, the imaging spectrometer data do not extend as far north as 

this deposit. 
1540 Summaries of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan

Figure 22B–4. Geologic map of the Kunduz area of interest from Doebrich and others (2006) and Abdullah and 

Chmyriov (1977).

22B.4 Mineral Maps of the Kunduz Area of Interest

Only the southern two-thirds of the Kunduz AOI was covered by the HyMap airborne imaging 

spectrometer survey. Spectroscopic analysis of these HyMap imaging spectrometer data resulted in the 

identification of a variety of minerals exposed at the surface. Although the occurrence of certain 

minerals may suggest that mineralization processes may have once operated in the area, many of the 

minerals that were identified are also common rock-forming minerals or minerals that can be derived 

from the weathering of a wide variety of rock types. Consequently, the distribution patterns of the 

identified minerals and the geologic context in which they occur are extremely important in 

understanding the causes of mapped mineral occurrences and evaluating the possible potential for 

related mineral deposits.

Figures 22B–6 depicts the results of the Material Identification and Characterization Algorithm

(MICA) analyses of the HyMap data for the Kunduz AOI for the 2-μm materials (clays, carbonates, 

phyllosilicates, sulfates, altered minerals, and other materials). Figure 22B–7 shows the results for the 

iron-bearing (1 μm) minerals. Green and dry vegetation dominate the specral character of the data for 

most of the area. The carbonates are the most dominant minerals detected in the Kunduz AOI, indicated 

by pixels containing the calcite and calcite mixed with clay/mica classes. Gypsum was not detected in 

the area.
Chapter 22B. Analysis of Imaging Spectrometer Data for the Kunduz Area of Interest 1541

Figure 22B–5. Sites of mineralization (Peters and others, 2007) indicated by deposit type on the geologic map of 

the Kunduz area of interest from Doebrich and others (2006) and Abdullah and Chmyriov (1977).

Because of the large number of classes represented and the subtleties of the distribution patterns 

represented in mineral maps, it is instructive to display these results as a series of image maps each 

depicting a selected group of minerals that are mineralogically related or commonly occur together in 

special geologic environments (figs. 22B–8–22B–12). Figure 22B–8 shows the distribution of carbonate 

minerals in the Kunduz AOI, whereas figure 22B–9 shows where clay minerals and micas occur. The 

distribution of iron-oxide and iron-hydroxide minerals is displayed in figure 22B–10. Minerals 

commonly found in hydrothermally altered rocks are mapped in figure 22B–11, and secondary minerals 

often associated with mineralized and (or) weathered rocks are mapped in figure 22B–12. 

22B.4.1 Carbonate Minerals

Carbonate minerals, overwhelmingly calcite, were mapped over the majority of the Kunduz AOI 

where it is not covered with substantial vegetation (fig. 22B–8). In general, calcite is mapped within 

every geologic unit. Small concentrations of pixels that potentially contain dolomite are distributed in 

the center of the area covered by the imaging spectrometer data.
1542 Summaries of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan

Figure 22B–6. Map of carbonates, phyllosilicates, sulfates, altered minerals, and other materials derived from 

HyMap data in the Kunduz area of interest. 

22B.4.2 Clays and Micas

A mixture of clays with carbonates was the primary material mapped in the AOI. Pixels 

containing these mixtures are detected in distinct patterns, especially in early Miocene geologic units.

The pixels that match the chlorite or epidote class do not occur in a spatially consistent pattern and are 

likely the result of noise in the imaging spectrometer data rather than the presence of these minerals.

22B.4.3 Iron Oxides and Iron Hydroxides

The Kunduz AOI contains conspicuous areas of hematite in the center of area (fig. 22B–10). 

Large concentrations of hematite appear in early Miocene and Eocene units. In early Miocene units, the 

distribution of hematite mimics that of the clay (see fig. 22B–9) and probably corresponds to the red 

clays described in that unit. Associations of hematite with clays occur elsewhere in the area, most 

obviously in the hematites along the eastern edge of the Kunduz AOI (fig. 22B–10). 
Chapter 22B. Analysis of Imaging Spectrometer Data for the Kunduz Area of Interest 1543

Figure 22B–7. Map of iron-bearing minerals and other materials derived from HyMap data in the Kunduz area 

of interest. 

22B.4.4 Common Alteration Minerals

Most of the minerals in this group are commonly present in hydrothermally altered rocks 

associated with epithermal mineral deposits (fig. 22B–11). Consequently, where they occur in distinct 

clusters is of great interest in terms of potential mineral deposits. However, the mineral distributions do 

not occur in distributions that are suggestive of such alteration in the Kunduz AOI. 

22B.4.5 Common Secondary Minerals

Secondary minerals, in the epidote and chlorite or epidote classes (fig. 22B–12), occur in 

scattered patterns in the Kunduz AOI, likely a result of noise in the imaging spectrometer data in areas 

of dry vegetation and (or) carbonates, which can lead to spurious false-positive detections of these 

minerals.
1544 Summaries of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan

Figure 22B–8. Map of distribution of carbonate minerals derived from HyMap data in the Kunduz area of 

interest. 

22B.4.6 Celestite

The Kunduz celestite deposit (Abdullah and others, 1977) was not covered by the airborne 

survey. Kokaly and Johnson (this volume) report on the preliminary analysis of imaging spectrometer 

data covering the Tangi-Murch celestite deposit in the Dudkash AOI. 

22B.5 Summary 

Green and dry vegetation cover most of the Kunduz AOI. In the areas with exposed rocks and 

soils, carbonate minerals are the most abundant. Associations of hematite with clays are consistent with

red clays of the Early Miocene units in the area. The Kunduz celestite deposit (Abdullah and others, 

1977) was not covered by the airborne survey. 
Chapter 22B. Analysis of Imaging Spectrometer Data for the Kunduz Area of Interest 1545

Figure 22B–9. Map of distribution of clay and mica minerals derived from HyMap data in the Kunduz area 

of interest. 
1546 Summaries of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan

Figure 22B–10. Map of distribution of iron-oxide and iron-hydroxide derived from HyMap data in the Kunduz 

area of interest. 
Chapter 22B. Analysis of Imaging Spectrometer Data for the Kunduz Area of Interest 1547

Figure 22B–11. Map of distribution of common alteration minerals derived from HyMap data in the 

Kunduz area of interest. 
1548 Summaries of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan

Figure 22B–12. Map of distribution of common secondary minerals derived from HyMap data in the 

Kunduz area of interest. 

22B.6 References Cited

Abdullah, Sh., and Chmyriov, V.M., 1977, Geological map of Afghanistan: Kabul, Afghanistan, 

Ministry of Mining and Industry of Democratic Republic of Afghanistan, scale 1:500,000. 

Abdullah, Sh., Chmyriov, V.M., Stazhilo-Alekseev, K.F., Dronov, V.I., Gannan, P.J., Rossovskiy, L.N., 

Kafarskiy, A.Kh., and Malyarov, E.P., 1977, Mineral resources of Afghanistan (2d ed.): Kabul, 

Afghanistan, Republic of Afghanistan Geological and Mineral Survey, 419 p. 

Cocks, T., Jenssen, R., Stewart, A., Wilson, I., and Shields, T., 1998, The HyMap airborne hyperspectral 

sensor—The system, calibration and performance, in Schaepman, M., Schlapfer, D., and Itten, K.I., 

eds., Proceedings of the 1st EARSeL Workshop on Imaging Spectroscopy, 6–8 October 1998, Zurich: 

Paris, European Association of Remote Sensing Laboratories, p. 37–43. 

Davis, P.A., 2007, Landsat ETM+ false-color image mosaics of Afghanistan: U.S. Geological Survey 

Open-File Report 2007–1029, 22 p. (Also available at http://pubs.usgs.gov/of/2007/1029/.) 

Doebrich, J.L., and Wahl, R.R., comps., with contributions by Doebrich, J.L., Wahl, R.R., Ludington, 

S.D., Chirico, P.G., Wandrey, C.J., Bohannon, R.G., Orris, G.J., Bliss, J.D., Wasy, Abdul, and 

Younusi, M.O., 2006, Geologic and mineral resource map of Afghanistan: U.S. Geological Survey 

Open File Report 2006–1038, scale 1:850,000, available at http://pubs.usgs.gov/of/2006/1038/. 
Chapter 22B. Analysis of Imaging Spectrometer Data for the Kunduz Area of Interest 1549

Hoefen, T.M., Kokaly, R.F., and King, T.V.V., 2010, Calibration of HyMap data covering the country 

of Afghanistan, in Proceedings of the 15th Australasian Remote Sensing and Photogrammetry 

Conference, Alice Springs, Australia, September 12–17, 2010, p. 409, available at 

http://dl.dropbox.com/u/81114/15ARSPC-Proceedings.zip/.

King, T.V.V., Kokaly, R.F., Hoefen, T.M., and Knepper, D.H., 2010, Resource mapping in Afghanistan 

using HyMap data, in Proceedings of the 15th Australasian Remote Sensing and Photogrammetry 

Conference, Alice Springs, Australia, September 12–17, 2010, p. 500, available at 

http://dl.dropbox.com/u/81114/15ARSPC-Proceedings.zip/

King, T.V.V., Kokaly, R.F., Hoefen, T.M., Dudek, K. and Livo, K.E., 2011, Surface materials map of 

Afghanistan—Iron-bearing minerals and other materials: U.S. Geological Survey Scientific 

Investigations Map 3152–B.

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Kokaly, R.F., King, T.V.V., and Livo, K.E., 2008, Airborne hyperspectral survey of Afghanistan 

2007—Flight line planning and HyMap data collection: U.S. Geological Survey Open-File Report 

2008–1235, 14 p.

Kokaly, Ray, 2011, PRISM—Processing routines in IDL for spectroscopic measurements: 

U.S. Geological Survey Open-File Report 2011–1155, available at http://pubs.usgs.gov/of/2011/1155/

Kokaly, R.F., King, T.V.V., Hoefen, T.M., Dudek, K. and Livo, K.E., 2011, Surface materials map of 

Afghanistan—Carbonates, phyllosilicates, sulfates, altered minerals, and other materials: 

U.S. Geological Survey Scientific Investigations Map 3152–A.

.

Peters, S.G., Ludington, S.D., Orris, G.J., Sutphin, D.M., Bliss, J.D., and Rytuba, J.J., eds., and the 

U.S. Geological Survey-Afghanistan Ministry of Mines Joint Mineral Resource Assessment Team, 

2007, Preliminary non-fuel mineral resource assessment of Afghanistan: U.S. Geological Survey 

Open-File Report 2007–1214, 810 p., 1 CD–ROM. (Also available at 

http://pubs.usgs.gov/of/2007/1214/.)