Geology topics

Research about Afghanistan

Source-linked reports with geographic coverage including Afghanistan.

At least 19 recordsLinked to original sources

USGS2024

ENSO-based outlook of droughts and agricultural outcomes in Afghanistan

Drought is one of the key drivers of food insecurity in Afghanistan, which is among the most food insecure countries in the world. In this study, we build on previous research and seek to answer the central question: “What is the influence of El Niño-Southern Oscillation (ENSO) on drought outlooks and agricultural yield outcome in Afghanistan, and how do these influences vary spatially ?” We do so by utilizing multiple indicators of droughts and available wheat yield reports. We find a clear distinction in the probability of drought (defined as being in the lower tercile) in Afghanistan during La Niña compared to El Niño events since 1981. The probability of drought in Afghanistan increased during La Niña, particularly in the North, Northeast, and West regions. La Niña events are related to an increase in the probability of snow drought, particularly in parts of the Amu Darya basin. It is found that relative to El Niño events, snow water equivalent [total runoff] during La Niña events January–March (March–July total runoff) decreases between 9% and 30% (28%–42%) for the five major basins in the country. The probability of agricultural drought during La Niña events is found to be higher than 70% in the rainfed and irrigated areas of the Northeast, North, and West regions. This result is at least partly supported by reported wheat yield composites related to La Niña events that tend to be lower than for El Niño events across all regions in the case of rainfed wheat (statistically significant in Northeast, West, and South regions) and in some cases for irrigated wheat. The results of this study have direct implications for improving early warning of worsening food insecurity in Afghanistan during La Niña events, given that we now have long-lead and skillful forecasts of ENSO up to 18–24 months in advance, which could potentially be used to provide earlier warning of worsening food insecurity in Afghanistan

Weather and Climate Extremes↗

USGS2022

A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan

From the Hindu Kush mountains to the Registan Desert, Afghanistan is a diverse landscape where droughts, floods, conflict, and economic market accessibility pose challenges for agricultural livelihoods and food security. The ability to remotely monitor environmental conditions is critical to support decision making for humanitarian assistance. The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams provide information on hydrologic states for routine integrated food security analysis. While developed for a specific project, these data are publicly available and useful for other applications that require hydrologic estimates of the water and energy balance. These two data streams are unique because of their suitability for routine monitoring, as well as for being a historical record for computing relative indicators of water availability. The global stream is available at ∼ 1-month latency, and monthly average outputs are on a 10 km grid from 1982–present. The second data stream, Central Asia (21–56 ∘ N, 30–100 ∘ E), at ∼ 1 d latency, provides daily average outputs on a 1 km grid from 2000–present. This paper describes the configuration of the two FLDAS data streams, background on the software modeling framework, selected meteorological inputs and parameters, and results from previous evaluation studies. We also provide additional analysis of precipitation and snow cover over Afghanistan. We conclude with an example of how these data are used in integrated food security analysis. For use in new and innovative studies that will improve understanding of this region, these data are hosted by U.S. Geological Survey data portals and the National Aeronautics and Space Administration (NASA). The Central Asia data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/VQ4CD3Y9YC0R (Jacob and Slinski, 2021), and the global data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/5NHC22T9375G (McNally, 2018).

Earth System Science Data↗

USGS2022

Quantifying and visualizing 32 years of agricultural land use change in Kabul, Afghanistan

Agriculture is a key element of Afghanistan’s economy and plays an essential role supporting the expanding population and urban development of Kabul, the country’s capital. Over the past decades the urban landscape has changed substantially and agricultural land use has shifted in its extent, location, and density. Identifying trends in the amount of agricultural area, as an indication of food production, is important for city planning and humanitarian efforts. While many studies have investigated Afghanistan's agriculture, most are conducted at scales that preclude their use for local-scale decision-making. This study quantifies agricultural extent across 32 years from 1988 to 2020 at local scale using simple and repeatable Landsat multispectral image analysis. The volume of data in time-series analysis complicatesvisualization of key findings and long-term trends. This study also explored visualization methods such as zonal mapping, animations, and the isolation of key themes in a 2D static map.

Kabul↗

USGS2022

Anthropogenic stressors compound climate impacts on inland lake dynamics: The case of Hamun Lakes

Inland lakes face unprecedented pressures from climatic and anthropogenic stresses, causing their recession and desiccation globally. Climate change is increasingly blamed for such environmental degradation, but in many regions, direct anthropogenic pressures compound, and sometimes supersede, climatic factors. This study examined a human-environmental system – the terminal Hamun Lakes on the Iran-Afghanistan border – that embodies amplified challenges of inland waters. Satellite and climatic data from 1984 to 2019 were fused, which documented that the Hamun Lakes lost 89% of their surface area between 1999 and 2001 (3809 km 2 versus 410 km 2 ), coincident with a basin-wide, multi-year meteorological drought. The lakes continued to shrink afterwards and desiccated in 2012, despite the above-average precipitation in the upstream basin. Rapid growth in irrigated agricultural lands occurred in upstream Afghanistan in the recent decade, consuming water that otherwise would have fed the Hamun Lakes. Compounding upstream anthropogenic stressors, Iran began storing flood water that would have otherwise drained to the lakes, for urban and agricultural consumption in 2009. Results from a deep Learning model of Hamun Lakes' dynamics indicate that the average lakes' surface area from 2010 to 2019 would have been 2.5 times larger without increasing anthropogenic stresses across the basin. The Hamun Lakes' desiccation had major socio-environmental consequences, including loss of livelihood, out-migration, dust-storms, and loss of important species in the region.

Science of the Total Envionrment↗

USGS2021

Remote sensing inventory and geospatial analysis of brick kilns and clay quarrying in Kabul, Afghanistan

Reconstruction and urban development in Kabul, Afghanistan, has prompted vast expansion of the clay quarrying and brick making industry. This study identified the extent and distribution of clay quarrying and brick kilns in the greater Kabul area between 1965 and 2018. Very high-resolution satellite imagery was interpreted to quantify and characterize the type, number, and location of brick kilns for 1965, 2004, 2011, and 2018. Geospatial analysis of kilns together with geologic data and the results of hyperspectral image analysis yielded information regarding the extent of relevant mineral resources. Finally, kernel density analysis of kiln locations for each date called attention to their shifting spatial distribution. The study found that the clay quarrying and brick making industry has expanded exponentially. The type of kilns has transitioned from artisanal style clamp kilns to small-scale Bull’s Trench Kilns (BTK), and ultimately to Fixed Chimney Bull’s Trench Kilns (FCBTK). While quarrying has occurred entirely within quaternary windblown loess and clay deposits, artisanal clamp kilns were located in fine sediments containing montmorillonite and FCBTKs have developed in sediments containing calcite and muscovite. The study’s inventory of kilns was then used to estimate kiln workforce at 27,500 workers and production at 1.579 billion bricks per year.

Kabul↗

USGS2021

Afghanistan artisanal and small-scale mining sector

For millennia, extractive activity in Afghanistan (officially the Islamic Republic of Afghanistan, or IRA) has been entirely artisanal or small-scale in scope. Various international governments, organizations, and companies have supported the growth of the sector, and the Government of the Islamic Republic of Afghanistan (GoIRA) views its mineral wealth as vital to the country’s stability and prosperity moving forward (Ministry of Mines and Petroleum 2019a). The development of the sector has been prioritized in multiple national plans, strategies, and roadmaps. Of particular importance is the formalization of the artisanal and small-scale mining (ASM) sector to improve working conditions and enable the government to earn royalties from mineral production.

Report↗

USGS2020

Geologic and mineral map (modified from the 1975 original map compilation by A.S. Shadchinev and others) and hyperspectral surface materials maps of the Ghorband, Salang, and Panjsher River Basins; Kapisa, Panjsher, Parwan, and Baghlan Provinces, Afghanistan

Introduction The geologic map and cross sections are a redrafted and modified version of the Geologic map and map of mineral resources of the basins of Ghorband, Salang, and Panjsher ; located in the Kapisa, Panjsher, Parwan, and Baghlan Provinces, Afghanistan. The original map and cross sections are contained in an unpublished Soviet report no. 1162A (Shadchinev and others, 1975) prepared in cooperation with the Ministry of Mines and Industries of the Royal Government of Afghanistan, in Kabul during 1975, under contract no. 55–184/17500. This redrafted map consists of parts of quadrangle map sheets 503–F, 504–C, 504–D, 504–E, and 504–F shown on an index map that can be found on the original 1:100,000-scale map by Shadchinev and others (1975). The redrafted map and cross sections illustrate the mineral deposits and geologic structure of the Ghorband, Salang, and Panjsher River Basins. Because there were no location coordinates provided on the original Soviet map, the map was registered to drainage patterns identified by contours from the Global Digital Elevation Model (GDEM). The end result can only be considered a best fit for the map extend, and some features may not be positioned in their correct geographic location. The redrafted geologic map and cross sections reproduce the topology of rock units, contacts, and faults of the original Soviet map and cross sections, and includes minor modifications based on our examination of the originals. Table 1, provided on both map sheets 1 and 2, shows mineral commodity locations also from the original Soviet map. However, because of the poor quality of the original map, some map features could not be identified and some may be misinterpreted. Further, we have attempted to translate the original Russian terminology and rock classifications into modern English geologic usage as literally as possible without changing any genetic or process-oriented implications in the original rock-unit descriptions. We also use the rock-unit age designations from the original maps, however, rock-unit colors and symbols differ from the colors and symbols shown on the original version. Unit colors were selected according to the color and pattern scheme of the Commission for the Geological Map of the World (http://www.ccgm.org). Unit symbols were assigned based on the geologic age and unit descriptions provided on the original Soviet map. Elevations on the cross sections are derived from the original topography and may not match the Global GDEM topography used on the redrafted geologic map of this report.

Baghlan, Kapisa, Panjsher, Parwan↗

USGS2020

Mapping the extent and methods of small-scale emerald mining in the Panjshir Valley, Afghanistan

Emerald mining in the Panjshir Valley, Afghanistan, has occurred for thousands of years, yet few records exist documenting the detailed spatial extent, techniques, or productivity of small-scale miners. This study proposes new methods to map and monitor the extent and changes in small-scale mining in remote and inaccessible terrain by integrating multispectral remote sensing analysis with archival geologic data and three-dimensional topographic change detection to examine emerald deposit zones and mining activity in the Panjshir Valley. Specifically, previously mapped geologic units known to host emeralds were re-analyzed using Landsat multispectral analysis to investigate the potential distribution of mining activity. Interpretation of very fine-resolution satellite imagery showed that mining activity is becoming more concentrated and transitioning from traditional tunneling methods to mechanized surface excavation. Finally, topographic change analysis of mechanized mine sites was combined with archival grade data to estimate production and consider improved recovery methods by small-scale miners.

Panjshir Valley↗

USGS2020

Passive seismic survey of sediment thickness, Dasht-e-Nawar basin, eastern Afghanistan

Exploration of water resources is needed for public supply, extraction of mineral resources, and economic development in Afghanistan. Remotely-sensed data are useful for identifying the general nature of surface sediments, however, “boots on the ground” geophysical surveys or drilling programs are needed to quantify the thickness of sediments or aquifers. The nature of such investigations presents a risk to field crews that may prohibit exploration of potentially valuable aquifers or mineral resources. The Dasht-e-Nawar basin, in east-central Afghanistan, contains a 400 km2 playa that includes evaporative mineral deposits, particularly lithium, which has been of interest since the 1970s. However, exploration of the basin, as with many areas of Afghanistan, has been hampered by decades of conflict. In 2014, an investigation of the basin was conducted by the U.S. Department of Defense Task Force for Business and Stability Operations (TFBSO), and their contractor, in cooperation with the U.S. Geological Survey (USGS). For this investigation the USGS compared the results of a rapid passive seismic survey of basin sediment thickness to the results of an independently conducted gravity survey of the same area. Each point measurement for the passive seismic method requires less than 30 minutes in the field by one person. The technique utilizes ambient seismic noise without an external sound source such as required by traditional seismic surveys. Additionally, the technique does not require external sensor arrays, which can be kilometers long for some geophysical techniques. The passive seismic equipment used in this study weighs approximately 1 kilogram and is about 10 cm3 in size. Although relatively new for assessment of sediment thickness, several investigations have found this method to be capable of estimating sediment thicknesses, in the 10’s to 1000 meter range, in settings with unconsolidated sediment over bedrock and a contrast in acoustic impedance. In this investigation, the gravity survey was conducted during a period of 3 weeks by an experienced field crew; required a detailed, centimeter-scale land elevation survey; and required laboratory analyses of sediment and rock densities to interpret the gravity data. In contrast, the passive seismic survey was collected by two inexperienced operators over a period of 8 days and required no additional data to interpret. Due to security restrictions, USGS personnel could not visit the site and the seismic operator was trained immediately prior to the field work. Although the quality of the seismic survey was affected by strong afternoon winds, and by the inexperience of the field operator, the results were fairly comparable to the gravity survey. Similar basin sediment thicknesses and patterns in sediment thickness were identified by both surveys in the basin with an estimated maximum thickness of approximately 170 m. The passive seismic technique required substantially less field resources and time than would be required by other geophysical surveys. Although this method will not be effective in all geologic settings, it may be a valuable assessment tool for use before conducting other, more intensive, geophysical efforts or drilling programs, especially in regions with elevated security risks such as Afghanistan.

Dasht-e-Nawar basin↗

USGS2017

Geologic map of the Dusar area, Herat Province, Afghanistan; Modified from the 1973 original map compilations of V.I. Tarasenko and others

The geologic maps and cross sections presented in this report are redrafted and modified versions of the Geologic map and map of useful minerals of the Dusar area (scale 1:50,000) and Geologic sketch map of the Dusar and Namak-sory ore occurrences (scale 1:10,000), located in the Herat Province, Afghanistan. The original maps and cross sections are contained in unpublished Soviet report no. 0290 (Tarasenko and others, 1973) prepared in cooperation with the Ministry of Mines and Industries of the Royal Government of Afghanistan, in Kabul during 1973 under contract no. 50728. The redrafted maps and cross sections (modified from Tarasenko and others, 1973) illustrate the geological structure and mineral occurrences of the Dusar copper-gold-silver-lead-zinc prospect area of western Afghanistan, located within the Dusar-Shaida copper and tin area of interest (AOI), Herat Province, Afghanistan. Mineralization in the Dusar area is hosted within Early Jurassic to Early Cretaceous stratified volcanic and sedimentary rocks associated with numerous diabase and gabbro-diabase intrusive bodies and is generally near a major northeast-trending system of faults and quartz veins. Host rocks consist of quartz keratophyre and quartz-feldspar porphyry, with layers of schist, phyllite, and quartz-chlorite and chlorite-sericite slate; and limestone and shale, with schist and carbonate-chlorite and chlorite slate. Known mineralization includes an extensive quartz vein system, shown on the map as the “northern occurrence,” as well as the Dusar and Namak-sory gossan zones, interpreted to have formed from remnant pyrite mineralization. The veins of the northern occurrence and their altered host rocks are known to contain anomalous to economic concentrations of precious and base metals, with concentrations locally in excess of 2 parts per million gold, 100 parts per million silver, 5 percent copper, and 1 percent lead. These veins occur in swarms, and are hosted along structures that are approximately concordant with the plane of the metamorphic fabric. The veins consist mostly of quartz, with minor carbonate and sulfide minerals, and display weak alteration halos along their margins. The gossans are locally anomalous in these metals, but their size and extent makes them attractive exploration targets for potential massive sulfide mineralization. The Dusar gossan zone is a massive, ochreous, and siliceous limonitic rock, approximately 2,200 meters long, 30 to 250 meters wide, and 2.0 to 7.2 meters thick. Drilling below the Dusar gossan intersected a siliceous, sericitic, and limonitic rock underlain by quartz keratophyre with abundant disseminated pyrite. Mineralized sections grade 0.06 weight percent copper and up to 0.05 weight percent zinc. The Namak-sory gossan zone contains a similar deposit with anomalous concentrations of copper, zinc, and gold. The redrafted maps and cross sections reproduce the topology of rock units, contacts, and faults of the original Soviet maps and cross sections, and include minor modifications based on examination of the originals and observations made during two brief field visits by USGS staff in August, 2010, and June, 2013.

Dusar Area, Herat Province↗

USGS2017

Quaternary deposits in southwestern Afghanistan

Geologic evidence in the closed Seistan Basin of southwestern Afghanistan and adjacent parts of Iran and Pakistan indicates that a lake as much as 65,000 sq km in size occupied this closed depression during Pleistocene time. The deposits consist mostly of lacustrine silt and clay and have a maximum observed thickness of about 250 m. A layer of alluvial gravels overlies the sequence. The deposits are probably early or middle Pleistocene in age; they are old enough to have sustained nearly 300 m of erosion over large areas but are not faulted or detectably folded in the central part of the basin although they are upwarped along the west edge of the basin. Sand dunes cover extensive areas of the basin. Dune orientation shows that the strong surface winds enter the basin blowing toward the south-southeast and then are deflected to the east, apparently as a response to mountains bordering the basin on its south side. The Gawdezereh, a large deflation depression, may be a result of an augmented excavation ability of winds that oc urs where turbulence is created along a zone of deflection.

Quaternary Research↗

USGS2015

Topographic and Hydrographic GIS Datasets for the Afghanistan Geological Survey and U.S. Geological Survey 2014 Mineral Areas of Interest

Mineral extraction and associated industries play an important role in the Afghan economy, particularly in the “transitional era” of declining foreign aid and withdrawal of foreign troops post 2014. In addition to providing a substantial source of government revenue, other potential benefits of natural resource development include boosted exports, employment opportunities, and strengthened industrialization (Joya, 2012). Continued exploration and investment in these industries has resulted in large economic improvements since 2007, when this series of studies was initiated. At that time, the “Preliminary Non-Fuel Mineral Resource Assessment of Afghanistan” was completed by members of the U.S. Geological Survey and Afghanistan Geological Survey (Peters and others, 2007). The assessment published a series of country-wide datasets, including a digital elevation model (DEM), elevation contours, hydrography, transportation routes, geophysics, and cultural datasets (Peters and others, 2007). It also delineated 20 mineralized areas for further study using a geologic-based methodology. A second data product, “Summaries of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan,” was released by Peters and others in 2011. This work highlighted geologic, geohydrologic, and hyperspectral studies that were carried out in specific Areas of Interest (AOIs) to assess the location and characteristics of mineral resources. Also included in the 2011 publication is a collection of appendixes and inventories of Geographic Information System (GIS) datasets for each of the 24 identified AOIs. A third data product was released in 2013 (Casey and Chirico, 2013), publishing datasets for five different AOIs, two subareas, and one AOI extension. Each dataset contains vector shapefiles of the AOI boundary, streams, roads, and contours at 25-, 50-, and 100-meter (m) intervals, as well as raster files of the AOI’s DEM and hillshade. This work represents the fourth installment of the series, and publishes a dataset of eight new AOIs and one subarea within Afghanistan. These areas include Dasht-e-Nawar, Farah, North Ghazni, South Ghazni, Chakhansur, Godzareh East, Godzareh West, and Namaksar-e-Herat AOIs and the Central Bamyan subarea of the South Bamyan AOI (datasets for South Bamyan were published previously in Casey and Chirico, 2013). For each AOI and subarea, this dataset collection consists of the areal extent boundaries, elevation contours at 25-, 50-, and 100-m intervals, and an enhanced DEM. Hydrographic datasets covering the extent of four AOIs and one subarea are also included in the collection. The resulting raster and vector layers are intended for use by government agencies, developmental organizations, and private companies in Afghanistan to support mineral assessments, monitoring, management, and investment.

Open-File Report↗

USGS2015

Geologic map of Kundelan ore deposits and prospects, Zabul Province, Afghanistan; modified from the 1971 original map compilations of K.I. Litvinenko and others

This map and cross sections are redrafted modified versions of the Geological map of the Kundelan ore deposit area, scale 1:10,000 (graphical supplement no. 18) and the Geological map of the Kundelan deposits, scale 1:2,000 (graphical supplement no. 3) both contained in an unpublished Soviet report by Litvinenko and others (1971) (report no. 0540). The unpublished Soviet report was prepared in cooperation with the Ministry of Mines and Industries of the Royal Government of Afghanistan in Kabul during 1971. This redrafted map and cross sections illustrate the geology of the main Kundelan copper-gold skarn deposit, located within the Kundelan copper and gold area of interest (AOI), Zabul Province, Afghanistan. Areas of interest (AOIs) of non-fuel mineral resources within Afghanistan were first described and defined by Peters and others (2007) and later by the work of Peters and others (2011a). The location of the main Kundelan copper-gold skarn deposit (area of this map) and the Kundelan copper and gold AOI is shown on the index map provided on this map sheet. The estimated resources of the Kundelan copper-gold skarn deposit are 21,400 metric tons (t) of copper, 1.6 t of gold, and 133.4 t of molybdenum at an average grade of 1.21 weight percent (wt. %) copper (ranging from 0.66 to 4.03 wt. % copper); 0.9 grams per metric ton (g/t) gold (ranging from 0.3 to 3.1 g/t gold); 0.14 wt. % molybdenum; and as much as 10 g/t silver and 0.03 wt. % bismuth (Peters and others, 2011b). Small past production of gold and base metals is also reported by Douvgal and others (1971) from many prospects within the Kundelan copper and gold AOI. Outside the skarn areas, argillic hydrothermal alteration is present (Abdullah and others, 1977). Most copper and gold prospects in the Kundelan copper and gold AOI are reported to contain commercial-grade ores of copper and (or) gold, and many prospect areas have potential for these commodities to be discovered in commercial volumes. Future initial mine exploration and later development in many of the prospects, and specifically in the Kundelan copper-gold skarn deposit, could result in near-term small- to medium-sized gold mining operations (Peters and others, 2011b). The redrafted map and cross sections reproduce the topology of rock units, contacts, faults, and so forth, of the original Soviet map and cross sections, and they include modifications based on our examination of these documents and our observations made during a brief field visit in August of 2010. We have attempted to translate the original Russian terminology and rock classifications into modern English geologic usage as literally as possible without changing any genetic or process-oriented implications in the original descriptions. We also use the age designations from the original Soviet maps, except for the phase I and II intrusive igneous rocks. Phase I and II igneous rocks are reassigned an Early Cretaceous age (from lower Paleogene) based on a uranium-lead (U-Pb) zircon SHRIMP analysis from quartz diorite, which yielded an age of 104±1 Ma (mega-annum). The information provided in the description of map units is from both the source report by Litvinenko and others (1971) and the original 1:10,000 scale map (graphical supplement no. 18), also from Litvinenko and others (1971). Because of the poor quality of the original map, some map features could not be identified and some features may be misinterpreted. The rock unit colors used on the redrafted maps and cross sections differ from the colors shown on the original Soviet version. Colors were selected according to the color and pattern scheme of the Commission for the Geological Map of the World (CGMW) at http://www.ccgm.org. Elevations on the cross sections are derived from the original Soviet topography and may not match the Global Digital Elevation Model (GDEM) topography used on the redrafted map of this report. Most hydrography derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) has not been included on our redrafted version of the map because of a poor fit with alluvial deposits from the unmodified original Soviet map (graphical supplement no. 18; Litvinenko and others, 1971).

Zabul Province↗

USGS2015

Summary of the Ahankashan Area of Interest

This report summarizes and interprets results of the work in the Ahankashan Area of Interest in northwestern Afghanistan and four study areas—the Ahankashan Prospect Area, Syahsang-Kushkak, Taghab-Soni, and Zakak-e ‘Olya—delineated for their potential undiscovered mineral occurrences with specific emphasis on porphyry copper and related occurrence types. The Area of Interest is underlain by rocks of three different geologic domains that cross from east to west—the Band-e-Bayan Block/Central Pamirs Domain in the south, the Hindu Kush Domain in the Paropamisus Mountains, and the Afghan Turkestan Domain in the north. The domains are sutured remnants of Tethyan tectonic elements. Interpretation of the geologic maps indicates the presence of thrust faults, strike-slip faults, and granitic intrusions emplaced in ground prepared by faulting. Thrust faulting was followed by strike-slip faulting and then followed by magmatic intrusions. Advanced Spaceborne Thermal Emission and Reflection Radiometer data were used to map minerals that have been altered by hydrothermal fluids typically associated with mineralization to delineate new potential occurrences of copper, gold, and silver. Propylitic-, argillic-, and phyllic-altered intrusive rocks are found in the area, as well as very minor amounts of hydrothermal silica-rich rocks. This area of interest is vastly underexplored and contains only seven known mineral occurrences, of which the Ahankashan copper (gold) skarn occurrence is the best known. Gold has been found in stream sediments near the Ahankashan skarn, in the Taghab-Soni study area, and possibly other parts of the Area of Interest, suggesting potential for at least small-scale placer occurrences.

Ahankashan Area of Interest↗

USGS2015

Assessment of bauxite, clay, and laterite deposits in Afghanistan

Bauxite-bearing rocks are present in several regions of Afghanistan; specifically, the southeast segment of the North Afghanistan Platform, the eastern parts of South Afghanistan, and within the Afghanistan-North and -South Pamir Fold Regions. Bauxite-bearing rocks occur at various stratigraphic levels, in lithologically different sequences of sedimentary rocks. The bauxites are paleosols and represent previous, rather than recent, weathering events. Bauxites and bauxite-type horizons are most common at the base of carbonate rock units, where they form the basal horizons of sedimentary rock sequences separated by erosion and stratigraphic unconformity surfaces. Less common are zones in redeposited weathering developed on igneous rocks. At present there are five known stratigraphic intervals with significant bauxite and bauxite-type deposits and occurrences: the lower Permian, the upper Permian, the Upper Triassic, the Lower Jurassic, and the base of the Upper Jurassic. This report summarizes a compilation and review of geological data for regions in Afghanistan that contain bauxite deposits and occurrences based on work conducted during 2009 to 2011 by the U.S. Geological Survey, the U.S. Department of Defense Task Force for Business and Stability Operations, and the Afghanistan Geological Survey. Permian strata contain bauxites and bauxite-like rocks that are recognizable at various stratigraphic intervals within several areas of southern Afghanistan and in the Central Afghan Massif in central Afghanistan. The main zones of known bauxite occurrences are the Haftqala bauxite zone (late Permian and Late Triassic), Shewa bauxite zone (early Permian), Qarghanaw bauxite zone (late Permian and Late Triassic), Arghandab block in Zabul Province (middle through late Permian), Arghandab block in Ghazni Province (early Permian), Surkhob bauxite zone (Early Jurassic), and Tirin block in Uruzgan, Zabul, and Kandahar Provinces (Late Jurassic). Although some bauxite occurrences were sampled in the course of reconnaissance exploration by Soviet workers in the 1960s and 1970s, the bauxite areas in Afghanistan generally are underexplored. The Obatu Sheila area is a known field of bauxite deposits of Late Jurassic age that had been studied in more detail than other known bauxite deposits and occurrences in Afghanistan. Obatu Sheila has an estimated reserve of 7.2 million tons.

Open-File Report↗

USGS2014

Mapping irrigated areas in Afghanistan over the past decade using MODIS NDVI

Agricultural production capacity contributes to food security in Afghanistan and is largely dependent on irrigated farming, mostly utilizing surface water fed by snowmelt. Because of the high contribution of irrigated crops (> 80%) to total agricultural production, knowing the spatial distribution and year-to-year variability in irrigated areas is imperative to monitoring food security for the country. We used 16-day composites of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to create 23-point time series for each year from 2000 through 2013. Seasonal peak values and time series were used in a threshold-dependent decision tree algorithm to map irrigated areas in Afghanistan for the last 14 years. In the absence of ground reference irrigated area information, we evaluated these maps with the irrigated areas classified from multiple snapshots of the landscape during the growing season from Landsat 5 optical and thermal sensor images. We were able to identify irrigated areas using Landsat imagery by selecting as irrigated those areas with Landsat-derived NDVI greater than 0.30–0.45, depending on the date of the Landsat image and surface temperature less than or equal to 310 Kelvin (36.9 ° C). Due to the availability of Landsat images, we were able to compare with the MODIS-derived maps for four years: 2000, 2009, 2010, and 2011. The irrigated areas derived from Landsat agreed well r 2 = 0.91 with the irrigated areas derived from MODIS, providing confidence in the MODIS NDVI threshold approach. The maps portrayed a highly dynamic irrigated agriculture practice in Afghanistan, where the amount of irrigated area was largely determined by the availability of surface water, especially snowmelt, and varied by as much as 30% between water surplus and water deficit years. During the past 14 years, 2001, 2004, and 2008 showed the lowest levels of irrigated area (~ 1.5 million hectares), attesting to the severe drought conditions in those years, whereas 2009, 2012 and 2013 registered the largest irrigated area (~ 2.5 million hectares) due to record snowpack and snowmelt in the region. The model holds promise the ability to provide near-real-time (by the end of the growing seasons) estimates of irrigated area, which are beneficial for food security monitoring as well as subsequent decision making for the country. While the model is developed for Afghanistan, it can be adopted with appropriate adjustments in the derived threshold values to map irrigated areas elsewhere.

Remote Sensing of Environment↗

USGS2014

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni1) and the WGS84 datum. The images for the Ghazni1 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Ghazni1 Mineral District↗

USGS2014

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni2) and the WGS84 datum. The images for the Ghazni2 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Ghazni2 Mineral District↗