Results for “Vegetation Classification and Survey” — Page 4

USGS2013

Louisiana Barrier Island Comprehensive Monitoring (BICM) Program Summary Report: Data and Analyses 2006 through 2010

The Barrier Island Comprehensive Monitoring (BICM) program was implemented under the Louisiana Coastal Area Science and Technology (LCA S&T) office as a component of the System Wide Assessment and Monitoring (SWAMP) program. The BICM project was developed by the State of Louisiana (Coastal Protection Restoration Authority [CPRA], formerly Department of Natural Resources [DNR]) to complement other Louisiana coastal monitoring programs such as the Coastwide Reference Monitoring System-Wetlands (CRMS-Wetlands) and was a collaborative research effort by CPRA, University of New Orleans (UNO), and the U.S. Geological Survey (USGS). The goal of the BICM program was to provide long-term data on the barrier islands of Louisiana that could be used to plan, design, evaluate, and maintain current and future barrier-island restoration projects. The BICM program used both historical and newly acquired (2006 to 2010) data to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. BICM datasets included aerial still and video photography (multiple time series) for shoreline positions, habitat mapping, and land loss; light detection and ranging (lidar) surveys for topographic elevations; single-beam and swath bathymetry; and sediment grab samples. Products produced using BICM data and analyses included (but were not limited to) storm-impact assessments, rate of shoreline and bathymetric change, shoreline-erosion and accretion maps, high-resolution elevation maps, coastal-shoreline and barrier-island habitat-classification maps, and coastal surficial-sediment characterization maps. Discussions in this report summarize the extensive data-collection efforts and present brief interpretive analyses for four coastal Louisiana geographic regions. In addition, several coastal-wide and topical themes were selected that integrate the data and analyses within a broader coastal context: (1) barrier-shoreline evolution driven by rapid relative sea-level rise (RSLR), (2) hurricane impacts to the Chandeleur Islands and likelihood of island recovery, (3) impact of tropical storms on barrier shorelines, (4) Barataria Bay tidal-inlet management, and (5) habitat changes related to RSLR. The final theme addresses potential future goals of the BICM program, including rotational annual to semi-decadal monitoring, proposed new-data collection, how to incorporate technological advances with previous data-collection and monitoring protocols, and standardizing methods and quality-control assessments for continued coastal monitoring and restoration.

Louisiana↗

USGS1994

A comparison of change detection methods using multispectral scanner data

Change detection methods were investigated as a cooperative activity between the U.S. Geological Survey and the National Bureau of Surveying and Mapping, People's Republic of China. Subtraction of band 2, band 3, normalized difference vegetation index, and tasseled cap bands 1 and 2 data from two multispectral scanner images were tested using two sites in the United States and one in the People's Republic of China. A new statistical method also was tested. Band 2 subtraction gives the best results for detecting change from vegetative cover to urban development. The statistical method identifies areas that have changed and uses a fast classification algorithm to classify the original data of the changed areas by land cover type present for each image date.

Open-File Report↗

USGS2007

Field Guide to the Plant Community Types of Voyageurs National Park

INTRODUCTION The objective of the U.S. Geological Survey-National Park Service Vegetation Mapping Program is to classify, describe, and map vegetation for most of the park units within the National Park Service (NPS). The program was created in response to the NPS Natural Resources Inventory and Monitoring Guidelines issued in 1992. Products for each park include digital files of the vegetation map and field data, keys and descriptions to the plant communities, reports, metadata, map accuracy verification summaries, and aerial photographs. Interagency teams work in each park and, following standardized mapping and field sampling protocols, develop products and vegetation classification standards that document the various vegetation types found in a given park. The use of a standard national vegetation classification system and mapping protocol facilitate effective resource stewardship by ensuring compatibility and widespread use of the information throughout the NPS as well as by other Federal and state agencies. These vegetation classifications and maps and associated information support a wide variety of resource assessment, park management, and planning needs, and provide a structure for framing and answering critical scientific questions about plant communities and their relation to environmental processes across the landscape. This field guide is intended to make the classification accessible to park visitors and researchers at Voyageurs National Park, allowing them to identify any stand of natural vegetation and showing how the classification can be used in conjunction with the vegetation map (Hop and others, 2001).

Techniques and Methods↗

USGS1997

The International Geosphere Biosphere Programme Data and Information System global land cover data set (DISCover)

The International Geosphere Biosphere Programme Data and Information System (IGBP-DIS), through the mapping expertise of the U.S. Geological Survey and the European Commission's Joint Research Centre, recently guided the completion of a 1-km resolution global land cover data set from advanced very high resolution radiometer (AVHRR) data. The 1-km resolution land cover product, “DISCover,” was based on monthly normalized difference vegetation index composites from 1992 and 1993. The development of DISCover was coordinated by the IGBP-DIS Land Cover Working Group as part of the IGBP-DIS Focus 1 activity. DISCover is a 17-class land cover data set based on the scientific requirements of IGBP elements. The mapping used unsupervised classification and postclassification refinement using ancillary data. The development of this data set was motivated by the need for global land cover data with higher spatial resolution, unproved temporal specificity, and known classification accuracy. The completed DISCover data set will soon be validated to determine the accuracy of the global classification.

Acta Astronautica↗

USGS2009

Terrestrial ecosystems - Isobioclimates of the conterminous United States

As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated isobioclimate classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe . A biophysical stratification approach, developed for South America (Sayre and others, 2008) and now being implemented globally, was used to model the ecosystem distributions. Bioclimate regimes strongly influence the differentiation and distribution of terrestrial ecosystems, and are therefore one of the key input layers in this biophysical stratification. The Rivas-Martínez methodology is based on the concept of establishing a quantifiable classification system which would closely relate the distribution of vegetation to climatic parameters and indices. This method first establishes bioclimatic indices calculated from various ranges of temperature and precipitation data, compares these indices to defined thresholds, and finally applies sets of decision rules to identify the climate classes. The climate classification is hierarchical with four levels: macrobioclimates, bioclimates, thermotypes, and ombrotypes. Thermotypes, which represent thermoclimatic belts, are identified using the positive annual temperature (Tp) thresholds or the compensated thermicity index (Itc) thresholds. Ombrotypes, which represent ombroclimatic belts, are based on the ombrothermic index (Io) which is calculated as a function of both the total positive precipitation and temperature . For this national implementation the source data used for establishing the bioclimatic indices was Daymet. Daymet temperature and precipitation data were developed from 18 years (1980–1997) of climatological records and is available at a spatial resolution of 1 kilometer . This implementation of the Rivas-Martínez methodology resulted in the generation of four climate layers for the conterminous United States: macroclimates, bioclimates, thermotypes, and ombrotypes. However, the biophysical stratification approach used for the ecosystems modeling effort required a single climate layer that accurately reflected regional variation in wet/dry gradients and hot/cold gradients, with a manageable number of classes. Therefore, the data layers for thermotypes and ombrotypes were combined, yielding 127 unique thermotype-ombrotype combinations.The isobioclimates image shows ombrotypic regions (dry/wet gradients) for each thermotypic (warm/cold) region. Additional information about this map and any of the data developed for the ecosystems modeling of the conterminous United States is available online at http://rmgsc.cr.usgs.gov/ecosystems/ .

Scientific Investigations Map↗

USGS1999

Change analysis in the United Arab Emirates: An investigation of techniques

Much of the landscape of the United Arab Emirates has been transformed over the past 15 years by massive afforestation, beautification, and agricultural programs. The "greening" of the United Arab Emirates has had environmental consequences, however, including degraded groundwater quality and possible damage to natural regional ecosystems. Personnel from the Ground- Water Research project, a joint effort between the National Drilling Company of the Abu Dhabi Emirate and the U.S. Geological Survey, were interested in studying landscape change in the Abu Dhabi Emirate using Landsat thematic mapper (TM) data. The EROs Data Center in Sioux Falls, South Dakota was asked to investigate land-cover change techniques that (1) provided locational, quantitative, and qualitative information on landcover change within the Abu Dhabi Emirate; and (2) could be easily implemented by project personnel who were relatively inexperienced in remote sensing. A number of products were created with 1987 and 1996 Landsat TM data using change-detection techniques, including univariate image differencing, an "enhanced" image differencing, vegetation index differencing, post-classification differencing, and changevector analysis. The different techniques provided products that varied in levels of adequacy according to the specific application and the ease of implementation and interpretation. Specific quantitative values of change were most accurately and easily provided by the enhanced image-differencing technique, while the change-vector analysis excelled at providing rich qualitative detail about the nature of a change.

Photogrammetric Engineering and Remote Sensing↗

USGS1983

Evaluation of thematic mapper data for natural resource assessment

The U.S. Geological Survey EROS Data Center evaluated the utility of Landsat Thematic Mapper (TM) date for natural resource assessment, emphasizing manual interpretation and digital classification of the data for U.S. Department of the Interior applications. Substantially more information was derived from TM data than from Landsat Multispectral Scanner (MSS) data. Greater resolution of TM data aided in locating roads, small stock ponds, and many other land features that could be used as landmarks. The improved spatial resolution of TM data also permitted more efficient visual interpretations of land use, better identification of resource types, and improved assessment of ecological status of natural vegetation. TM data also provided a new source of spectral information that was useful for natural resource assessment. New mid-infrared spectral bands, TM band 5 and band 7, aided in distinguishing water resources, wetland vegetation resources, and other important terrain features. The added information was useful for both manual interpretation and digital data classification of vegetation resources and land features. Results from the analyses of both TM and TM simulator (TMS) spectral data suggest that the coefficient of variation for major land cover types is generally less for TM data than for MSS data taken from the same area. This reduction in variance should contribute to an improved multispectral analysis, contributing new information about vegetation in natural ecosystems. Although the amount of new information in TM bands 5 and 7 is mall, it is unique in that the same information cannot be derived from four-band Landsat MSS spectral data.

Conference Paper↗

USGS2014

Structure and vulnerability of Pacific Northwest tidal wetlands – A summary of wetland climate change research by the Western Ecology Division, U.S. EPA

Climate change poses a serious threat to the tidal wetlands of the Pacific Northwest (PNW) region of the U.S. In response to this threat, scientists at the Western Ecology Division of the U.S. EPA at and the Western Fisheries Research Center of the U.S. Geological Survey, along with other partners, initiated a series of studies on the structure and vulnerability of tidal wetlands to climate change. One research thrust was to evaluate community structure of PNW marshes, experimentally assess the vulnerability of marsh plants to inundation and salinity stress (as would happen with sea level rise), and evaluate the utility of the National Wetland Inventory (NWI) classification system. Another research thrust was to develop tools that provide insights into possible impacts of climate change. This effort included enhancing the Sea Level Affecting Marshes Model (SLAMM) to predict the effects of sea level rise on submerged aquatic vegetation (Zostera marina) distributions, evaluating changes in river flow into coastal estuaries in response to precipitation changes, and synthesizing Pacific Coast estuary, watershed, and climate data in a downloadable tool. Because the research resulting from these efforts was published in multiple venues, we summarized them in this document. We anticipate that future research efforts by the U.S. EPA will continue with a focus on climate change impacts on a regional scale.

California, Oregon, Washington↗

USGS2013

Hyperspectral surface materials map of quadrangle 3468, Chak-e Wardak-Siyahgird (509) and Kabul (510) quadrangles, Afghanistan, showing carbonates, phyllosilicates, sulfates, altered minerals, and other materials

This map shows the spatial distribution of selected carbonates, phyllosilicates, sulfates, altered minerals, and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. The map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Epidote or chlorite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Open-File Report↗

USGS2013

Hyperspectral surface materials map of quadrangle 3468, Chak-e Wardak-Siyahgird (509) and Kabul (510) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Open-File Report↗

USGS2013

Hyperspectral surface materials map of quadrangles 3664 and 3764, Char Shengo (123), Shibirghan (124), Jalajin (117), and Kham-Ab (118) quadrangles, Afghanistan, showing carbonates, phyllosilicates, sulfates, altered minerals, and other materials

This map shows the spatial distribution of selected carbonates, phyllosilicates, sulfates, altered minerals, and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. The map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Epidote or chlorite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Open-File Report↗

USGS2013

Hyperspectral surface materials map of quadrangles 3664 and 3764, Char Shengo (123), Shibirghan (124), Jalajin (117), and Kham-Ab (118) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Open-File Report↗

USGS2013

Hyperspectral surface materials map of quadrangle 3166, Jaldak (701) and Maruf-Nawa (702) quadrangles, Afghanistan, showing carbonates, phyllosilicates, sulfates, altered minerals, and other materials

This map shows the spatial distribution of selected carbonates, phyllosilicates, sulfates, altered minerals, and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. The map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Epidote or chlorite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Open-File Report↗

USGS2013

Hyperspectral surface materials map of quadrangle 3166, Jaldak (701) and Maruf-Nawa (702) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Open-File Report↗

USGS2013

Hyperspectral surface materials map of quadrangle 3162, Chakhansur (603) and Kotalak (604) quadrangles, Afghanistan, showing carbonates, phyllosilicates, sulfates, altered minerals, and other materials

This map shows the spatial distribution of selected carbonates, phyllosilicates, sulfates, altered minerals, and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. The map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Epidote or chlorite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Open-File Report↗

USGS2013

Hyperspectral surface materials map of quadrangle 3162, Chakhansur (603) and Kotalak (604) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Open-File Report↗

USGS2013

Hyperspectral surface materials map of quadrangle 3266, Uruzgan (519) and Moqur (520) quadrangles, Afghanistan, showing carbonates, phyllosilicates, sulfates, altered minerals, and other materials

This map shows the spatial distribution of selected carbonates, phyllosilicates, sulfates, altered minerals, and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. The map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Epidote or chlorite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Open-File Report↗

USGS2013

Hyperspectral surface materials map of quadrangle 3266, Uruzgan (519) and Moqur (520) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Open-File Report↗