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At least 1,189 records · Page 66Linked to original sources
USGS2025

Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks

Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the Dragonfly TM program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes <24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in <15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.

Alaska↗
USGS2019

National earthquake information center strategic plan, 2019–23

Executive Summary Damaging earthquakes occur regularly around the world; since the turn of the 20th century, hundreds of earthquakes have caused significant loss of life and (or) millions of dollars or more in economic losses. While most of these did not directly affect the United States and its Territories, by studying worldwide seismicity we can better understand how to mitigate the effects of earthquakes when they do occur within U.S. borders. Within the U.S. Government, this mandate falls on the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC), which has the statutory responsibility for monitoring and reporting on earthquakes domestically and globally. The NEIC has been operating since 1966, and throughout its history has been recognized as a world leader for earthquake information. For much of this time, NEIC has been cooperating with a number of regional seismic networks (RSNs) which operate in areas of heightened seismicity in the United States. In 2000, the Advanced National Seismic System (ANSS) was founded as a cooperative umbrella for earthquake-related data collection, analysis, and dissemination in the United States, thereby promoting advanced interoperability between the NEIC and RSN partners. The NEIC also cooperates and coordinates with dozens of global seismic networks. At present (2019), NEIC acquires real-time waveform data from more than 2,000 seismic stations worldwide, contributed from more than 130 seismic networks. Since 2006, the NEIC has operated on a 24-hour, 7-days per week (24/7) basis, and reports on about 30,000 earthquakes per year. Soon after the occurrence of a significant global earthquake, notifications are issued to government representatives, aid agencies, the press, and members of the general public by the Earthquake Notification Service (ENS), electronic feeds, and through the USGS Earthquake Hazards Program (EHP) website. Event-specific web pages provide detailed source parameter information outlining the location and magnitude of the earthquake, including more detailed source characteristics like moment magnitude and focal mechanisms and finite fault solutions. Further, NEIC produces a suite of real-time situational awareness products, including ShakeMap, ShakeCast, Did-You-Feel-It? (DYFI?), and Prompt Assessment of Global Earthquakes for Response (PAGER), to characterize the shaking resulting from the earthquake and the impact it is likely to have on nearby populations and infrastructure. All of these products are ultimately archived in the ANSS Comprehensive Catalog (ComCat), hosted and served by the NEIC. The NEIC also pursues an active research program to improve its ability to characterize earthquakes and understand their hazards. These efforts are all aimed at mitigating the risks of earthquakes to humankind. To maintain its prominent position in earthquake monitoring, the NEIC must continue to evolve, concurrently improving its operations and 24/7 robustness, streamlining services and infrastructure, and keeping pace with research and innovation in the field of seismology. This document outlines how the NEIC might best achieve such goals, by describing specific avenues and opportunities for development in the next five years (2019–23). Several key areas of operational and research focus are identified in this plan as being of the highest importance. First, NEIC must finalize improvements to its regional monitoring capabilities, including the implementation of a variety of improved earthquake detection and association algorithms. One of the most exciting avenues of recent research expansion in earthquake monitoring has involved the use of machine learning; NEIC must explore the benefits of machine learning for improved earthquake detection and source characterization. NEIC also needs to address issues related to the timeliness of earthquake information, exploring the benefits of distributing information as it becomes available, rather than when certain quality criteria are met. To that end, the incorporation of real-time Global Positioning System (GPS) data into the NEIC operational workflow will help improve the speed and accuracy of information for moderate-to-large earthquakes. Finally, NEIC should explore how to further expand and improve the quality and content of the products served during earthquake response efforts, including the generation of new earthquake sequence-specific products, adding an evolutionary component to earthquake information, and continued improvements to earthquake impact products.

Circular↗
USGS1986

Principles of logic and the use of digital geographic information systems

Digital geographic information systems allow many different types of data to be spatially and statistically analyzed. Logical operations can be performed on individual or multiple data planes by algorithms that can be implemented in computer systems. Users and creators of the systems should fully understand these operations. This paper describes the relationships of layers and features in geographic data bases and the principles of logic that can be applied by geographic information systems and suggests that a thorough knowledge of the data that are entered into a geographic data base and of the logical operations will produce results that are most satisfactory to the user. Methods of spatial analysis are reduced to their primitive logical operations and explained to further such understanding.

Circular↗
USGS2009

ATM Coastal Topography-Alabama 2001

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Alabama coastline, acquired October 3-4, 2001. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative scanning Lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning Lidar system that measures high-resolution topography of the land surface, and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for pre-survey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography.

Alabama↗
USGS2009

ATM coastal topography-Florida 2001: Western Panhandle

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the western Florida panhandle coastline, acquired October 2-4 and 7-10, 2001. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative scanning Lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning Lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography.

Florida↗
USGS2009

ATM Coastal Topography-Florida 2001: Eastern Panhandle

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the eastern Florida panhandle coastline, acquired October 2, 2001. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative scanning Lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning Lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography.

Florida↗
USGS2009

ATM Coastal Topography-Texas, 2001: UTM Zone 14

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Texas coastline within UTM zone 14, acquired October 12-13, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

Texas↗
USGS2009

ATM Coastal Topography-Texas, 2001: UTM Zone 15

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Texas coastline within UTM zone 15, from Matagorda Peninsula to Galveston Island, acquired October 12-13, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

Texas↗
USGS2009

ATM Coastal Topography-Mississippi, 2001

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Mississippi coastline, from Lakeshore to Petit Bois Island, acquired September 9-10, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

Mississippi↗
USGS2010

ATM Coastal Topography-Louisiana, 2001: UTM Zone 15 (Part 1 of 2)

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Louisiana coastline beach face within UTM Zone 15, from Isles Dernieres to Grand Isle, acquired September 7 and 10, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

Louisiana↗
USGS2009

ATM Coastal Topography - Louisiana, 2001: UTM Zone 16 (Part 2 of 2)

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Louisiana coastline beach face within UTM Zone 16, from Grand Isle to the Chandeleur Islands, acquired September 7 and 9, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

Louisiana↗
USGS2010

Cartographic Production for the FLaSH Map Study: Generation of Rugosity Grids, 2008

Project Summary This series of raster data is a U.S. Geological Survey (USGS) Data Series release from the Florida Shelf Habitat Project (FLaSH). This disc contains two raster images in Environmental Systems Research Institute, Inc. (ESRI) raster grid format, jpeg image format, and Geo-referenced Tagged Image File Format (GeoTIFF). Data is also provided in non-image ASCII format. Rugosity grids at two resolutions (250 m and 1000 m) were generated for West Florida shelf waters to 250 m using a custom algorithm that follows the methods of Valentine and others (2004). The Methods portion of this document describes the specific steps used to generate the raster images. Rugosity, also referred to as roughness, ruggedness, or the surface-area ratio (Riley and others, 1999; Wilson and others, 2007), is a visual and quantitative measurement of terrain complexity, a common variable in ecological habitat studies. The rugosity of an area can affect biota by influencing habitat, providing shelter from elements, determining the quantity and type of living space, influencing the type and quantity of flora, affecting predator-prey relationships by providing cover and concealment, and, as an expression of vertical relief, can influence local environmental conditions such as temperature and moisture. In the marine environment rugosity can furthermore influence current flow rate and direction, increase the residence time of water in an area through eddying and current deflection, influence local water conditions such as chemistry, turbidity, and temperature, and influence the rate and nature of sedimentary deposition. State-of-the-art computer-mapping techniques and data-processing tools were used to develop shelf-wide raster and vector data layers. Florida Shelf Habitat (FLaSH) Mapping Project (http://coastal.er.usgs.gov/flash) endeavors to locate available data, identify data gaps, synthesize existing information, and expand our understanding of geologic processes in our dynamic coastal and marine systems.

Data Series↗
USGS2010

High-Frequency, Crosswell Radar Data Collected in a Laboratory Tank

Crosswell radar data were collected among three wells in a laboratory tank filled with dry sand. Embedded within the sand was a long plastic box, which was the target for the data collection. Two datasets were collected between each pair of wells, making a total of six datasets. The frequencies in the data ranged from 0.5 to 1.5 gigahertz, and the peak frequency was 0.9 gigahertz. The data are well suited for evaluating various processing algorithms, and the data linearly scale to typical field conditions.

Data Series↗
USGS2011

Digital surfaces and hydrogeologic data for the Floridan aquifer system in Florida and in parts of Georgia, Alabama, and South Carolina

A digital dataset for the Floridan aquifer system in Florida and in parts of Georgia, Alabama, and South Carolina was developed from selected reports published as part of the Regional Aquifer-System Analysis (RASA) Program of the U.S. Geological Survey (USGS) in the 1980s. These reports contain maps and data depicting the extent and elevation of both time-stratigraphic and hydrogeologic units of which the aquifer system is composed, as well as data on hydrology, meteorology, and aquifer properties. The three primary reports used for this dataset compilation were USGS Professional Paper 1403-B (Miller, 1986), Professional Paper 1403-C (Bush and Johnston, 1988), and USGS Open-File Report 88-86 (Miller, 1988). Paper maps from Professional Papers 1403-B and 1403-C were scanned and georeferenced to the North American Datum of 1927 (NAD27) using the Lambert Conformal Conic projection (standard parallels 33 and 45 degrees, central longitude -96 degrees, central latitude 39 degrees). Once georeferenced, tracing of pertinent line features contained in each image (for example, contours and faults) was facilitated by specialized software using algorithms that automated much of the process. Resulting digital line features were then processed using standard geographic information system (GIS) software to remove artifacts from the digitization process and to verify and update attribute tables. The digitization process for polygonal features (for example, outcrop areas and unit extents) was completed by hand using GIS software.

Alabama, Florida, Georgia, South Carolina↗
USGS2012

Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area

This product "Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area" is a 1:250,000-scale point spatial dataset developed as part of a regional Southwest Principal Aquifers (SWPA) study (Anning and others, 2012). The study examined the vulnerability of basin-fill aquifers in the southwestern United States to nitrate contamination and arsenic enrichment. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions.

Arizona, California, Colorado, Idaho, Nevada, New ↗
USGS2012

Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area

This product "Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area" is a 1:250,000-scale vector spatial dataset developed as part of a regional Southwest Principal Aquifers (SWPA) study (Anning and others, 2012). The study examined the vulnerability of basin-fill aquifers in the southwestern United States to nitrate contamination and arsenic enrichment. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions.

Arizona, California, Colorado, Idaho, Nevada, New ↗
USGS2013

Surface mineral maps of Afghanistan derived from HyMap imaging spectrometer data, version 2

This report presents a new version of surface mineral maps derived from HyMap imaging spectrometer data collected over Afghanistan in the fall of 2007. This report also describes the processing steps applied to the imaging spectrometer data. The 218 individual flight lines composing the Afghanistan dataset, covering more than 438,000 square kilometers, were georeferenced to a mosaic of orthorectified Landsat images. The HyMap data were converted from radiance to reflectance using a radiative transfer program in combination with ground-calibration sites and a network of cross-cutting calibration flight lines. The U.S. Geological Survey Material Identification and Characterization Algorithm (MICA) was used to generate two thematic maps of surface minerals: a map of iron-bearing minerals and other materials, which have their primary absorption features at the shorter wavelengths of the reflected solar wavelength range, and a map of carbonates, phyllosilicates, sulfates, altered minerals, and other materials, which have their primary absorption features at the longer wavelengths of the reflected solar wavelength range. In contrast to the original version, version 2 of these maps is provided at full resolution of 23-meter pixel size. The thematic maps, MICA summary images, and the material fit and depth images are distributed in digital files linked to this report, in a format readable by remote sensing software and Geographic Information Systems (GIS). The digital files can be downloaded from http://pubs.usgs.gov/ds/787/downloads/.

Data Series↗
USGS1999

Simulating contaminant attenuation, double-porosity exchange, and water age in aquifers using MOC3D

MOC3D is a general-purpose computer model developed by the U.S. Geological Survey (USGS) for simulation of three-dimensional solute transport in ground water (Konikow and others, 1996). The model is an update to the widely used USGS two-dimensional solute-transport model (MOC) and is implemented as an optional “package” for the ground-water flow model MODFLOW (Harbaugh and McDonald, 1996). Directly coupling the time-tested MOC transport algorithms with the widely used MODFLOW program makes MOC3D a powerful tool for simulation of solute transport in ground water in many hydrogeologic settings. The model simulates transport processes that include: Advection - Transport of dissolved solutes at the same rate as the average ground-water flow velocity. Diffusion - Spreading of solute from areas of high concentration to areas of low concentration, caused by “random” molecular motion Dispersion - Diffusion-like spreading of solute that is caused primarily by spatial variability in aquifer properties, which results in spatial variability in transport velocity. Retardation - Reduction in the apparent solute velocity, compared to the ground-water velocity, caused by linear equilibrium sorption on aquifer materials. Decay - Disappearance of solute caused by reactions such as radioactive decay or biodegradation that are proportional to concentration. Growth - Creation (or disappearance) of solute mass caused by reactions that proceed independent of the solute concentration, such as some cases of biodegradation Double-porosity exchange - rate-limited exchange of solute mass between mobile and immobile zones; for example, between fractures and the rock matrix.

Fact Sheet↗