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USGS2010

Vegetation classification and distribution mapping report: Canyon de Chelly National Monument

Executive Summary: The classification and distribution mapping of the vegetation of Canyon de Chelly National Monument (CACH) and surrounding environment was accomplished through a multi-agency effort between 2003 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center and Fort Collins Science Center, Navajo Natural Heritage Program, Northern Arizona University, and NatureServe. The project team described 48 plant communities for CACH—35 of which were described from quantitative classification based on field-relevé data collected in 2004. Five additional plant communities were based on field relevés collected in a previous study. The team derived four additional plant communities from field observations during the photointerpretation phase of the project, and field documented them during accuracy assessment. The National Vegetation Classification Standard served as a conceptual framework for assigning these plant communities to the alliance and association level. Ten of the 48 plant communities were designated “park specials”, that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing CACH, with three different map-class schemas: base, group, and management map classes. The base map classes represented the finest level of spatial detail. Photointerpreters delineated initial polygons through manual interpretation of 2003/2004 1:12,000-scale true color aerial photography supplemented by occasional computer screen digitizing on a mosaic of digitized aerial photos. These polygons were labeled with base map classes during photointerpretation. Field visits verified interpretation concepts. The vegetation map database includes • ? 53 base map classes, which consist of associations and park specials classified with the quantitative analysis • ? additional associations noted during photointerpretation • ? non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 4,718 polygons in the project area. A field-based accuracy assessment of the base map classes showed the overall accuracy to be 50.8% The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, Version 2 (Federal Geographic Data Committee 2008). Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as a first approximation of the group level. The project team identified 16 group map classes in this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 79.9%. In consultation with park staff, the team developed management map classes that consisted of park-defined groupings of base map classes and were intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 28 management map classes have an overall accuracy of 77.1%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary geographic information system and digital database products were also produced that can be used independently, or to augment the main products. These products include shapefiles of the location of field-collected data and relational databases of field-collected data.

Report↗

USGS1991

USFWS selected geographic analyses

The geographic information system (GIS) used by the National Wetlands Research Center (NWRC) of the U.S. Fish and Wildlife Service has been valuable in assisting natural resource managers in planning and managing coastal fish and wildlife resources. In the past 5 years, NWRC has conducted about 60 studies employing this technology. Applications have ranged from simple natural resource inventories to documentation of trends in wetland changes and complex predictive modeling of impacts of harbor expansion on biological resources. Maps, tables, and data bases from these studies have been presented before local, State, and Congressional committees as well as numerous scientific and public organizations. This paper describes and summarizes selected GIS projects related to resource inventories, analyses of wetland change, and cartographic modeling of coastal areas of the United States.

Conference Paper↗

USGS2010

National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 2, northeast United States: IMPV01_2

This 30-meter resolution data set represents the imperviousness layer for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System, browse graphic: nlcd01-partition. The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004) and http://www.mrlc.gov/mrlc2k.asp.. The NLCD 2001 was created by partitioning the United States into mapping-zones. A total of 68 mapping-zones browse graphic: nlcd01-mappingzones.jpg were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping-zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

northeast United States↗

USGS2010

National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 3, Southwest United States: IMPV01_3

Data Series↗

USGS1996

National Digital Orthophoto Program

A critical component of the National Spatial Data Infrastructure (NSDI) is Framework. Framework provides a base on which to collect, register, and integrate geospatial information accurately and consistently. The Federal Geographic Data Committee (FGDC) proposed that Framework include geodetic control, orthoimagery, elevation, transportation, hydrography, governmental units, and cadastral data. The Mapping Science Committee of the National Research Council recommends that geodetic control, orthoimagery, and elevation data become the critical foundation of the NSDI. The National Digital Orthophoto Program (NDOP) is a working model on how Federal, State, and local government, as well as private industry, can participate to develop the orthoimagery Framework for the Nation.

Report↗

USGS2022

Data sources and methods for digital mapping of eight valley-fill aquifer systems in upstate New York

Digital hydrogeologic maps were developed in eight study areas in upstate New York by the U.S. Geological Survey in cooperation with the New York State Department of Environmental Conservation. The digital maps define the hydrogeologic framework of the valley-fill aquifers and surrounding till-covered uplands in the vicinity of the villages of Ellenville and Wurtsboro and hamlets of Woodbourne and South Fallsburg in Sullivan and Ulster Counties, town of Greene in Chenango County, city of Cortland and town of Cincinnatus in Cortland County, city of Jamestown in Chautauqua County, city of Olean and village of Ellicottville in Cattaraugus County, and villages of Fishkill and Wappinger Falls in Dutchess County. The hydrogeologic framework provided the foundation for groundwater-flow models that were used in the delineation of areas contributing groundwater flow to production wells screened in four of the eight valley-fill aquifers considered in this study. The hydrogeologic framework for the other four study areas was developed for potential future use in groundwater contributing-area studies. Data used in the creation of all digital surfaces and thicknesses included published surficial geology; aquifer maps and hydrogeologic sections; light detection and ranging (lidar) datasets; the Soil Survey Geographic Database; and lithologic well logs from the National Water Information System, New York State Department of Environmental Conservation, New York State Department of Transportation, and Empire State Organized Geologic Information System databases. Digital maps of the surficial geology; thickness of the surficial sand and gravel aquifers; and tops of the confining lacustrine silt and clay units, confined sand and gravel aquifers, and bedrock surfaces were created by using ArcGIS (a geographic information system). All surfaces and thicknesses were generated by using one of the following ArcGIS interpolation tools: Topo to Raster, Natural Neighbors, Kriging, or Empirical Bayesian Kriging. The datasets developed in this study provide a greater understanding of the underlying hydrogeologic framework in glacial valley-fill aquifers and can be applied in the evaluation of groundwater-supply development and protection.

New York↗

USGS2010

EAARL Coastal Topography-Sandy Hook Unit, Gateway National Recreation Area, New Jersey, Post-Nor'Ida, 2009

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Sandy Hook Unit of Gateway National Recreation Area in New Jersey, acquired post-Nor'Ida (November 2009 nor'easter) on December 4, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL 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 sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗

USGS1994

National Spatial Data Infrastructure and its usefulness to the dredging community

The solution to understanding the dredging impacts is the type of scenario that lends itself to new approaches to understanding interrelationships between multiple variables within a dynamic environment. New data are becoming available to allow the examination of the consequences of dredging in a manner not done before. Efforts have been made by the Federal Geographic Data Committee (FGDC) and the creation of a National Spatial Data Infrastructure (NSDI) as an element of the National Information Highway has helped in solving some of the problems of the unavailability and unacceptability of data needed to support the applications.

Conference Paper↗

USGS2011

Geographic profiling to assess the risk of rare plant poaching in natural areas

We demonstrate the use of an expert-assisted spatial model to examine geographic factors influencing the poaching risk of a rare plant (American ginseng, Panax quinquefolius L.) in Shenandoah National Park, Virginia, USA. Following principles of the analytic hierarchy process (AHP), we identified a hierarchy of 11 geographic factors deemed important to poaching risk and requested law enforcement personnel of the National Park Service to rank those factors in a series of pair-wise comparisons. We used those comparisons to determine statistical weightings of each factor and combined them into a spatial model predicting poaching risk. We tested the model using 69 locations of previous poaching incidents recorded by law enforcement personnel. These locations occurred more frequently in areas predicted by the model to have a higher risk of poaching than random locations. The results of our study can be used to evaluate resource protection strategies and to target law enforcement activities.

Environmental Management↗

USGS2010

EAARL Coastal Topography and Imagery-Assateague Island National Seashore, Maryland and Virginia, Post-Nor'Ida, 2009

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Assateague Island National Seashore in Maryland and Virginia, acquired post-Nor'Ida (November 2009 nor'easter) on November 28 and 30, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar(EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL 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 sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗

USGS2010

EAARL coastal topography-Cape Hatteras National Seashore, North Carolina, post-Nor'Ida, 2009: first surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, acquired post-Nor'Ida (November 2009 nor'easter) on November 27 and 29 and December 1, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL 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 sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗

USGS2011

EAARL Coastal Topography-Cape Hatteras National Seashore, North Carolina, Post-Nor'Ida, 2009: Bare Earth

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, acquired post-Nor'Ida (November 2009 nor'easter) on November 27 and 29 and December 1, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL 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 sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

Data Series↗

USGS1996

Floristic summary of 22 National Parks in the Midwestern United States

Biological diversity is studied at many geographical scales, but specimen collecting is invariably done at a local level. Collecting of animal and plant specimens leads to the compilation of checklists for multiple small areas, which are sometimes merged to produce larger, regional checklists. Such an approach was employed to study the regional vascular flora of 22 national parks of the midwestern United States. Total number of plant taxa (species level and below) ranged from 86 at Hopewell Culture National Historical Park to 1,399 at Indiana Dunes National Lakeshore and averaged 520 per park. Infraspecific taxa were 12% or less of all taxa at all parks and averaged 7%. Genera per parkranged from 70 to 562, and families ranged from 41 to 145. Non-native species averaged 95 per park, or about 27% on average of the total number of taxa per park. The aggregated regional flora contained just over 2,900 taxa, 828 genera and 160 families. Eleven percent of the taxa were below the species level. Almost 17% of the taxa were non-native, a relatively large percentage, but not out of the range of percentages reported in the literature. The observed and estimated numbers of taxa for this region were in good agreement with other estimates for these latitudes and for a standard regional size. However, the parks do not represent their respective state floras very well when they are aggregated at that scale. Indiana was the best represented state with 65% of the state flora found in the parks, while only 25% of each state's flora were represented by parks in Iowa, Kansas, and Nebraska, and the average representation was only 42%.

Iowa, Indiana, Kansas, Michigan, Minnesota, Missou↗

USGS1988

Glaciers of Antarctica

Of all the world's continents Antarctica is the coldest, the highest, and the least known. It is one and a half times the size of the United States, and on it lies 91 percent (30,109,800 km 3 ) of the estimated volume of all the ice on Earth. Because so little is known about Antarctic glaciers compared with what is known about glaciers in populated countries, satellite imagery represents a great leap forward in the provision of basic data. From the coast of Antarctica to about 81?south latitude, there are 2,514 Landsat nominal scene centers (the fixed geographic position of the intersection of orbital paths and latitudinal rows). If there were cloud-free images for all these geographic centers, only about 520 Landsat images would be needed to provide complete coverage. Because of cloud cover, however, only about 70 percent of the Landsat imaging area, or 55 percent of the continent, is covered by good quality Landsat images. To date, only about 20 percent of Antarctica has been mapped at scales of 1:250,000 or larger, but these maps do include about half of the coastline. The area of Antarctica that could be planimetrically mapped at a scale of 1:250,000 would be tripled if the available Landsat images were used in image map production. This chapter contains brief descriptions and interpretations of features seen in 62 carefully selected Landsat images or image mosaics. Images were chosen on the basis of quality and interest; for this reason they are far from evenly spaced around the continent. Space limitations allow less than 15 percent of the Landsat imaging area of Antarctica to be shown in the illustrations reproduced in this chapter. Unfortunately, a wealth of glaciological and other features of compelling interest is present in the many hundreds of images that could not be included. To help show some important features beyond the limit of Landsat coverage, and as an aid to the interpretation of certain features seen in the images, 38 oblique aerial photographs have been included. Again, these represent only a small fraction of the large number of aerial photographs now available in various national collections. The chapter is divided into five geographic sections. The first is the Transantarctic Mountains in the Ross Sea area. Some very large outlet glaciers flow from the East Antarctic ice sheet through the Transantarctic Mountains to the Ross Ice Shelf. Byrd Glacier, one of the largest in the world, drains an area of more than 1,000,000 km 2 . Next, images from the Indian Ocean sector are discussed. These include the Lambert Glacier- Amery Ice Shelf system, so large that about 25 images must be mosaicked to cover its complex system of tributary glaciers. Shirase Glacier, a tidal outlet glacier in the sector, flows at a speed of 2.5 km a -l . About 200 km inland and 200 km west of Shirase Glacier lie the Queen Fabiola ("Yamato") Mountains, whose extensive exposures of `blue ice' lay claim to being the world's most important meteorite-collecting locality, with more than 4,700 meteorite fragments discovered since 1969. The Atlantic Ocean sector is fringed by ice shelves into which flow large ice streams like Jutulstraumen, Stancomb-Wills, Slessor, and Recovery Glaciers. Filchner and Ronne Ice Shelves together cover an area two-thirds the size of Texas. From the western margin of the Ronne Ice Shelf, the north-trending arc of the Antarctic Peninsula, with its fjord and alpine landscape and fringing ice shelves, stretches towards South America. The Pacific Ocean sector begins with the Ellsworth Mountains, which include the highest peaks (Vinson Massif at 4,897 m) in Antarctica. The area between the Ellsworth Mountains and the eastern margin of the Ross Ice Shelf is fringed with small ice shelves and some major outlet glaciers. One of these, Pine Island Glacier, was found from comparing 1973 and 1975 images to have an average ice-front velocity of 2.4 km a -1 . This part of Antarctica contains many dormant volcanoes; the summits of servers, such as Mount Takahe with its 8-km-wide summit caldera, protrude through the West Antarctic ice sheet.

Professional Paper↗

USGS2013

Center of Excellence for Geospatial Information Science research plan 2013-18

The U.S. Geological Survey Center of Excellence for Geospatial Information Science (CEGIS) was created in 2006 and since that time has provided research primarily in support of The National Map. The presentations and publications of the CEGIS researchers document the research accomplishments that include advances in electronic topographic map design, generalization, data integration, map projections, sea level rise modeling, geospatial semantics, ontology, user-centered design, volunteer geographic information, and parallel and grid computing for geospatial data from The National Map. A research plan spanning 2013–18 has been developed extending the accomplishments of the CEGIS researchers and documenting new research areas that are anticipated to support The National Map of the future. In addition to extending the 2006–12 research areas, the CEGIS research plan for 2013–18 includes new research areas in data models, geospatial semantics, high-performance computing, volunteered geographic information, crowdsourcing, social media, data integration, and multiscale representations to support the Three-Dimensional Elevation Program (3DEP) and The National Map of the future of the U.S. Geological Survey.

Open-File Report↗

USGS1997

USGS Wildland Fire Workshop, EROS Data Center, Sioux Falls, SD, July 9-10, 1997

Report on the first workshop on USGS wildland fire expertise and capabilities. The workshop brought together operational and research representatives ofthe Federal fire management agencies to initiate a more comprehensive assessment ofthe USGS's capabilities and the appropriate role(s) for USGS interaction and involvement with the fire community. The report discusses how the USGS can play a significant role in wildland fire research and offer the fire community several unique capabilities. Foremost capability is the role as data producer; fire detection, assessment, ecological modeling, and rehabilitation and restoration relying on digital elevation models, digital line-graphs, national technical means, and image data are also discussed. The bureau offers technical expertise using geographic information systems (GIS), image processing and analysis, data base management and clearinghouse experience, and access to national technical means data. The bureau must exploit the USGS's expertise and prominence in wildland fire research. The USGS is an experienced player in fire ecology, fire assessment, and fuels loading research. Finally, the USGS also offers strong interdisciplinary experience in watershed and geologic landslide modeling, which is key for assessing postfire effects.

Report↗

USGS2022

Climate extremes as drivers of surface-water-quality trends in the United States

Surface-water quality can change in response to climate perturbations, such as changes in the frequency of heavy precipitation or droughts, through direct effects, such as dilution and concentration, and through physical processes, such as bank scour. Water quality might also change through indirect mechanisms, such as changing water demand or changes in runoff interaction with organic matter on the landscape. Many studies predict future changes in water-quality related to climate changes; however, fewer studies specifically document changes in water quality related to changes in climate, and they are usually limited in geographic scope. Recently, the U.S. Geological Survey's National Water-Quality Program reported nearly 12,000 trends in concentration and load for numerous water-quality constituents, including nutrients, sediment, major ions, and carbon. The results provide an unprecedented opportunity to examine sites across the conterminous United States for changes in water quality related to climate changes. We used published water-quality trends, modeled using the method of Weighted Regressions on Time, Season and Discharge, and calculated trends in climate extremes indices, using a modified Mann-Kendall trend method. The water-quality and the climate extremes trends were combined to identify areas in the conterminous United States where changes in climate extremes may have changed water quality. We investigated the water-quality trends in these areas to determine whether the trends related to changes in climate. We found that it was important to go beyond spatial correlation and examine trends on a watershed scale to investigate key drivers of trends. We found successful management practices in Iowa to reduce chloride concentrations, despite increases in icing days. For sediment, it appeared that management practices were having a larger effect than climate changes. For nutrients, complex forces affecting water quality make it difficult to unequivocally attribute water-quality change to climate change.

Science of the Total Environment↗

USGS2013

An evaluation of the individual components and accuracies associated with the determination of impervious area

The percentage of impervious surface area in a watershed has been widely recognized as a key indicator of terrestrial and aquatic ecosystem condition. Although the use of the impervious indicator is widespread, there is currently no consistent or mutually accepted method of computing impervious area and the approach of various commonly used techniques varies widely. Further, we do not have reliable information on the components of impervious surfaces, which would be critical in any future planning attempts to remediate problems associated with impervious surface coverage. In cooperation with the USGS Geographic Analysis and Monitoring Program (GAM) and The National Map, and the EPA Landscape Ecology Program, this collaborative research project utilized very high resolution imagery and GIS techniques to map and quantify the individual components of total impervious area in six urban/suburban watersheds in different parts of the United States. These data were served as ground reference, or "truth," for the evaluation for four techniques used to compute impervious area. The results show some important aspects about the component make-up of impervious cover and the variability of methods commonly used to compile this critical emerging indicator of ecosystem condition.

GIScience and Remote Sensing↗