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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 469 records · Page 26Linked to original sources
USGS1979

Satellites monitor Atlanta regional development

Since the adoption of a Regional Development Plan in 1975, the Atlanta Regional Commission has investigated methods for monitoring regional development patterns in a periodic, efficient manner. A promising approach appears to be the use of Landsat satellite data. In cooperation with the Earth Resources Observation Systems (EROS) Data Center, the commission used machine processing of digital temporal overlays of Landsat data collected in 1972, 1974 and 1976 to detect land use and land cover changes in the Atlanta metropolitan area. Results of the analysis revealed the conversion of forested and open space areas to residential, commercial and industrial land use in the urban-rural fringe zone from 1972 to 1974 and from 1974 to 1976. The study indicated that a land use and land cover change-detection program may be used to revise small-area forecasts of land use, population and employment made by planning models.

Atlanta, Georgia↗
USGS1983

U.S. Geological Survey land remote sensing activities

The U.S. Geological Survey (USGS) and the Department of the Interior (DOI) were among the earliest to recognize the potential applications of satellite land remote sensing for management of the country's land and water resources…not only as a user but also as a program participant responsible for final data processing, product generation, and data distribution. With guidance from Dr. William T. Pecora, who was the Survey's Director at that time and later Under Secretary of Interior, the Earth Resources Observation Systems (EROS) Program was established in 1966 as a focal point for these activities within the Department. Dr. Pecora was among the few who could envision a role for the Survey and the Department as active participants in programs yet to come--like the Landsat, Magsat, Seasat and, most recently, Shuttle Imaging Radar programs.

Pecora VIII Symposium↗
USGS1981

The role of remotely sensed and other spatial data for predictive modeling: the Umatilla, Oregon example

The U. S. Geological Survey's Earth Resources Observations Systems Data Center, in cooperation with the U.S. Army Corps of Engineers, Portland District, developed and tested techniques that used remotely sensed and other spatial data in predictive models to evaluate irrigation agriculture in the Umatilla River Basin of north-central Oregon. Landsat data and 1:24,000-scale aerial photographs were initially used to map he expansion of irrigate from 1973 to 1979 and to identify crops under irrigation in 1979. The crop data were then used with historical water requirement figures and digital topographic and hydrographic data to estimate water and power use for the 1979 irrigation season. The final project task involved production of a composite map of land suitability for irrigation development based on land cover (from Landsat), land-ownership, soil irrigability, slope gradient, and potential energy costs. The methods and data used in the study demonstrated the flexibility of remotely sensed and other spatial data as input for predictive models. When combined, they provided useful answers to complex questions facing resource managers.

Oregon↗
USGS1987

Overview of the land analysis system (LAS)

The Land Analysis System (LAS) is a fully integrated digital analysis system designed to support remote sensing, image processing, and geographic information systems research. LAS is being developed through a cooperative effort between the National Aeronautics and Space Administration Goddard Space Flight Center and the U. S. Geological Survey Earth Resources Observation Systems (EROS) Data Center. LAS has over 275 analysis modules capable to performing input and output, radiometric correction, geometric registration, signal processing, logical operations, data transformation, classification, spatial analysis, nominal filtering, conversion between raster and vector data types, and display manipulation of image and ancillary data. LAS is currently implant using the Transportable Applications Executive (TAE). While TAE was designed primarily to be transportable, it still provides the necessary components for a standard user interface, terminal handling, input and output services, display management, and intersystem communications. With TAE the analyst uses the same interface to the processing modules regardless of the host computer or operating system. LAS was originally implemented at EROS on a Digital Equipment Corporation computer system under the Virtual Memorial System operating system with DeAnza displays and is presently being converted to run on a Gould Power Node and Sun workstation under the Berkeley System Distribution UNIX operating system.

Conference Paper↗
USGS1987

A conceptual method for monitoring locust habitat

A procedure to map and monitor vegetation conditions in near-real time was developed at the United States Geological Survey;s Earth Resources Observation Systems Data Center for use in locust control efforts. Meteorological satellite dat were acquired daily for 3 weeks in October and November 1986 over a 1.4-million-square-kilometer study area centered on Botswana in southern Africa. Advanced Very High Resolution Radiometer data were screened to remove cloud-contaminated data and registered to a 1-kilometer geographic base. Each day the normalized difference vegetation index (NDVI) was calculated to determine the presence and relative amounts of green vegetation in the area. Over a 10-day cycle, subsequent dates of NDVI data were composited to fill in data removed by the cloud-screening process. At any pixel location, the maximum NDVI value was retained. At the end of the 10-day cycle, a composite vegetation-greenness map was produced and another cycle started. Greenness-change maps were produced by comparing two 10-day composite greenness images. Automated map production procedures were used to merge the NDVI image data with cartographic data (boundaries, roads, tick marks) digitized from 1:1,000,000-scale operational navigation charts. The vegetation-greenness map shoes the current distribution of vegetation in the region and can be used to locate potential locust breeding area. The change map shows areas where increases and decreases in greenness have occurred between processing cycles. Significant areas of locust damage in remote regions are characterized by an unexpected decrease in greenness. These maps can be used by locust control teams to efficiently target areas for reconnaissance. In general, the procedures and products have utility for resource managers who are required to monitor vegetation resources over large geographic regions.

Pecora XI Symposium↗
USGS1985

Comparison of fire fuel maps produced using MSS and AVHRR data

The fuel information, in support of the Bureau of Land Management's (BLM) national fire program, has been obtained through the manila interpretation of Landsat multi-spectral scanner images and digital image analysis of Advanced Very High Resolution Radiometer (AVHRR) data. The BLM, in cooperation with the Earth Resources Observation Systems Data Center, determined that the accuracy (approximately 90 percent overall) was similar for deriving fire fuel information for Malheur County in eastern Oregon using either approach, and for an area the size of Malheur County (6.4 million acres), the costs were about the same (0.19 cents per acre). But the cost per acre was substantially lower (0.04 cents) where digital analysis of AVHRR data were used to derive fire fuel information for a 42-million-acre area in eastern Oregon. Based on these results, the BLM is using digital analysis of AVHRR data to support its operational fire fuel mapping program.

Oregon↗
USGS1985

The use of low-resolution satellite image data for rangeland monitoring

The U.S. Geological Survey's Earth Resources Observation Systems (EROS) Data Center and the Bureau of Indian Affairs (BIA) jointly evaluated the used of Advanced Very High Resolution Radiometer (AVHRR) images for the calculate of normalized difference data as a green biomass indicator in an arid rangeland environment. The normalized difference data were compared to corresponding field-collected herbage data, and were used in a geographic information system to provide range management information.

Pecora 10 Symposium↗
USGS1993

Processing techniques for global land 1-km AVHRR data

The U.S. Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center (EDC) in cooperation with several international science organizations has developed techniques for processing daily Advanced Very High Resolution Radiometer (AVHRR) 1-km data of the entire global land surface. These techniques include orbital stitching, geometric rectification, radiometric calibration, and atmospheric correction. An orbital stitching algorithm was developed to combine consecutive observations acquired along an orbit by ground receiving stations into contiguous half-orbital segments. The geometric rectification process uses an AVHRR satellite model that contains modules for forward mapping, forward terrain correction, and inverse mapping with terrain correction. The correction is accomplished by using the hydrologic features coastlines and lakes from the Digital Chart of the World. These features are rasterized into the satellite projection and are matched to the AVHRR imagery using binary edge correlation techniques. The resulting coefficients are related to six attitude correction parameters: roll, roll rate, pitch, pitch rate, yaw, and altitude. The image can then be precision corrected to a variety of map projections and user-selected image frames. Because the AVHRR lacks onboard calibration for the optical wavelengths, a series of time-variant calibration coefficients derived from vicarious calibration methods and are used to model the degradation profile of the instruments. Reducing atmospheric effects on AVHRR data is important. A method has been develop that will remove the effects of molecular scattering and absorption from clear sky observations, using climatological measurements of ozone. Other methods to remove the effects of water vapor and aerosols are being investigated.

Pecora 12 Symposium↗
USGS1985

Digital to analog conversion and visual evaluation of Thematic Mapper data

As a part of the National Aeronautics and Space Administration Landsat D Image Data Quality Analysis Program, the Earth Resources Observation Systems Data Center (EDC) developed procedures to optimize the visual information content of Thematic Mapper data and evaluate the resulting photographic products by visual interpretation. A digital-to-analog transfer function was developed which would properly place the digital values on the most useable portion of a film response curve. Individual black-and-white transparencies generated using the resulting look-up tables were utilized in the production of color-composite images with varying band combinations. Four experienced photointerpreters ranked 2-cm-diameter (0. 75 inch) chips of selected image features of each band combination for ease of interpretability. A nonparametric rank-order test determined the significance of interpreter preference for the band combinations.

Journal of Imaging Technology↗
USGS1982

Refining Landsat classification results using digital terrain data

Scientists at the U.S. Geological Survey's Earth Resources Observation systems (EROS) Data Center have recently completed two land-cover mapping projects in which digital terrain data were used to refine Landsat classification results. Digital ter rain data were incorporated into the Landsat classification process using two different procedures that required developing decision criteria either subjectively or quantitatively. The subjective procedure was used in a vegetation mapping project in Arizona, and the quantitative procedure was used in a forest-fuels mapping project in Montana. By incorporating digital terrain data into the Landsat classification process, more spatially accurate landcover maps were produced for both projects.

Journal of Applied Photographic Engineering↗
USGS1986

Vegetation and terrain mapping in Alaska using Landsat MSS and digital terrain data

During the past 5 years, the U.S. Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center Field Office in Anchorage, Alaska has worked cooperatively with Federal and State resource management agencies to produce land-cover and terrain maps for 245 million acres of Alaska. The need for current land-cover information in Alaska comes principally from the mandates of the Alaska National Interest Lands Conservation Act (ANILCA), December 1980, which requires major land management agencies to prepare comprehensive management plans. The land-cover mapping projects integrate digital Landsat data, terrain data, aerial photographs, and field data. The resultant land-cover and terrain maps and associated data bases are used for resource assessment, management, and planning by many Alaskan agencies including the U.S. Fish and Wildlife Service, U.S. Forest Service, Bureau of Land Management, and Alaska Department of Natural Resources. Applications addressed through use of the digital land-cover and terrain data bases range from comprehensive refuge planning to multiphased sampling procedures designed to inventory vegetation statewide. The land-cover mapping programs in Alaska demonstrate the operational utility of digital Landsat data and have resulted in a new land-cover mapping program by the USGS National Mapping Division to compile 1:250,000-scale land-cover maps in Alaska using a common statewide land-cover map legend.

Alaska↗
USGS2011

Landsat science team meeting summary

The Landsat Science Team sponsored by the U.S. Geo- logical Survey (USGS) and NASA met in Mesa, AZ, from March 1-3, 2011. The team met in Mesa so that they could receive briefings and tours of the Landsat Data Continuity Mission (LDCM) spacecraft that is being developed by Orbital Sciences Corporation in nearby Gilbert, AZ.

The Earth Observer↗
USGS2009

NASA and USGS invest in invasive species modeling to evaluate habitat for Africanized Honey Bees

Invasive non-native species, such as plants, animals, and pathogens, have long been an interest to the U.S. Geological Survey (USGS) and NASA. Invasive species cause harm to our economy (around $120 B/year), the environment (e.g., replacing native biodiversity, forest pathogens negatively affecting carbon storage), and human health (e.g., plague, West Nile virus). Five years ago, the USGS and NASA formed a partnership to improve ecological forecasting capabilities for the early detection and containment of the highest priority invasive species. Scientists from NASA Goddard Space Flight Center (GSFC) and the Fort Collins Science Center developed a longterm strategy to integrate remote sensing capabilities, high-performance computing capabilities and new spatial modeling techniques to advance the science of ecological invasions [Schnase et al., 2002].

The Earth Observer↗
USGS1999

The Global Land-Cover Characteristics Database: The users' perspective

A unique global land-cover characteristics database developed by the U.S. Geological Survey has been available to users since mid-1997. Access to the data is through the internet under the EROS (Earth Resources Observation Systems) Data Center's home page (http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html). Since the release of the database, the data have been incorporated into various environmental research and modeling applications, including mapping global biodiversity, mesoscale climate simulations, carbon cycle modeling, and estimating habitat destruction. Since the early stages of the project, user feedback has provided a means to understand data utility in applications, garner suggestions for data improvements, and gain insights into the technical challenges faced by users. Synthesis of user feedback provided a means to generate a user profile and derive a list of applications-critical criteria for land-cover data. User suggestions have lead to revisions in the database, including label changes, alternative classification schemes, and additional projections for the data.

Photogrammetric Engineering and Remote Sensing↗
USGS2020

Development of a new open-source tool to map burned area and burn severity

Accurate and complete geospatial fire occurrence records are important in determining postfire effects, emissions, hazards, and fuel loading inventories. Currently, the Monitoring Trends in Burn Severity (MTBS) project maps the fire perimeter and burn severity of all large fires on public lands. Although the MTBS project maps a large proportion of the fire acreage, it maps a smaller proportion of the actual number of fires in the United States, thereby creating a data gap. To fill this data gap, fire scientists at the U.S. Geological Survey (USGS) Earth Resources Observation and Science Center (EROS; Sioux Falls, South Dakota) proposed creating an open-source Fire Mapping Tool (FMT; available at https://mtbs.gov/qgis-fire-mapping-tool) as part of a two-phase National Aeronautics and Space Administration (NASA) Applied Fire Science Program grant. Phase II developed the FMT to map burn perimeters and severity not included in the MTBS database. This paper will focus on Phase II and will explain the algorithms that enhance the FMT’s functionality, demonstrate fire mapping procedures, and provide an example comparison between MTBS analyst fire products and those mapped using the FMT. The overall goal in the production of the FMT was to provide a freely available tool that can be used to map fires anywhere in the world.

Washington↗
USGS1977

International training in remote sensing

The training and assistance programme at the Earth Resources Observation Systems (EROS) Data Center, Sioux Falls, South Dakota (United States of America), is designed to provide for the transfer of remote-sensing technology to land managers and resource specialists, both domestic and foreign. The programme does not emphasize research and development (i.e., sensor development, feasibility analysis, applications research etc.) nor does it provide services to operational remote-sensing applications projects. Instead, the objectives of the programme are to comprehend, interpret, assess and translate state-of-the-art remote-sensing techniques and transfer to users those techniques in such manner that they can be easily understood. The purpose of this paper is to describe briefly the user assistance programmes available at the EROS Data Center, with emphasis on the international activities.

Conference Paper↗