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At least 469 records · Page 26Linked to original sources

USGS2012

Burn severity mapping in Australia 2009

In 2009, the Victoria Department of Sustainability and Environment estimated approximately 430,000 hectares of Victoria Australia were burned by numerous bushfires. Burned Area Emergency Response (BAER) teams from the United States were deployed to Victoria to assist local fire managers. The U.S. Geological Survey Earth Resources Observation and Science Center (USGS/EROS) and U.S. Forest Service Remote Sensing Applications Center (USFS/RSAC) aided the support effort by providing satellite-derived "soil burn severity " maps for over 280,000 burned hectares. In the United States, BAER teams are assembled to make rapid assessments of burned lands to identify potential hazards to public health and property. An early step in the assessment process is the creation of a soil burn severity map used to identify hazard areas and prioritize treatment locations. These maps are developed primarily using Landsat satellite imagery and the differenced Normalized Burn Ratio (dNBR) algorithm.

Conference Paper↗

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↗

USGS2013

Metrically preserving the USGS aerial film archive

Since 1972, the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota, has provided fi lm-based products to the public. EROS is home to an archive of 12 million frames of analog photography ranging from 1937 to the present. The archive contains collections from both aerial and satellite platforms including programs such as the National High Altitude Program (NHAP), National Aerial Photography Program (NAPP), U.S. Antarctic Resource Center (USARC), Declass 1(CORONA, ARGON, and LANYARD), Declass 2 (KH-7 and KH-9), and Landsat (1972 – 1992, Landsat 1–5).

Photogrammetric Engineering and Remote Sensing↗

USGS2010

Appraising U.S. Geological Survey science records

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center has legislative charters to preserve and make accessible land remote sensing records important to the United States. This essay explains the appraisal process developed by EROS to ensure the science records it holds and those offered to it align with those charters. The justifications behind the questions employed to weed and to complement the EROS archive are explained along with the literature reviewed supporting their inclusion. Appraisal results are listed by individual collection and include the recommendations accepted by EROS management.

Archival Issues↗

USGS1967

Explorers from space

The statement that a new era in exploration is opening will almost surely bring to mind the venturing of man into space and the ever more imminent exploration of the moon. The reference here, however, is to exploration of earth itself and to the unique capabilities for study of the earth that space technology will provide. Demands for water, minerals, energy, food, and for working, living and recreational space are outrunning our ability to meet them by traditional methods. In order to satisfy these demands, it is necessary now, just as it has been in the past, to look to the activities, the instruments, and the technologies that in part create the pressures for aid in meeting them. Studies being made at the U.S. Geological Survey and elsewhere of the potential applications of remote sensors in space to earth resources research indicate that now, at last, it will be possible to approach solutions on a regional or global basis. This paper discusses the plans for an Earth Resources Observational Satellites Program which will be designed for that purpose.

Journal of Geological Education↗

USGS1977

Urban and regional land use change detected by using Landsat data

The Atlanta Regional Commission and the Earth Resources Observation Systems Data Center participated in a demonstration of the use of Landsat digital data to detect land use change in the Atlanta, Ga., area. Temporal overlays combining Landsat band-5 data from October 1972 and 1974 were made by using the General Electric Image 100 system. The 1972 data were divided by the 1974 data, and low ratios indicate areas where land use and land cover had changed. These low ratios were classified into a land-use-change theme. A classification based on the use of the four bands of the multispectral scanner data, taken in 1974, yielded six land use categories: (1) Commercial-industrial-multifamily, (2) single-family residential, (3) cleared land, (4) open space, (5) forested land, and (6) water. These six 1974 categories and the change theme were combined to determine changes between 1972 and 1974.

Georgia↗

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

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↗