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At least 163 records · Page 9Linked to original sources
USGS1987

Raster and vector processing for scanned linework

An investigation of raster editing techniques, including thinning, filling, and node detecting, was performed by using specialized software. The techniques were based on encoding the state of the 3-by-3 neighborhood surrounding each pixel into a single byte. A prototypical method for converting the edited raster linkwork into vectors was also developed. Once vector representations of the lines were formed, they were formatted as a Digital Line Graph, and further refined by deletion of nonessential vertices and by smoothing with a curve-fitting technique.

Photogrammetric Engineering and Remote Sensing↗
USGS1989

Image processing techniques for digital orthophotoquad production

Orthophotographs have long been recognized for their value as supplements or alternatives to standard maps. Recent trends towards digital cartography have resulted in efforts by the US Geological Survey to develop a digital orthophotoquad production system. Digital image files were created by scanning color infrared photographs on a microdensitometer. Rectification techniques were applied to remove tile and relief displacement, thereby creating digital orthophotos. Image mosaicking software was then used to join the rectified images, producing digital orthophotos in quadrangle format.

Photogrammetric Engineering and Remote Sensing↗
USGS1988

Extracting topographic structure from digital elevation data for geographic information-system analysis

Software tools have been developed at the U.S. Geological Survey's EROS Data Center to extract topographic structure and to delineate watersheds and overland flow paths from digital elevation models. The tools are specialpurpose FORTRAN programs interfaced with general-purpose raster and vector spatial analysis and relational data base management packages. The first phase of analysis is a conditioning phase that generates three data sets: the original OEM with depressions filled, a data set indicating the flow direction for each cell, and a flow accumulation data set in which each cell receives a value equal to the total number of cells that drain to it. The original OEM and these three derivative data sets can then be processed in a variety of ways to optionally delineate drainage networks, overland paths, watersheds for userspecified locations, sub-watersheds for the major tributaries of a drainage network, or pour point linkages between watersheds. The computer-generated drainage lines and watershed polygons and the pour point linkage information can be transferred to vector-based geographic information systems for futher analysis. Comparisons between these computergenerated features and their manually delineated counterparts generally show close agreement, indicating that these software tools will save analyst time spent in manual interpretation and digitizing.

Photogrammetric Engineering and Remote Sensing↗
USGS1980

Resolving the percentage of component terrains within single resolution elements

An approximate maximum likelihood technique employing a widely available (BMD) discriminant analysis program has been developed for resolving the percentage of component terrains within single resolution elements. The method employs all four channels of Landsat data simultaneously and does not require prior knowledge of the percentage of components in mixed pixels. For five test cases, the method proved to be superior to single band weighted average and linear regression techniques and permitted an estimate of the total area occupied by component terrains to within 6 percent of the true area covered. It is believed this accuracy should be sufficient for many geologic applications of Landsat multispectral data.

Photogrammetric Engineering and Remote Sensing↗
USGS1982

Assessing mesquite-grass vegetation condition from Landsat

Landsat multispectral scanner (MSS) band values, band ratios, and vegetation index models were compared with selected rangeland vegetation parameters collected at six test sites within the honey mesquitellotebushlmixed grass association in north-central Texas. The comparisons at four dates showed that two vegetation index models, TV16 and GVI, are highly correlated (P = 0.01) with green yield, green cover, and plant moisture content. The green vegetation index (GVZ) developed by Kauth and Thomas (1976), was highly correlated and superior to other models in relationship to wet green yield, dry green yield, and cured vegetation cover. TV16, developed by Rouse et al. (1974), was more highly correlated with green vegetation cover and vegetation moisture content. Both TV16 and GVI are superior to other models in their relationship with green cover. None of the Landsat MSS parameters tested was significantly correlated with dry total yield, percent bare ground, or moisture of the soil measured at the surface or at a 20 cm depth. I t is concluded that Landsat MSS data are sensitive to seasonal changes in vegetation growth conditions and inherent ecological differences within a relatively unqorm vegetationlsoil system.

Texas↗
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↗
USGS1986

Vegetation mapping of Nowitna National Wildlife Refuge, Alaska using Landsat MSS digital data

A Landsat-derived vegetation map was prepared for Nowitna National Wildlife Refuge. The refuge lies within the middle boreal subzone of north central Alaska. Seven major vegetation classes and sixteen subclasses were recognized: forest (closed needleleaf, open needleleaf, needleleaf woodland, mixed, and broadleaf); broadleaf scrub (lowland, alluvial, subalpine); dwarf scrub (prostrate dwarf shrub tundra, dwarf shrub-graminoid tussock peatland); herbaceous (graminoid bog, marsh and meadow); scarcely vegetated areas (scarcely vegetated scree and floodplain); water (clear, turbid); and other areas (mountain shadow). The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photointerpretation, and digital Landsat data. Major steps in the Landsat analysis involved preprocessing (geometric correction), derivation of statistical parameters for spectral classes, spectral class labeling of sample areas, preliminary classification of the entire study area using a maximum-likelihood algorithm, and final classification utilizing ancillary information such as digital elevation data. The final product is a 1:250,000-scale vegetation map representative of distinctive regional patterns and suitable for use in comprehensive conservation planning.

Alaska↗
USGS1988

Intermediate-scale vegetation mapping of Innoko National Wildlife Refuge, Alaska using Landsat MSS digital data

A Landsat-derived vegetation map was prepared for lnnoko National Wildlife Refuge. The refuge lies within the northern boreal subzone of northwestern central Alaska. Six major vegetation classes and 21 subclasses were recognized: forest (closed needleleaf, open needleleaf, needleleaf woodland, mixed, and broadleaf); broadleaf scrub (lowland, upland burn regeneration, subalpine); dwarf scrub (prostrate dwarf shrub tundra, erect dwarf shrub heath, dwarf shrub-graminoid peatland, dwarf shrub-graminoid tussock peatland, dwarf shrub raised bog with scattered trees, dwarf shrub-graminoid marsh); herbaceous (graminoid bog, graminoid marsh, graminoid tussock-dwarf shrub peatland); scarcely vegetated areas (scarcely vegetated scree and floodplain); and water (clear, sedimented). The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photo-interpretation, and digital Landsat data. Major steps in the Landsat analysis involved preprocessing (geometric correction), derivation of statistical parameters for spectral classes, spectral class labeling of sample areas, preliminary classification of the entire study area using a maximum-likelihood algorithm, and final classification utilizing ancillary information such as digital elevation data. The final product is 1:250,000-scale vegetation map representative of distinctive regional patterns and suitable for use in comprehensive conservation planning.

Alaska↗
USGS1980

Landsat wildland mapping accuracy

A Landsat-aided classification of ten wildland resource classes was developed for the Shivwits Plateau region of the Lake Mead National Recreation Area. Single stage cluster sampling (without replacement) was used to verify the accuracy of each class.

Arizona↗
USGS1982

Use of Landsat data to evaluate lesser prairie chicken habitats in western Oklahoma

Landsat digital data were used to evaluate lesser prairie chicken (Tympanuchus pallidicinctus) habitats in western Oklahoma. Data for 7 (4,144 ha) study areas, 4 in shinnery oak (Quercus havardii), and 3 in sand sagebrush (Artemisia filifolia) rangeland, were analyzed using the Interactive Digital Image Manipulation System at the EROS Center. In shinnery oak rangeland, density of displaying males was correlated positively with percentage of area in grassland classes and negatively correlated with the percentage in brushland classes. In sand sagebrush rangeland, density of displaying males was negatively, but not significantly correlated with percentage of area in bare soil and grassland classes, and positively, but not significantly correlated with percentage of area in brushland classes. The trends found between density of displaying males and the Landsat-generated resource classes closely parallel similar relationships found with field sampling techniques. Analysis of the Landsat digital data for this study cost 13.8 cents/ha. Because larger areas could have been analyzed with the same digital data, the unit cost for analysis would decline with increasingly larger areas.

Oklahoma↗
USGS2002

The national elevation data set

The NED is a seamless raster dataset from the USGS that fulfills many of the concepts of framework geospatial data as envisioned for the NSDI, allowing users to focus on analysis rather than data preparation. It is regularly maintained and updated, and it provides basic elevation data for many GIS applications. The NED is one of several seamless datasets that the USGS is making available through the Web. The techniques and approaches developed for producing, maintaining, and distributing the NED are the type that will be used for implementing the USGS National Map (http://nationalmap.usgs.gov/).

Photogrammetric Engineering and Remote Sensing↗
USGS2008

Towards monitoring land-cover and land-use changes at a global scale: the global land survey 2005

Land cover is a critical component of the Earth system, infl uencing land-atmosphere interactions, greenhouse gas fl uxes, ecosystem health, and availability of food, fi ber, and energy for human populations. The recent Integrated Global Observations of Land (IGOL) report calls for the generation of maps documenting global land cover at resolutions between 10m and 30m at least every fi ve years (Townshend et al., in press). Moreover, despite 35 years of Landsat observations, there has not been a unifi ed global analysis of land-cover trends nor has there been a global assessment of land-cover change at Landsat-like resolution. Since the 1990s, the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) have supported development of data sets based on global Landsat observations (Tucker et al., 2004). These land survey data sets, usually referred to as GeoCover ™, provide global, orthorectifi ed, typically cloud-free Landsat imagery centered on the years 1975, 1990, and 2000, with a preference for leaf-on conditions. Collectively, these data sets provided a consistent set of observations to assess land-cover changes at a decadal scale. These data are freely available via the Internet from the USGS Center for Earth Resources Observation and Science (EROS) (see http://earthexplorer.usgs.gov or http://glovis.usgs.gov). This has resulted in unprecedented downloads of data, which are widely used in scientifi c studies of land-cover change (e.g., Boone et al., 2007; Harris et al., 2005; Hilbert, 2006; Huang et al. 2007; Jantz et al., 2005, Kim et al., 2007; Leimgruber, 2005; Masek et al., 2006). NASA and USGS are continuing to support land-cover change research through the development of GLS2005 - an additional global Landsat assessment circa 20051 . Going beyond the earlier initiatives, this data set will establish a baseline for monitoring changes on a 5-year interval and will pave the way toward continuous global land-cover monitoring at Landsat-like resolution in the next decade.

Photogrammetric Engineering and Remote Sensing↗
USGS2004

An evaluation of gap-filled Landsat SLC-off imagery for wildland fire burn severity mapping

n May 31, 2003 unusual artifacts appeared within image data collected by the Enhanced Thematic Mapper plus (ETM+) instrument on-board the Landsat 7 spacecraft. The U.S. Geological Survey (USGS), with the support of NASA, has been working to find a means of compensating for the data gaps that result from a failure of the instrument’s scan line corrector (SLC). The SLC is an electromechanical device that compensates for the forward motion of the spacecraft by modifying the instrument’s optical path. The problem is likely due to a mechanical failure of the device for which there is no redundancy and that cannot be repaired or coaxed back into service. Further information regarding Landsat 7 and the SLC failure can be found at the Landsat Project home page (http://landsat7.usgs.gov).

Photogrammetric Engineering and Remote Sensing↗
USGS2007

Interferometric synthetic aperture radar (InSAR)—its past, present and future

Very simply, interferometric synthetic aperture radar (InSAR) involves the use of two or more synthetic aperture radar (SAR) images of the same area to extract landscape topography and its deformation patterns. A SAR system transmits electromagnetic waves at a wavelength that can range from a few millimeters to tens of centimeters and therefore can operate during day and night under all-weather conditions. Using SAR processing technique (Curlander and McDonough, 1991), both the intensity and phase of the reflected (or backscattered) radar signal of each ground resolution element (a few meters to tens of meters) can be calculated in the form of a complex-valued SAR image that represents the reflectivity of the ground surface. The amplitude or intensity of the SAR image is determined primarily by terrain slope, surface roughness, and dielectric constants, whereas the phase of the SAR image is determined primarily by the distance between the satellite antenna and the ground targets. InSAR imaging utilizes the interaction of electromagnetic waves, referred to as interference, to measure precise distances between the satellite antenna and ground resolution elements to derive landscape topography and its subtle change in elevation.

Photogrammetric Engineering and Remote Sensing↗
USGS2004

Filling Landsat ETM+ SLC-off gaps using a segmentation model approach

The purpose of this article is to present a methodology for filling Landsat Scan Line Corrector (SLC)-off gaps with same-scene spectral data guided by a segmentation model. Failure of the SLC on the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) instrument resulted in a loss of approximately 25 percent of the spectral data. The missing data span across most of the image with scan gaps varying in size from two pixels near the center of the image to 14 pixels along the east and west edges. Even with the scan gaps, the radiometric and geometric qualities of the remaining portions of the image still meet design specifications and therefore contain useful information (see http:// landsat7.usgs.gov for additional information). The U.S. Geological Survey EROS Data Center (EDC) is evaluating several techniques to fill the gaps in SLC-off data to enhance the usability of the imagery (Howard and Lacasse 2004) (PE&RS, August 2004). The method presented here uses a segmentation model approach that allows for same-scene spectral data to be used to fill the gaps. The segment model is generated from a complete satellite image with no missing spectral data (e.g., Landsat 5, Landsat 7 SLCon, SPOT). The model is overlaid on the Landsat SLC-off image, and the missing data within the gaps are then estimated using SLC-off spectral data that intersect the segment boundary. A major advantage of this approach is that the gaps are filled using spectral data derived from the same SLC-off satellite image.

Photogrammetric Engineering and Remote Sensing↗
USGS2005

Recent U.S. Geological Survey applications of Lidar

As lidar (light detection and ranging) technology matures, more applications are being explored by U.S. Geological Survey (USGS) scientists throughout the Nation, both in collaboration with other Federal agencies and alone in support of USGS natural-hazards research (Crane et al., 2004). As the technology continues to improve and evolve, USGS scientists are finding new and unique methods to use and represent high-resolution lidar data, and new ways to make these data and derived information publicly available. Different lidar sensors and configurations have offered opportunities to use high-resolution elevation data for a variety of projects across all disciplines of the USGS. The following examples are just a few of the diverse projects in the USGS where lidar data is being used.

Photogrammetric Engineering and Remote Sensing↗
USGS2008

The need for a national LIDAR dataset

On May 21st and 22nd 2008, the U.S. Geological Survey (USGS), the National Aeronautics and Space Administration (NASA), and the Association of American State Geologists (AASG) hosted the Second National Light Detection and Ranging (Lidar) Initiative Strategy Meeting at USGS Headquarters in Reston, Virginia. The USGS is taking the lead in cooperation with many partners to design and implement a future high-resolution National Lidar Dataset. Initial work is focused on determining viability, developing requirements and specifi cations, establishing what types of information contained in a lidar signal are most important, and identifying key stakeholders and their respective roles. In February 2007, USGS hosted the fi rst National Lidar Initiative Strategy Meeting at USGS Headquarters in Virginia. The presentations and a published summary report from the fi rst meeting can be found on the Center for Lidar Information Coordination and Knowledge (CLICK) Website: http://lidar.cr.usgs.gov. The fi rst meeting demonstrated the public need for consistent lidar data at the national scale. The goals of the second meeting were to further expand on the ideas and information developed in the fi rst meeting, to bring more stakeholders together, to both refi ne and expand on the requirements and capabilities needed, and to discuss an organizational and funding approach for an initiative of this magnitude. The approximately 200 participants represented Federal, State, local, commercial and academic interests. The second meeting included a public solicitation for presentations and posters to better democratize the workshop. All of the oral presentation abstracts that were submitted were accepted, and the 25 poster submissions augmented and expanded upon the oral presentations. The presentations from this second meeting, including audio, can be found on CLICK at http://lidar.cr.usgs.gov/national_lidar_2008.php. Based on the presentations and the discussion sessions, the following points were emphasized throughout the meeting

Photogrammetric Engineering and Remote Sensing↗