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Results for “Photogrammetric Engineering & Remote Sensing”

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At least 199 records · Page 11Linked to original sources
USGS1977

A radiometric interpretive legend for Landsat digital thematic maps

A legend is suggested for use with computer-generated thematic maps made from Landsat digital data that designates some of the radiometric characteristics of each thematic map unit as well as the described terrain attributes of each map unit. The relationship between spectral band and radiance for each map unit is shown by a two-dimensional polygon with the four Landsat multispectral scanner bands plotted on the ordinate and radiance levels on the abscissa. The resulting shape is colored to correspond with the map unit color, thus facilitating the recognition and understanding of the computer-generated map units.

Photogrammetric Engineering and Remote Sensing↗
USGS2000

Airborne laser mapping of Assateague National Seashore Beach

Results are presented from topographic surveys of the Assateague Island National Seashore using an airborne scanning laser altimeter and kinematic Global Positioning System (GPS) technology. The instrument used was the Airborne Topographic Mapper (ATM), developed by the NASA Arctic Ice Mapping (AIM) group from the Goddard Space Flight Center's Wallops Flight Facility. In November, 1995, and again in May, 1996, these topographic surveys were flown as a functionality check prior to conducting missions to measure the elevation of extensive sections of the Greenland Ice Sheet as part of NASA's Global Climate Change program. Differences between overlapping portions of both surveys are compared for quality control. An independent assessment of the accuracy of the ATM survey is provided by comparison to surface surveys which were conducted using standard techniques. The goal of these projects is to make these measurements to an accuracy of ± 10 cm. Differences between the fall 1995 and 1996 surveys provides an assessment of net changes in the beach morphology over an annual cycle.

Maryl↗
USGS1988

An integrated approach for automated cover-type mapping of large inaccessible areas in Alaska

The lack of any detailed cover type maps in the state necessitated that a rapid and accurate approach to be employed to develop maps for 329 million acres of Alaska within a seven-year period. This goal has been addressed by using an integrated approach to computer-aided analysis which combines efficient use of field data with the only consistent statewide spatial data sets available: Landsat multispectral scanner data, digital elevation data derived from 1:250 000-scale maps, and 1:60 000-scale color-infrared aerial photographs.

Alaska↗
USGS1988

Differences in visible and near-IR responses, and derived vegetation indices, for the NOAA-9 and NOAA-10 AVHRRs: a case study

This study evaluates the differences in the visible and near-IR responses of the Advanced Very High Resolution Radiometers (AVHRR) of the National Oceanic and Atmospheric Administration (NOAA)-9 and -10 satellites for coincident sample locations. The study also evaluates the differences in vegetation indices computed from those data. Data were acquired of the southeast portion of the United States for the 6 December 1986 daylight orbits of NOAA-9 and NOAA-10 satellites. The results suggest that, with appropriate gain and offset, the vegetation indices of the two sensor systems may be interchangeable for assessment of land surfaces.

Photogrammetric Engineering and Remote Sensing↗
USGS1988

NOAA-10 AVHRR thermal-infrared image of the Colorado Rocky Mountains

This month we demonstrate an example of the use of thermal infrared imagery to produce a relatively sharp surrogate shaded-relief image. The image shows one aspect of the drama and usefulness of calibrated thermal imagery that (because of compatible projection and pixel size) can be easily combined with other spectral bands of a satellite image. Such data can be enhanced in yet another way by stereoscopically combining two similar images with different orbital paths, such as was shown in the AVHRR column for January 1988.

Colorado↗
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↗
USGS1982

Evaluating depth to shallow groundwater using Heat Capacity Mapping Mission (HCMM) data

Four dates of Heat Capacity Mapping Mission (HCMM) data were analyzed to evaluate the utility of HCMM thermal data for evaluating depth to shallow groundwater. During the summer, shallow water tables can create lower soil temperatures throughout the diurnal temperature cycle. Because of large spatial and temporal ground cover variations, HCMM daytime radiometric temperatures alone did not correlate with water table depth. The radiometric temperatures consisted of radiance contributions from different crop canopies and their respective soil backgrounds. However, when surface soil temperatures were empirically estimated from HCMM temperatures and percent cover of each pixel, significant correlations were obtained between estimated soil temperatures and water table depth. Correlations increased as the season progressed and temperature gradients within the soil profile increased. However, estimated soil temperatures were also correlated with near-surface soil moisture since during the daytime, increasing soil moisture reduced surface soil temperature. Complementary effects of shallow water tables and soil moisture on daytime temperatures cannot be separated.

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↗
USGS1988

Conversion of Cartesian coordinates from and to Generalized Balanced Ternary addresses

Hexagonal grids have several advantages over square grids, such as a greater angular resolution and unambiguous connectivity. The Generalized Balanced Ternary (GBT) system is a spatial addressing method for hexagonal grids in which the hexagons are arranged in hierarchical aggregates, and which accommodates vector operations in GBT space. Efficient algorithms for converting Cartesian coordinates from and to GBT addresses are based on the dual representation of the hexagonal tessellation. The GBT-to-Cartesian algorithm is an order of magnitude faster than the Cartesian-to-GBT algorithm, the latter requiring interpolation and GBT addition for each digit of the generated GBT address.

Photogrammetric Engineering and Remote Sensing↗
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↗