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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

The influence of the number of ground control points on the scene-to-map registration accuracy

The optimum number of ground control points required to rectify a full scene or a portion of a LANDSAT MSS scene was investigated using data from southeastern Louisiana/southwestern Mississippi and eastern Kansas. The ground control points utilized were randomly distributed across the partial or full scene. This work suggest that 24 round control points are more than adequate to rectify a partial or full scene of LANDSAT MSS data. The error incurred in choosing ground control points representing artificial versus natural features was also studied.

Dow, D. D.↗
NASA NTRS1985

Landsat Thematic Mapper geodetic accuracy - Implications for geocoded map compatibility

The geodetic accuracy and geometric fidelity of corrected thematic mapper (TM) imagery are evaluated. The positional accuracy requirements for the TM are for a single band to within 0.5 pixels of true earth-surface locations at any point over 90 percent of the image and for interband registration to within 0.3 pixel tolerance over 90 percent of the data. Landsat 4 and 5 TM data are analyzed to investigate: (1) single band geometric integrity, (2) 30 m resolution interband registration; (3) image to image conformity; (4) image to ground conformity; and (5) image projective geometry conformity to a mapped earth geometry. The procedures used to study these characteristics are described. The data reveal that Landsat TM digital data met or exceed map accuracy standards for horizontal control.

Bryant, N. A.↗
NASA NTRS1985

Accuracy of geologic maps produced from Landsat data

Remote sensing techniques are now being applied to space-acquired data for use in preparing geologic maps, at least at the reconnaissance level, when maps produced from Landsat multispectral scanner data are compared with those made by conventional ground/aerial techniques, accuracies of the Landsat maps fall in the 40-60 percent range relative to their conventional counterparts. A study of map accuracy achieved with Landsat-4 Thematic Mapper (TM) data indicates a 10-15 percent improvement in this range. Results from TM scenes for Death Valley, California and the Waterpocket Fold, Utah are evaluated in this paper. While accuracy values should improve even more when corrections for topographic effects are made, there appears to be an upper limit to accuracy (not yet determined), owing to a fundamental difference between geologic maps (which show stratigraphic unit distribution below the regolith) and Landsat-derived rock units maps (which identify rock and regolith types at the surface). However, preliminary results from the Utah study indicate a marked improvement and accuracy to better than 80 percent when high spatial resolution TM-equivalent data from an aircraft mission are used.

Short, N. M.↗
NASA NTRS1982

Cartographic mapping study

The errors associated with planimetric mapping of the United States using satellite remote sensing techniques are analyzed. Assumptions concerning the state of the art achievable for satellite mapping systems and platforms in the 1995 time frame are made. An analysis of these performance parameters is made using an interactive cartographic satellite computer model, after first validating the model using LANDSAT 1 through 3 performance parameters. An investigation of current large scale (1:24,000) US National mapping techniques is made. Using the results of this investigation, and current national mapping accuracy standards, the 1995 satellite mapping system is evaluated for its ability to meet US mapping standards for planimetric and topographic mapping at scales of 1:24,000 and smaller.

Wilson, C.↗
NASA NTRS1976

Applications of space technology to developing nations

The use of imagery from the Landsat spacecraft for the monitoring and management of natural resources in developing countries is discussed. The Landsat imagery can be used to make cartographic maps at scales of 1:250,000 which meet the US National Map Accuracy Standards, providing a means of map updating to correct for river meanders or changing shorelines. The Landsat data can also be used in defining and measuring agricultural areas, identifying pest breeding areas, and monitoring irrigation practices and crop performance. Total volume estimates can be obtained in many cases for surface bodies of water, and subsurface water supplies can be detected from changes in vegetation in some instances.

Freden, S. C.↗
NASA NTRS1982

Familiarization with LANDSAT imagery

Learning objectives of the activities provided include: (1) reading the annotation of a LANDSAT image; (2) becoming acquainted with the characteristics of 1:1,000,000 scale transparencies and prints of MSS images; (3) noting the general information visible in LANDSAT photo products; (4) observing changes of appearance of any ground feature or class in the black and white images made from the four MSS bands and the characteristic color of each class in color composites; (5) determining the degree to which a LANDSAT image meets map accuracy standards and can be fitted to map projections; (6) assessing the effects of LANDSAT enlargements and scale changes and of the limitations of satellite resolution relative to aerial photos; (7) observing the influence of time of acquisition (season) on a scene; (8) getting a feel for image quality as dependent on processing and photoreproduction; (9) appreciating the characteristics of the RBV and thermal band imagery obtained from LANDSAT-3; and (10) becoming familiar with certain attributes of adjacent LANDSAT images which permit them to be joined in mosaics and to be viewed in stereo.

Source record↗
NASA NTRS1976

Side-looking radar mosaicking experiment

A block of 24 overlapping synthetic aperture side-looking radar images flown over a well mapped area of about 90,000 sq km provided an opportunity to evaluate the mapping accuracy achieved in current radar mosaicking projects. The maps of scale 1:24,000 that are available in the imaged area permitted the study of the geometric errors of the radar mosaics and of individual radar strips. An estimate was obtained for the effect of the distribution and density of ground control points and for the accuracy of different mosaicking methods that are currently employed with synthetic aperture radar images. It is shown that a successful radar mosaicking process requires the elimination of image errors of up to several kilometers. These errors are introduced as a result of the limited precision of the inertial aircraft navigation. An example of a radar mapping effort in which the navigation errors could be eliminated is presented. The resulting radar mosaics have residual RMS mapping errors of planimetry of about plus or minus 150 m.

Leberl, F.↗
NASA NTRS2001

Multi-resolution mapping using surface, descent and orbit images

Our objective is to produce high-accuracy maps of the terrain elevation at landing sites on planetary bodies through the use of all available image data. These technologies are important for performing rover navigation in future space missions and the maps provide a tool for coordinating rovers in a robotic colony.

localization↗
NASA NTRS1974

Study of USGS/NASA land use classification system

It is known from several previous investigations that many categories of land-use can be mapped via computer processing of Earth Resources Technology Satellite data. The results are presented of one such experiment using the USGS/NASA land-use classification system. Douglas County, Georgia, was chosen as the test site for this project. It was chosen primarily because of its recent rapid growth and future growth potential. Results of the investigation indicate an overall land-use mapping accuracy of 67% with higher accuracies in rural areas and lower accuracies in urban areas. It is estimated, however, that 95% of the State of Georgia could be mapped by these techniques with an accuracy of 80% to 90%.

Spann, G. W.↗
NASA NTRS1973

Overall evaluation of ERTS imagery for cartographic application

The author has identified the following significant results. The apparently successful fitting of a plane coordinate (UTM) grid to an ERTS-1 bulk image represents a breakthrough of potential economic importance. If such results continue to be attained it means that ERTS-1 imagery even in bulk form can be reproduced as planimetric image maps that meet National Map Accuracy Standards up to the 1:250,000 scale. Such maps permit positions of image points to be geodetically defined to within 75 meters (rms). Previous efforts to map with ERTS-1 images resulted in errors approaching 300 meters (rms).

Colvocoresses, A. P.↗
NASA NTRS1973

Investigation of the utility of ERTS-1 imagery for updating land use and resource data in Guatemala

The author has identified the following significant results. An intensive analysis of the imagery received has been completed and findings are reported. Conclusions are restricted by receipt of only limited amounts of cloud-free coverage of test areas. In most cases the interpretation findings were as anticipated from previous experience with multiband images. Band 7 provides promising indication of some economically important environmental communities. It also permits viewing through thin cirrus cloud layers for features of medium to high contrast. Band 4 provides information of submerged reefs and of movement of suspended sediment bodies in water areas. ERTS-1 bulk images have positional mapping accuracy adequate for representation at 1:1,000,000 scale maps. Cloud cover is a true constraint to useable satellite coverage.

Garcia, L. E.↗
NASA NTRS1984

An automated land-use mapping comparison of the Bayesian maximum likelihood and linear discriminant analysis algorithms

The Bayesian maximum likelihood parametric classifier has been tested against the data-based formulation designated 'linear discrimination analysis', using the 'GLIKE' decision and "CLASSIFY' classification algorithms in the Landsat Mapping System. Identical supervised training sets, USGS land use/land cover classes, and various combinations of Landsat image and ancilliary geodata variables, were used to compare the algorithms' thematic mapping accuracy on a single-date summer subscene, with a cellularized USGS land use map of the same time frame furnishing the ground truth reference. CLASSIFY, which accepts a priori class probabilities, is found to be more accurate than GLIKE, which assumes equal class occurrences, for all three mapping variable sets and both levels of detail. These results may be generalized to direct accuracy, time, cost, and flexibility advantages of linear discriminant analysis over Bayesian methods.

Tom, C. H.↗
NASA NTRS1980

An evaluation of satellite data for estimating the area of small forestland in the southern lower peninsula of Michigan

A winter black and white band 5, a winter color, a fall color, and a diazo color composite of the fall scene were used to assess the use and potential of LANDSAT images for mapping and estimating acreage of small scattered forest tracts in Barry County, Michigan. Forests as small as 2.5 acres were mapped from each LANDSAT data source. The maps for each image were compared with an available forest-type map. Mapping errors detected were categorized as boundary and identification errors. The most frequently misclassified areas were agriculture lands, treed-bogs, brushlands and lowland and mixed hardwood stands. Stocking level affected interpretation more than stand size. The overall level of the interpretation performance was expressed through the estimation of classification, interpretation, and mapping accuracies. These accuracies ranged from 74 between 74% and 98%. Considering errors, accuracy, and cost, winter color imagery is the best LANDSAT alternative for mapping small forest tracts. However, since the availability of cloud-free winter images of the study area is significantly lower than images for other seasons, a diazo enhanced image of a fall scene is recommended as the best next best alternative.

Karteris, M. A.↗
NASA NTRS1998

Characteristics of Forests in Western Sayani Mountains, Siberia from SAR Data

This paper investigated the possibility of using spaceborne radar data to map forest types and logging in the mountainous Western Sayani area in Siberia. L and C band HH, HV, and VV polarized images from the Shuttle Imaging Radar-C instrument were used in the study. Techniques to reduce topographic effects in the radar images were investigated. These included radiometric correction using illumination angle inferred from a digital elevation model, and reducing apparent effects of topography through band ratios. Forest classification was performed after terrain correction utilizing typical supervised techniques and principal component analyses. An ancillary data set of local elevations was also used to improve the forest classification. Map accuracy for each technique was estimated for training sites based on Russian forestry maps, satellite imagery and field measurements. The results indicate that it is necessary to correct for topography when attempting to classify forests in mountainous terrain. Radiometric correction based on a DEM (Digital Elevation Model) improved classification results but required reducing the SAR (Synthetic Aperture Radar) resolution to match the DEM. Using ratios of SAR channels that include cross-polarization improved classification and

Ranson, K. Jon↗
NASA NTRS1984

Cartographic accuracy of Landsat-4 MSS and TM image data

Investigations of the cartographic quality of Landsat-4 MSS and TM image data in CCT-p formats have produced rectification accuracies (rmse/xy/ values) of + or - 2/3 to + or - 1 data pixel for both whole and subscene areas using polynomials of the first through third degree. In order to achieve these accuracies with MSS data, 15 or more Ground Control Points (GCPs) are required, whereas with the TM data sets as few as 5-10 GCPs will suffice. Factors which limit the cartographic rectification accuracies of the Landsat-4 data include: (1) spatial resolution of the data; (2) map and digitizing errors; and (3) terrain relief. Of these factors, data resolution is the most significant, limiting the location of GCPs to about + or - 0.5 pixel. Horizontal displacements due to terrain relief can be minimized by selecting GCPs at or near midrange elevations. Overall, the representative rmse(xy) values of + or - 25 and + or - 55 m for TM and MSS data sets are within U.S. National Map Accuracy Standards for cartographic products of 1:100,000 and 1:200,000 scale, respectively.

Welch, R.↗
NASA NTRS1985

An analysis of Landsat Thematic Mapper P-Product internal geometry and conformity to earth surface geometry

Performance requirements regarding geometric accuracy have been defined in terms of end product goals, but until recently no precise details have been given concerning the conditions under which that accuracy is to be achieved. In order to achieve higher spatial and spectral resolutions, the Thematic Mapper (TM) sensor was designed to image in both forward and reverse mirror sweeps in two separate focal planes. Both hardware and software have been augmented and changed during the course of the Landsat TM developments to achieve improved geometric accuracy. An investigation has been conducted to determine if the TM meets the National Map Accuracy Standards for geometric accuracy at larger scales. It was found that TM imagery, in terms of geometry, has come close to, and in some cases exceeded, its stringent specifications.

Bryant, N. A.↗
NASA NTRS2003

Mathematical Inversion of Lightning Data: Techniques and Applications

A survey of some interesting mathematical inversion studies dealing with radio, optical, and electrostatic measurements of lightning are presented. A discussion of why NASA is interested in lightning, what specific physical properties of lightning are retrieved, and what mathematical techniques are used to perform the retrievals are discussed. In particular, a relatively new multi-station VHF time-of-arrival (TOA) antenna network is now on-line in Northern Alabama and will be discussed. The network, called the Lightning Mapping Array (LMA), employs GPS timing and detects VHF radiation from discrete segments (effectively point emitters) that comprise the channel of lightning strokes within cloud and ground flashes. The LMA supports on-going ground-validation activities of the low Earth orbiting Lightning Imaging Sensor (LIS) satellite developed at NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama. The LMA also provides detailed studies of the distribution and evolution of thunderstorms and lightning in the Tennessee Valley, and offers interesting comparisons with other meteorological/geophysical datasets. In order to take full advantage of these benefits, it is essential that the LMA channel mapping accuracy (in both space and time) be fully characterized and optimized. A new channel mapping retrieval algorithm is introduced for this purpose. To characterize the spatial distribution of retrieval errors, the algorithm has been applied to analyze literally tens of millions of computer-simulated lightning VHF point sources that have been placed at various ranges, azimuths, and altitudes relative to the LMA network. Statistical results are conveniently summarized in high-resolution, color-coded, error maps.

Koshak, William↗
NASA NTRS2021

Semantic Segmentation of High-Resolution Satellite Imagery using Generative Adversarial Networks with Progressive Growing

With increase in urbanization and Earth Sciences research into urban areas, the need to quickly and accurately segment urban rooftop maps has never been greater. Cur-rent machine learning techniques struggle to produce high accuracy maps in dense urban zones where there is high image noise and foot print overlap. In this paper, we evaluate a training methodology for pixel-wise segmentation for high resolution satellite imagery using progressive growing of generative adversarial networks as a solution. We apply our model to segmenting building rooftops and compare these results to conventional methods for rooftop segmentation. We evaluate our approach using the SpaceNet version 2 and xView datasets. Our experiments show that for SpaceNet, progressive Generative Adversarial Network (GAN) training achieved a test accuracy of 93% compared to 89% for traditional GAN training and 87% for U-Net architecture, while for xView, we achieved 71% accuracy using progressive GAN training compared to 69% through traditional GAN training and 65% using U-Net.

Semantic↗