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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Evaluation of Skylab data for land use mapping

Skylab multispectral scanner data, digitized Skylab color IR photography, digitized Skylab black and white multiband photography, and Earth Resources Technology Satellite (ERTS) multispectral scanner data collected within a twenty-four hour time period over an area in south-central Indiana near Bloomington on June 9 and 10, 1973, were compared in a machine-aided land use analysis of the area. The overall classification performance results, obtained with nine land use classes were 87% correct classification using the 'best' 4 channels of the Skylab multispectral scanner, 80% for the channels on the Skylab multispectra scanner, which are spectrally comparable to the ERTS multispectral scanner, 88% for the ERTS multispectral scanner, 83% for the digitized color IR photography, and 76% for the digitized black and white multiband photography. The results indicate that the Skylab multispectral scanner may yield even higher classification accuracies when a noise filtered multispectral scanner data set becomes available in the near future.

Biehl, L. L.↗
NASA NTRS1978

The application of remote sensing technology to the solution of problems in the management of resources in Indiana

The author has identified the following significant results. Of the sampling techniques considered, a combination soil mapping and area sampling offered the most practical method for gathering soils data. Using the dot grid count, a relative percentage composition of soils can be calculated for each spectral class. From these percentages, a legend describing the dominant soils and inclusions can be developed. Interval drainage class seemed to be correlated with magnitude. For every parent material area, the more poorly drained soils had a lower magnitude of reflectance. Soil spectral classes seemed to be predominantly one internal drainage class.

Weismiller, R. A.↗
NASA NTRS1992

The search for crustal resources - MAGSAT and beyond

In the decade since global satellite magnetic field data have been available from MAGSAT, notable progress has been made in processing these data for purposes of mapping crustal anomalies. Several regional magnetic anomaly maps compiled using these new techniques (e.g. Kursk region, U.S.S.R.; central Africa; Kiruna, Sweden; and the U.S.A. midcontinent) provide insight into the nature and tectonic evolution of the crust that contribute to conceptual crustal models useful in regional resource exploration. A recent mail survey of geopotential-field specialists involved in resource exploration indicates interest in MAGSAT data and future satellite missions with improved resolution. It is apparent that magnetic anomalies derived from satellite observations can aid in the search for crustal resources.

Taylor, P. T.↗
NASA NTRS1982

Potential Role of Land Use and Land Cover Information in Powerplant Siting: Example of Three Mile Island

Selecting a site for a nuclear powerplant can be helped by digitizing land use and land cover data, population data, and other pertinent data sets, and then placing them in a geographic information system. Such a system begins with a set of standardized maps for location reference and then provides for retrieval and analysis of spatial data keyed to the maps. This makes possible thematic mapping by computer, or interactive visual display for decisionmaking. It also permits correlating land use area measurements with census and other data (such as fallout dosages), and the updating of all data sets. The system is thus a tool for dealing with resource management problems and for analyzing the interaction between people and their environment. An explanation of a computer-plotted map of land use and cover for Three Mile Island and vicinity is given.

Wray, J. R.↗
NASA NTRS1983

Forest Resource Information System (FRIS)

The technological and economical feasibility of using multispectral digital image data as acquired from the LANDSAT satellites in an ongoing operational forest information system was evaluated. Computer compatible multispectral scanner data secured from the LANDSAT satellites were demonstrated to be a significant contributor to ongoing information systems by providing the added dimensions of synoptic and repeat coverage of the Earth's surface. Major forest cover types of conifer, deciduous, mixed conifer-deciduous and non-forest, were classified well within the bounds of the statistical accuracy of the ground sample. Further, when overlayed with existing maps, the acreage of cover type retains a high level of positional integrity. Maps were digitized by a graphics design system, overlayed and registered onto LANDSAT imagery such that the map data with associated attributes were displayed on the image. Once classified, the analysis results were converted back to map form as a cover type of information. Existing tabular information as represented by inventory is registered geographically to the map base through a vendor provided data management system. The notion of a geographical reference base (map) providing the framework to which imagery and tabular data bases are registered and where each of the three functions of imagery, maps and inventory can be accessed singly or in combination is the very essence of the forest resource information system design.

Source record↗
NASA NTRS1974

Coastal wetlands analysis from ERTS MSS digital data and field spectral measurements

Classification, delineation and evaluation of coastal wetlands can be made on the basis of major vegetative associations. To produce wetland maps, two vegetation-analysis look-up tables were developed for use in the ERTS ANALYSIS System. These look-up tables are based on Earth Resources Technology Satellite (ERTS) digital values in Multispectral Scanner (MSS) bands 4, 5, and 7 and were developed using seasonal spectral reflectance measurements from field observations. Computer-generated maps at an approximate scale of 1:20,000 were produced for the primary test site, Chincoteague Marsh, Virginia. There is a high degree of accuracy in the identification of wetland features and plant associations. The classification was also tested on other Atlantic coast salt marshes and a brackish marsh in the Chesapeake Bay.

Carter, V.↗
NASA NTRS1973

Use of ERTS data for a multidisciplinary analysis of Michigan resources

The author has identified the following significant results. A computerized procedure has been developed to correlate coordinates from topographic maps and/or aerial photographs with ERTS data coordinates. Application to data from other multispectral scanners is anticipated. In the procedure, a map transformation from earth coordinates to ERTS point and line numbers is calculated using selected ground control points and the method of least squares. The map transformation is then applied to the earth coordinates of selected areas to obtain the corresponding ERTS point and line numbers. An optional provision allows moving the boundaries of the plots inwards by variable distances (typically half a resolution element) so the selected pixels will not overlap adjacent features.

Anderson, A. L.↗
NASA NTRS1973

Mapping coastal vegetation, land use and environmental impact from ERTS-1

The author has identified the following significant results. Vegetation map overlays at a scale of 1:24,000 compiled by multispectral analysis from NASA aircraft imagery for all of Delaware's wetlands are being used as ground truth for ERTS-1 mapping and by state agencies for wetlands management. Six major vegetation species were discriminated and mapped, including percentages of minor species. Analogue enhancements of wetlands vegetation and dredge-fill operations have been produced using General Electric's GEMS data processing and ERTS-1 false color composites. Digital, thematic land use, and vegetation mapping of entire Delaware Bay area is in progress using Bendix Corporation's Earth Resources Data System and ERTS-1 digital tapes. Statistical evaluation of target-group selection reliability has been completed. Three papers have been published on ERTS-1 coastal vegetation and land use. Local and state officials are participating in the ERTS-1 program as co-investigators.

Klemas, V.↗
NASA NTRS1975

CARETS: A prototype regional environmental information system. Volume 2, parts A and B: Norfolk and environs; a land use perspective

The author has identified the following significant results. The Norfolk-Portsmouth metropolitan statistical area in southeastern Virginia was the site of intensive testing of a number of land resources assessment methods. Land use and land cover data at three levels of detail were derived by manual image interpretation from both aircraft and satellite sources and used to characterize the 1,766 sq km (682 sq mi) area from the perspective of its various resource-related activities and problems. Measurements at level 1 from 1:100, 000 scale maps revealed 42 percent of the test area (excluding bays and estuaries) to be forest, 28 percent agriculture, 23 percent urban and built-up, 4 percent nonforested wetlands, and 2 percent water. At the same scale and level of detail, 10 percent of the area underwent change from one land use category to another in the period 1959-70, 62 percent of which involved the relatively irreversible change from forest or agriculture to urban uses.

Norfolk-Portsmouth SHSA↗
NASA NTRS1993

Domain connectivity among systems of overset grids

This progress report describes research performed to achieve algorithmic improvements in the use of overset grids for the computation of unsteady flowfields about geometrically complex and moving component configurations. A hole-map computational method is detailed that reduces computational demand and corresponding demand on human resources. Results indicate that the method is both efficient and flexible for use in complex simulation cases. Tests were performed on shuttle orbiter/external tank, wing/store, and V-22 tilt-rotor configurations. The number of simulated points and the corresponding time on a SGI 4D-210 workstation are presented.

Meakin, Robert L.↗
NASA NTRS2001

Road Extraction from AVIRIS Using Spectral Mixture and Q-Tree Filter Techniques

Accurate road location and condition information are of primary importance in road infrastructure management. Additionally, spatially accurate and up-to-date road networks are essential in ambulance and rescue dispatch in emergency situations. However, accurate road infrastructure databases do not exist for vast areas, particularly in areas with rapid expansion. Currently, the US Department of Transportation (USDOT) extends great effort in field Global Positioning System (GPS) mapping and condition assessment to meet these informational needs. This methodology, though effective, is both time-consuming and costly, because every road within a DOT's jurisdiction must be field-visited to obtain accurate information. Therefore, the USDOT is interested in identifying new technologies that could help meet road infrastructure informational needs more effectively. Remote sensing provides one means by which large areas may be mapped with a high standard of accuracy and is a technology with great potential in infrastructure mapping. The goal of our research is to develop accurate road extraction techniques using high spatial resolution, fine spectral resolution imagery. Additionally, our research will explore the use of hyperspectral data in assessing road quality. Finally, this research aims to define the spatial and spectral requirements for remote sensing data to be used successfully for road feature extraction and road quality mapping. Our findings will facilitate the USDOT in assessing remote sensing as a new resource in infrastructure studies.

Gardner, Margaret E.↗
NASA NTRS2010

Analysis of Ancient Fluvial Patterns on the Surface of Mars

This project involves the study of ancient fluvial patterns on the surface of Mars, including raised curvilinear features (RCFs) and negative relief channels. It requires the use of geological images provided by the Mars Reconnaissance Orbiter to determine how water shaped the surface of Mars in the form of rivers, lakes and/or oceans approximately 3.5 billion years ago, during the Noachian period. The role of the intern is to examine the images and record the corresponding measurements of ancient river systems in an Excel spreadsheet to assist in determining the Noachian water cycle on Mars. Resources used to make these measurements include the Arena software, hand-drawn sketch maps, Microsoft Word, Microsoft Excel and the images provided by the Mars Reconnaissance Orbiter. The Context Imager (CTX) returns black and white images at a resolution of six meters per pixel. The camera can take images with a width of 30 km and a length of 160 km. Seventeen images were observed in total. Images are analyzed and notes are taken concerning their terminal deposits, stream ordering and drainage pattern. The Arena software is utilized to make the images more visible by allowing control of contrast and magnification. Once the image is adjusted, measurements: length, average width, drainage basin area, sinuous ridge area are recorded, at a magnification of one, through using the line segment and polygon tools. After an image has been analyzed and measured, a sketch map is drawn in order to clearly identify the various segments, basins and terminal deposits the intern observed. Observations are used to further classify the fluvial patterns; their drainage pattern is defined as dendritic, parallel, trellis, rectangular, radial, centripetal, deranged or discordant. Once observational notes are completed, mathematical relations are used to determine drainage density, stream frequency, theoretic basin area and sinuosity index. These data will be added to a larger data set that will yield a comprehensive view of early Mars drainage systems. The data obtained from the work conducted will be used to characterize the nature and behavior of water on the surface of Mars. Thorough understanding of the Martian water cycle will serve as biologically significant information. Through working on this project, I acquired insight into the study of planet Mars, and skills in the Arena software as well as the organization of a vast amount of data.

Jethani, Henna↗
NASA NTRS2015

Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = −0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

Soil MOisture↗
NASA NTRS2011

Integrating Machine Learning into a Crowdsourced Model for Earthquake-Induced Damage Assessment

On January 12th, 2010, a catastrophic 7.0M earthquake devastated the country of Haiti. In the aftermath of an earthquake, it is important to rapidly assess damaged areas in order to mobilize the appropriate resources. The Haiti damage assessment effort introduced a promising model that uses crowdsourcing to map damaged areas in freely available remotely-sensed data. This paper proposes the application of machine learning methods to improve this model. Specifically, we apply work on learning from multiple, imperfect experts to the assessment of volunteer reliability, and propose the use of image segmentation to automate the detection of damaged areas. We wrap both tasks in an active learning framework in order to shift volunteer effort from mapping a full catalog of images to the generation of high-quality training data. We hypothesize that the integration of machine learning into this model improves its reliability, maintains the speed of damage assessment, and allows the model to scale to higher data volumes.

crowdsourcing↗
NASA NTRS2015

Oyster Fisheries App

This project is creating a cloud‐enabled, HTML 5 web application to help oyster fishermen and state agencies apply Earth science to improve the management of this important natural and economic resource. The Oyster Fisheries app gathers and analyzes environmental and water quality information, and alerts fishermen and resources managers about problems in oyster fishing waters. An intuitive interface based on Google Maps displays the geospatial information and provides familiar interactive controls to the users. Alerts can be tailored to notify users when conditions in specific leases or public fishing areas require attention. The app is hosted on the Amazon Web Services cloud. It is being developed and tested using some of the latest web development tools such as web components and Polymer.

Perez Guerrero, Geraldo A.↗
NASA NTRSDate not supplied

Mobile LiDAR as A Tool for Terrestrial and Planetary Cave Exploration and Mapping

The Kinematic Navigation and Cartography Knapsack (KNaCK) team at NASA’s Marshall Space Flight Center in Huntsville, Alabama is developing tools that enable ultra-high resolution terrain mapping and navigation using mobile LiDAR (Light Detection and Ranging) and SLAM (Simultaneous Localization and Mapping) algorithms in fully GPS-denied and unilluminated environments. The backpack mounted LiDAR instrument under development by our team demonstrates the potential of mobile SLAM LiDAR for use in challenging lunar and planetary surface environments as well as for lunar, planetary, and terrestrial cave exploration, study, and utilization.

LiDAR↗
NASA NTRS2004

Concept Maps Applied to Mars Exploration Public Outreach

This paper describes CMEX Mars, an effort in the creation of a comprehensive set of concept maps to describe all aspects of Mars exploration. These concept maps, created using the CmapTools software developed by the Institute for Human and Machine Cognition, are available on the Internet at http:/cmex.arc.nasa.gov/CMEX and are linked among themselves as well as to resources on the Internet. The work described took place mainly between 1998 and 2001 and combined the goals of: 1) developing a library of concept maps for educational outreach while also 2) refining the capabilities of the software used to create the interactive maps and 3) making them available on the Internet. Here we focus on the library of Mars exploration concept maps that has been created.

Briggs, Geoffrey↗
NASA NTRS1975

Alaskan resources, current development. Traditional cultural values, and the role of LANDSAT data in current and future land use management planning

Past, present, and proposed applications of LANDSAT data for renewable resource assessments in Alaska are described. Specific projects briefly discussed include: a feasibility investigation applying LANDSAT data to caribou habitat mapping in northeast Alaska, analysis of a native corporate region in southwest Alaska, analysis of a game management unit in interior Alaska, and two proposed analyses in northwest Alaska. These analyses principally address range evaluations concerning caribou, moose, and Dall sheep, but results have application to other renewable resource themes. Application of resource assessment results to a statewide land use management plan is discussed.

Laperriere, A. J.↗