Search NASA⌕ Search

SEARCH · Search NASA

Results for “Geographic Information Systems (GIS)”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7

Interpreting forest and grassland biome productivity utilizing nested scales of image resolution and biogeographical analysis

Several hardware, software, and data collection problems encountered were conquered. The Geographic Information System (GIS) data from other systems were converted to ERDAS format for incorporation with the image data. Statistical analysis of the relationship between spectral values and productivity is being pursued. Several project sites, including Jackson, Pope, Boulder, Smokies, and Huntington Forest are evolving as the most intensively studied areas, primarily due to availability of data and time. Progress with data acquisition and quality checking, more details on experimental sites, and brief summarizations of research results and future plans are discussed. Material on personnel, collaborators, facilities, site background, and meetings and publications of the investigators are included.

Iverson, L. R.↗

Use of topographic and climatological models in a geographical data base to improve Landsat MSS classification for Olympic National Park

An unsupervised computer classification of vegetation/landcover of Olympic National Park and surrounding environs was initially carried out using four bands of Landsat MSS data. The primary objective of the project was to derive a level of landcover classifications useful for park management applications while maintaining an acceptably high level of classification accuracy. Initially, nine generalized vegetation/landcover classes were derived. Overall classification accuracy was 91.7 percent. In an attempt to refine the level of classification, a geographic information system (GIS) approach was employed. Topographic data and watershed boundaries (inferred precipitation/temperature) data were registered with the Landsat MSS data. The resultant boolean operations yielded 21 vegetation/landcover classes while maintaining the same level of classification accuracy. The final classification provided much better identification and location of the major forest types within the park at the same high level of accuracy, and these met the project objective. This classification could now become inputs into a GIS system to help provide answers to park management coupled with other ancillary data programs such as fire management.

Cibula, William G.↗

Advanced techniques for the storage and use of very large, heterogeneous spatial databases. The representation of geographic knowledge: Toward a universal framework

A new approach to building geographic data models that is based on the fundamental characteristics of the data is presented. An overall theoretical framework for representing geographic data is proposed. An example of utilizing this framework in a Geographic Information System (GIS) context by combining artificial intelligence techniques with recent developments in spatial data processing techniques is given. Elements of data representation discussed include hierarchical structure, separation of locational and conceptual views, and the ability to store knowledge at variable levels of completeness and precision.

Peuquet, Donna J.↗

Requirements and principles for the implementation and construction of large-scale geographic information systems

This paper provides a brief survey of the history, structure and functions of 'traditional' geographic information systems (GIS), and then suggests a set of requirements that large-scale GIS should satisfy, together with a set of principles for their satisfaction. These principles, which include the systematic application of techniques from several subfields of computer science to the design and implementation of GIS and the integration of techniques from computer vision and image processing into standard GIS technology, are discussed in some detail. In particular, the paper provides a detailed discussion of questions relating to appropriate data models, data structures and computational procedures for the efficient storage, retrieval and analysis of spatially-indexed data.

Smith, Terence R.↗

The use of remotely sensed data for the monitoring of forest change in tropical areas

This paper provides an overview of the use of several remote sensing systems for monitoring changes in tropical forests. Particular attention is given to the use of data from the AVHRR sensors on the NOAA series of satellites, the Landsat MSS and TM, and aircraft and spacecraft acquired Synthetic Aperture Radar. Multisensor and multistage approaches to monitoring change in tropical forests is examined. Forest change monitoring through a geographic information system (GIS) approach is addressed. Finally some suggestions are made for research addressing forest change monitoring in tropical areas.

Joyce, Armond T.↗

Multisensor monitoring of deforestation in the Guinea Highlands of West Africa

Multiple remote sensing systems were used to assess deforestation in the Guinea Highlands (Fouta Djallon) of West Africa. Sensor systems included: (1) historical (1953) and current (1989) aerial mapping photography; (2) current large-scale, small format (35mm) aerial photography; (3) current aerial video imagery; and (4) historical (1973) and recent (1985) LANDSAT MSS. Photographic and video data were manually interpreted and incorporated in a vector-based geographic information system (GIS). LANDSAT data were digitally classified. General results showed an increase in permanent and shifting agriculture over the past 35 years. This finding is consistent with hypothesized strategies to increase agricultural production through a shortening of the fallow period in areas of shifting cultivation. However, results also show that the total area of both permanent and shifting agriculture had expanded at the expense of natural vegetation and an increase in erosion. Although sequential LANDSAT MSS cannot be used in this region to accurately map land over, the location, direction and magnitude of changes can be detected in relative terms. Historical and current aerial photography can be used to map agricultural land use changes with some accuracy. Video imagery is useful as ancillary data for mapping vegetation. The most prudent approach to mapping deforestation would incorporate a multistage approach based on these sensors.

Gilruth, Peter T.↗

Assessment of vegetation change in a fire-altered forest landscape

This research focused on determining the degree to which differences in burn severity relate to postfire vegetative cover within a Michigan pine forest. Landsat MSS data from June 1973 and TM data from October 1982 were classified using an unsupervised approach to create prefire and postfire cover maps of the study area. Using a raster-based geographic information system (GIS), the maps were compared, and a map of vegetation change was created. An IR/red band ratio from a June 1980 Landsat scene was classified to create a map of three degres of burn severity, which was then compared with the vegetation change map using a GIS. Classification comparisons of pine and deciduous forest classes (1973 to 1982) revealed that the most change in vegetation occurred in areas subjected to the most intense burn. Two classes of regenerating forest comprised the majority of the change, while the remaining change was associated with shrub vegetation or another forest class.

Jakubauskas, Mark E.↗

Cartographic modeling of snow avalanche path location within Glacier National Park, Montana

Geographic information system (GIS) techniques were applied to the study of snow-avalanche path location within Glacier National Park, Montana. Aerial photointerpretation and field surveys confirmed the location of 121 avalanche paths within the selected study area. Spatial and nonspatial information on each path were integrated using the ARC/INFO GIS. Lithologic, structural, hydrographic, topographic, and land-cover impacts on path location were analyzed. All path frequencies within variable classes were normalized by the area of class occurrence relative to the total area of the study area and were added to the morphometric information contained within INFO tables. The normalized values for each GIS coverage were used to cartographically model, by means of composite factor weightings, avalanche path locations.

Walsh, Stephen J.↗

NASA applications project in Miami County, Indiana

This project was designed to acquaint county government officials and their clientele with remote sensing and geographic information systems (GIS) products that contain information about land conditions and land use. The specific project objectives are: (1) to investigate the feasibility of using remotely sensed data to identify and quantify specific land cover categories and conditions for purposes of tax assessment, cropland area measurements, and land use evaluation; (2) to evaluate the use of remotely sensed data to assess soil resources and conditions which affect productivity; (3) to investigate the use of satellite remote sensing data as an aid in assessing soil management practices; and (4) to evaluate the market potential of products derived from the above projects.

Johannsen, Chris J.↗

A description of the Global Resources Information Database

This paper describes the Global Resources Information Database (GRID), which is part of the Global Environmental Monitoring (GEM) Program. The following four objectives were established for GRID: (1) to collect and disseminate geographical information; (2) to construct within developing countries a geographical information system (GIS); (3) to demonstrate the ability of GIS to fuse global and national data sets for resource and environment management and planning at the national level; and (4) to train individuals from developing countries in remote sensing technology. The activities of GRID are coordinated at the GEM center at Nairobi (Kenya).

Vermillion, Charles H.↗

Development of satellite remote sensing techniques as an economic tool for forestry industry

A cooperative commercial development project designed to focus on cost-effective and practical applications of satellite remote sensing in forest management is discussed. The project, initiated in September, 1988 is being executed in three phases: (1) development of a forest resource inventory and geographic information system (GIS) updating systems; (2) testing and evaluation of remote-sensing products against forest industry specifications; and (3) integration of remote-sensing services and products in an operational setting. An advisory group represented by eleven major forest-product companies will provide direct involvement of the target market. The advisory group will focus on the following questions: Does the technology work for them? How can it be packaged to provide the needed forest-management information? Can the products and information be provided in a cost-effective manner?

Sader, Steven A.↗

Center for Mapping, Ohio State University

There are many future opportunities for Centers for the Commercial Development of Space (CCDS) activities that are directly linked to industry strategic objectives. In the fields of mapping, remote sensing, and geographic information systems (GIS), the near term opportunities may exceed all that have occurred in the past 10 years. It is strongly believed that a national spatial data infrastructure must be established in this country, if we are to remain a leader in the information age.

Starr, Lowell↗

Development of a prototype spatial information processing system for hydrologic research

Significant advances have been made in the last decade in the areas of Geographic Information Systems (GIS) and spatial analysis technology, both in hardware and software. Science user requirements are so problem specific that currently no single system can satisfy all of the needs. The work presented here forms part of a conceptual framework for an all-encompassing science-user workstation system. While definition and development of the system as a whole will take several years, it is intended that small scale projects such as the current work will address some of the more short term needs. Such projects can provide a quick mechanism to integrate tools into the workstation environment forming a larger, more complete hydrologic analysis platform. Described here are two components that are very important to the practical use of remote sensing and digital map data in hydrology. Described here is a graph-theoretic technique to rasterize elevation contour maps. Also described is a system to manipulate synthetic aperture radar (SAR) data files and extract soil moisture data.

Sircar, Jayanta K.↗

Mapping Florida Scrub Jay habitat for purposes of land-use management

Geographical information system (GIS) applications were used to map areas of primary and secondary Florida Scrub Jay habitat on Kennedy Space Center (KSC) using vegetation and soils maps. Data from field studies were used for accuracy assessment and evaluating the importance of mapping classes. Primary habitat accounts for 15 percent of the potential habitat and contained 57 percent of the Florida Scrub Jay population on KSC. Proximity analysis identified potential population centers, which were 44 percent of the potential habitat and contained 86 percent of the population. This study is an example of how remote sensing and GIS applications can provide information for land-use planning, habitat management, and the evaluation of cumulative impacts.

Breininger, David R.↗

Utilization of Geographic Information System in Lunar Mapping

Substantial digital remote sensing, lunar orbital photography, Earth-based remote sensing, and mapping of a variety of surficial lunar phenomena have occurred since the advent of the Space Age. This has led to a bewildering and quite disparate collection of archival sources insofar as this digital data and its cartographic representation can be found within many countries of the world. The importance of this mapping program in support of human expansion onto our nearest planetary neighbor has been recognized. A series of small scale maps of the Moon at 1 km to 1 cm, done with the support of Geographic Information System (GIS), would serve decision makers well in the process of accessing the development of manned occupance of the Moon. Maps and the data that they are derived from are the primary way in which people explore new environments and use previously discovered data to increase the bounties of any exploration. The inherent advantage of GIS is that it would allow immediate online access on the Moon of topographically represented data with analysis either on site or from Earth.

Mardon, A. A.↗

Estimating high mosquito-producing rice fields using spectral and spatial data

The cultivation of irrigated rice provides ideal larval habitat for a number of anopheline vectors of malaria throughout the world. Anopheles freeborni, a potential vector of human malaria, is associated with the nearly 240,000 hectares of irrigated rice grown annually in Northern and Central California; therefore, this species can serve as a model for the study of rice field anopheline population dynamics. Analysis of field data revealed that rice fields with early season canopy development, that are located near bloodmeal sources (i.e., pastures with livestock) were more likely to produce anopheline larvae than fields with less developed canopies located further from pastures. Remote sensing reflectance measurements of early-season canopy development and geographic information system (GIS) measurements of distanes between rice fields and pastures with livestock were combined to distinguish between high and low mosquito-producing rice fields. Using spectral and distance measures in either a discriminant or Bayesian analysis, the identification of high mosquito-producing fields was made with 85 percent accuracy nearly two months before anopheline larval populations peaked. Since omission errors were also minimized by these approaches, they could provide a new basis for directing abatement techniques for the control of malaria vectors.

Wood, B. L.↗

Neuro-classification of multi-type Landsat Thematic Mapper data

Neural networks have been successful in image classification and have shown potential for classifying remotely sensed data. This paper presents classifications of multitype Landsat Thematic Mapper (TM) data using neural networks. The Landsat TM Image for March 23, 1987 with accompanying ground observation data for a study area In Miami County, Indiana, U.S.A. was utilized to assess recognition of crop residues. Principal components and spectral ratio transformations were performed on the TM data. In addition, a layer of the geographic information system (GIS) for the study site was incorporated to generate GIS-enhanced TM data. This paper discusses (1) the performance of neuro-classification on each type of data, (2) how neural networks recognized each type of data as a new image and (3) comparisons of the results for each type of data obtained using neural networks, maximum likelihood, and minimum distance classifiers.

Zhuang, Xin↗

A system for verifying models and classification maps by extraction of information from a variety of data sources

Recent updates to a geographical information system (GIS) called VICAR (Video Image Communication and Retrieval)/IBIS are described. The system is designed to handle data from many different formats (vector, raster, tabular) and many different sources (models, radar images, ground truth surveys, optical images). All the data are referenced to a single georeference plane, and average or typical values for parameters defined within a polygonal region are stored in a tabular file, called an info file. The info file format allows tracking of data in time, maintenance of links between component data sets and the georeference image, conversion of pixel values to `actual' values (e.g., radar cross-section, luminance, temperature), graph plotting, data manipulation, generation of training vectors for classification algorithms, and comparison between actual measurements and model predictions (with ground truth data as input).

Norikane, L.↗