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At least 181 records · Page 10

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.↗

History of wildland fires on Vandenberg Air Force Base, California

The fire history of the past 50 years for Vandenberg AFB, California was determined using aerial photography, field investigation, and historical and current written records. This constitutes a record of the vegetation age classes for the entire base. The location, cause, and fuel type for sixty fires from this time period were determined. The fires were mapped and entered into a geographic infomation system (GIS) for Vandenberg. Fire history maps derived from this GIS were printed at 1:9600 scale and are on deposit at the Vandenberg Environmental Task Force Office. Although some ecologically significant plant communities on Vandenberg are adapted to fire, no natural fire frequency could be determined, since only one fire possibly caused by lightning occurred in the area now within the base since 1937. Observations made during this study suggest that burning may encourage the invasion of exotic species into chaparral, in particular Burton Mesa or sandhill chaparral, an unusual and geographically limited form of chaparral found on the base.

Hickson, Diana E.↗

Recent trends in geographic information system research

This paper reviews recent contributions to the body of published research on Geographic Information Systems (GISs). Increased usages of GISs have placed a new demand upon the academic and research community and despite some lack of formalized definitions, categorizations, terminologies, and standard data structures, the community has risen to the challenge. Examinations of published GIS research, in particular on GIS data structures, reveal a healthy, active research community which is using a truly interdisciplinary approach. Future work will undoubtably lead to a clearer understanding of the problems of handling spatial data, while producing a new generation of highly sophisticated GISs.

Clarke, K. C.↗

Interfacing geographic information systems and remote sensing for rural land-use analysis

Recent advances in computer-based geographic information systems (GISs) are briefly reviewed, with an emphasis on the incorporation of remote-sensing data in GISs for rural applications. Topics addressed include sampling procedures for rural land-use analyses; GIS-based mapping of agricultural land use and productivity; remote sensing of land use and agricultural, forest, rangeland, and water resources; monitoring the dynamics of irrigation agriculture; GIS methods for detecting changes in land use over time; and the development of land-use modeling strategies.

Nellis, M. Duane↗

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.↗

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.↗

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.↗

Category identification of changed land-use polygons in an integrated image processing/geographic information system

A framework is proposed for analyzing ancillary data and developing procedures for incorporating ancillary data to aid interactive identification of land-use categories in land-use updates. The procedures were developed for use within an integrated image processsing/geographic information systems (GIS) that permits simultaneous display of digital image data with the vector land-use data to be updated. With such systems and procedures, automated techniques are integrated with visual-based manual interpretation to exploit the capabilities of both. The procedural framework developed was applied as part of a case study to update a portion of the land-use layer in a regional scale GIS. About 75 percent of the area in the study site that experienced a change in land use was correctly labeled into 19 categories using the combination of automated and visual interpretation procedures developed in the study.

Westmoreland, Sally↗

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↗

Estimating dry grass residues using landscape integration analysis

The acreage of grassland and grassland-savannah is extensive in California, making direct measurement and assessment logistically impossible. Grasslands cover the entire Central Valley up to about 1200 m elevation in the Coast Range and Sierra Nevada Range. Kuchler's map shows 5.35 M ha grassland with an additional 3.87 M ha in Oak savannah. The goal of this study was to examine the use of high spectral resolution sensors to distinguish between dry grass and soil in remotely sensed images. Spectral features that distinguish soils and dry plant material in the shortwave infrared (SWIR) region are thought to be primarily caused by cellulose and lignin, biochemicals which are absent from soils or occur as breakdown products in humid substances that lack the narrow-band features. We have used spectral mixing analysis (SMA) combined with Geographic Information Systems (GIS) analysis to characterize plant communities and dry grass biomass. The GIS was used to overlay elevation maps, and vegetation maps, with the SMA results. The advantage of non-image data is that it provides an independent source of information for the community classification.

Hart, Quinn J.↗

Geographic information analysis: An ecological approach for the management of wildlife on the forest landscape

This document is a summary of the project funded by NAGw-1460 as part of the Earth Observation Commericalization/Applications Program (EOCAP) directed by NASA's Earth Science and Applications Division. The goal was to work with several agencies to focus on forest structure and landscape characterizations for wildlife habitat applications. New analysis techniques were used in remote sensing and landscape ecology with geographic information systems (GIS). The development of GIS and the emergence of the discipline of landscape ecology provided us with an opportunity to study forest and wildlife habitat resources from a new perspective. New techniques were developed to measure forest structure across scales from the canopy to the regional level. This paper describes the project team, technical advances, and technology adoption process that was used. Reprints of related refereed journal articles are in the Appendix.

Ripple, William J.↗

Geographic Information System Data Analysis

Data was collected in order to further NASA Langley Research Center's Geographic Information System(GIS). Information on LaRC's communication, electrical, and facility configurations was collected. Existing data was corrected through verification, resulting in more accurate databases. In addition, Global Positioning System(GPS) points were used in order to accurately impose buildings on digitized images. Overall, this project will help the Imaging and CADD Technology Team (ICTT) prove GIS to be a valuable resource for LaRC.

Billings, Chad↗

Geospatial Education and Research Development: A Laboratory for Remote Sensing and Environmental Analysis (LaRSEA)

Old Dominion University has claimed the title "University of the 21st Century," with a bold emphasis on technology innovation and application. In keeping with this claim, the proposed work has implemented a new laboratory equipped for remote sensing as well as curriculum and research innovations afforded for present and future faculty and students. The developments summarized within this report would not have been possible without the support of the NASA grant and significant cost-sharing of several units within the University. The grant effectively spring-boarded the university into major improvements in its approach to remote sensing and geospatial information technologies. The university has now committed to licensing Erdas Imagine software for the laboratory, a campus-wide ESRI geographic information system (GIS) products license, and several smaller software and hardware utilities available to faculty and students through the laboratory. Campus beneficiaries of this grant have included faculty from departments including Ocean, Earth. and Atmospheric Sciences, Political Science and Geography, Ecological Sciences, Environmental Health, and Civil and Environmental Engineering. High student interest is evidenced in students in geology, geography, ecology, urban studies, and planning. Three new courses have been added to the catalog and offered this year. Cross-cutting curriculum changes are in place with growing enrollments in remote sensing, GIS, and a new co-taught seminar in applied coastal remote sensing. The enabling grant has also allowed project participants to attract external funding for research grants, thereby providing additional funds beyond the planned matching, maintenance and growth of software and hardware, and stipends for student assistants. Two undergraduate assistants and two graduate assistants have been employed by full-time assistantships as a result. A new certificate is offered to students completing an interdisciplinary course sequence in remote sensing and coastal environments. Subsequent phases of the project are under planning. including seminars for regional coastal managers and public dissemination of remote sensing science through the local media and university publications.

Allen, Thomas R., Jr.↗

A Multiple Resource Inventory of Delaware Using an Airborne Profiling Laser

An airborne profiling laser is used to monitor multiple resources related to landscape structure, both natural and man-made, across regions encompassing hundreds of thousands of hectares. A small, lightweight, inexpensive airborne profiling laser is used to inventory Delaware forests, to estimate impervious surface area statewide, and to locate potentially Suitable Delmarva Fox Squirrel (Scrotum niger cinereus) habitat. Merchantable volume estimates are within 14% of US Forest Service estimates at the county level and within 4% statewide. Total above-ground dry biomass estimates are within 19% of USES estimates at the county level and within 16% statewide. Mature forest stands suitable for reintroduction of the Delmarva Fox Squirrel, an endangered species historically endemic to the eastern shores of Delaware, Maryland, and Virginia, are identified and mapped along the laser transacts. Intersection lengths with various types of impervious surface (roofs, concrete/asphalt) and open water are tallied to estimate percent and areal coverage statewide, by stratum and county. Laser estimates of open water are within 7% of photointerpreted GIS estimates at the county level and within 3% of the GIS at the state level.

Nelson, Ross↗

A Dynamic Optimization Technique for Siting the NASA-Clark Atlanta Urban Rain Gauge Network (NCURN)

NASA satellites and ground instruments have indicated that cities like Atlanta, Georgia may create or alter rainfall. Scientists speculate that the urban heat island caused by man-made surfaces in cities impact the heat and wind patterns that form clouds and rainfall. However, more conclusive evidence is required to substantiate findings from satellites. NASA, along with scientists at Clark Atlanta University, are implementing a dense, urban rain gauge network in the metropolitan Atlanta area to support a satellite validation program called Studies of PRecipitation Anomalies from Widespread Urban Landuse (SPRAWL). SPRAWL will be conducted during the summer of 2003 to further identify and understand the impact of urban Atlanta on precipitation variability. The paper provides an. overview of SPRAWL, which represents one of the more comprehensive efforts in recent years to focus exclusively on urban-impacted rainfall. The paper also introduces a novel technique for deploying rain gauges for SPRAWL. The deployment of the dense Atlanta network is unique because it utilizes Geographic Information Systems (GIS) and Decision Support Systems (DSS) to optimize deployment of the rain gauges. These computer aided systems consider access to roads, drainage systems, tree cover, and other factors in guiding the deployment of the gauge network. GIS and DSS also provide decision-makers with additional resources and flexibility to make informed decisions while considering numerous factors. Also, the new Atlanta network and SPRAWL provide a unique opportunity to merge the high-resolution, urban rain gauge network with satellite-derived rainfall products to understand how cities are changing rainfall patterns, and possibly climate.

Shepherd, J. Marshall↗

Fractals and Spatial Methods for Mining Remote Sensing Imagery

The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of the data before any useful process-oriented modeling involving scale-dependent data can be conducted. Through the support of research grants from NASA, we have developed a software module called ICAMS (Image Characterization And Modeling System) to address the need to develop innovative spatial techniques and make them available to the broader scientific communities. ICAMS provides new spatial techniques, such as fractal analysis, geostatistical functions, and multiscale analysis that are not easily available in commercial GIS/image processing software. By bundling newer spatial methods in a user-friendly software module, researchers can begin to test and experiment with the new spatial analysis methods and they can gauge scale effects using a variety of remote sensing imagery. In the following, we describe briefly the development of ICAMS and present application examples.

Lam, Nina↗

[Development and Use of Hidrosig]

The NASA portion of this joint NSF-NASA grant consists of objective 2 and a part of objective 3. A major effort was made on objective 2, and it consisted of developing a numerical GIs environment called Hidrosig. This major research tool is being developed by the University of Colorado for conducting river-network-based scaling analyses of coupled water-energy-landform-vegetation interactions including water and energy balances, and floods and droughts, at multiple space-time scales.Objective 2: To analyze the relevant remotely sensed products from satellites, radars and ground measurements to compute the transported water mass for each complete Strahler stream using an 'assimilated water balance equation' at daily and other appropriate time scales. This objective requires analysis of concurrent data sets for Precipitation (PPT), Evapotranspiration (ET) and stream flows (Q) on river networks. To solve this major problem, our decision was to develop Hidrosig, a new Open-Source GIs software. A research group in Colombia, South America, developed the first version of Hidrosig, and Ricardo Mantilla was part of this effort as an undergraduate student before joining the graduate program at the University of Colorado in 2001. Hydrosig automatically extracts river networks from large DEMs and creates a "link-based" data structure, which is required to conduct a variety of analyses under objective 2. It is programmed in Java, which is a multi-platform programming language freely distributed by SUN under a GPL license. Some existent commercial tools like Arc-Info, RiverTools and others are not suitable for our purpose for two reasons. First, the source code is not available that is needed to build on the network data structure. Second, these tools use different programming languages that are not most versatile for our purposes. For example, RiverTools uses an IDL platform that is not very efficient for organizing diverse data sets on river networks. Hidrosig establishes a clear data organization framework that allows a simultaneous analysis of spatial fields along river network structures involving Horton- Strahler framework. Software tools for network extraction from DEMs and network-based analysis of geomorphologic and topologic variables were developed during the first year and a part of second year.

Gupta, Vijay K.↗