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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Use of GPR Surveys in Historical Archaeology Studies at Gainesville, Mississippi (22HA600)

Ground Penetrating Radar (GPR) is used to study the underground remains of historic structures on the grounds of Stennis Space Center (SSC) in this viewgraph presentation. The main goal of the project described is to research, develop, and validate Remote Sensing (RS) and Geographic Information System (GIS) methods for aiding cultural resource assessments within SSC. The project georeferences historic imagery and maps to assist archaeological RS, field surveys, and excavations.

Goodwin, Ben↗
NASA NTRS2003

Mapping Soil pH Buffering Capacity of Selected Fields

Soil pH buffering capacity, since it varies spatially within crop production fields, may be used to define sampling zones to assess lime requirement, or for modeling changes in soil pH when acid forming fertilizers or manures are added to a field. Our objective was to develop a procedure to map this soil property. One hundred thirty six soil samples (0 to 15 cm depth) from three Georgia Coastal Plain fields were titrated with calcium hydroxide to characterize differences in pH buffering capacity of the soils. Since the relationship between soil pH and added calcium hydroxide was approximately linear for all samples up to pH 6.5, the slope values of these linear relationships for all soils were regressed on the organic C and clay contents of the 136 soil samples using multiple linear regression. The equation that fit the data best was b (slope of pH vs. lime added) = 0.00029 - 0.00003 * % clay + 0.00135 * % O/C, r(exp 2) = 0.68. This equation was applied within geographic information system (GIS) software to create maps of soil pH buffering capacity for the three fields. When the mapped values of the pH buffering capacity were compared with measured values for a total of 18 locations in the three fields, there was good general agreement. A regression of directly measured pH buffering capacities on mapped pH buffering capacities at the field locations for these samples gave an r(exp 2) of 0.88 with a slope of 1.04 for a group of soils that varied approximately tenfold in their pH buffering capacities.

Weaver, A. R.↗
NASA NTRS2003

Disaster Response and Preparedness Application: Emergency Environmental Response Tool (EERT)

In 2000, the National Aeronautics and Space Administration (NASA) Environmental Office at the John C. Stennis Space Center (SSC) developed an Environmental Geographic Information Systems (EGIS) database. NASA had previously developed a GIS database at SSC to assist in the NASA Environmental Office's management of the Center. This GIS became the basis for the NASA-wide EGIS project, which was proposed after the applicability of the SSC database was demonstrated. Since its completion, the SSC EGIS has aided the Environmental Office with noise pollution modeling, land cover assessment, wetlands delineation, environmental hazards mapping, and critical habitat delineation for protected species. At SSC, facility management and safety officers are responsible for ensuring the physical security of the facilities, staff, and equipment as well as for responding to environmental emergencies, such as accidental releases of hazardous materials. All phases of emergency management (planning, mitigation, preparedness, and response) depend on data reliability and system interoperability from a variety of sources to determine the size and scope of the emergency operation. Because geospatial data are now available for all NASA facilities, it was suggested that this data could be incorporated into a computerized management information program to assist facility managers. The idea was that the information system could improve both the effectiveness and the efficiency of managing and controlling actions associated with disaster, homeland security, and other activities. It was decided to use SSC as a pilot site to demonstrate the efficacy of having a baseline, computerized management information system that ultimately was referred to as the Emergency Environmental Response Tool (EERT).

Smoot, James↗
NASA NTRS2002

Remote Sensing and Information Technology for Large Farms

A method of applying of remote sensing (RS) and information management technology to help large farms produce at maximum efficiency is undergoing development. The novelty of the method does not lie in the concept of "precision agriculture," which involves variation of seeding, of application of chemicals, and of irrigation according to the spatially and temporally local variations in the growth stages and health of crops and in the chemical and physical conditions of soils. The novelty also does not lie in the use of RS data registered with other data in a geographic information system (GIS) to guide the use of precise agricultural techniques. Instead, the novelty lies in a systematic approach to overcoming obstacles that, heretofore, have impeded the timely distribution of reliable, relevant, and sufficient GIS data to support day-to-day, acre-to-acre decisions concerning the application of precise agricultural techniques to increase production and decrease cost. The development and promotion of the method are inspired in part by a vision of equipping farm machinery to accept GIS (including RS) data and using the data for automated or semiautomated implementation of precise agricultural techniques. Primary examples of relevant GIS data include information on plant stress, soil moisture, and effects of applied chemicals, all derived by automated computational analysis of measurements taken by one or more airborne spectroradiometers. Proper management and timeliness of the large amount of GIS information are of paramount concern in agriculture. Information on stresses and changes in crops is especially perishable and important to farmers. The need for timeliness and management of information is satisfied by use of computing hardware and software capable of (1) rapid georectification and other processing of RS data, (2) packaging the output data in the form of GIS plots, and (3) making the data available to farmers and other subscribers by Internet password access. It is a goal of this development program to make RS data available no later than the data after an aerial survey. In addition, data from prior surveys are kept in the data base. Farmers can, for example, use current and prior data to analyze changes.

Williams, John E.↗
NASA NTRS2002

Use of IKONOS Data for Mapping Cultural Resources of Stennis Space Center, Mississippi

Cultural resource surveys are important for compliance with Federal and State law. Stennis Space Center (SSC) in Mississippi is researching, developing, and validating remote sensing and Geographical Information System (GIS) methods for aiding cultural resource assessments on the center's own land. The suitability of IKONOS satellite imagery for georeferencing scanned historic maps is examined in this viewgraph presentation. IKONOS data can be used to map historic buildings and farmland in Gainsville, MS, and plan archaeological surveys.

Spruce, Joseph P.↗
NASA NTRS2003

Satellites as Sentinels for Climate and Health

Remotely-sensed data and observations are providing powerful new tools for addressing climate and environment-related human health problems through increased capabilities for monitoring, risk mapping, and surveillance of parameters useful to such problems as vector- borne and infectious diseases, air and water quality,. harmful algal blooms, W radiation, contaminant and pathogen transport in air and water, and thermal stress. Remote sensing, geographic information systems (GIs), global positioning systems (GPS), improved computation capabilities, and interdisciplinary research between the Earth and health science communities, together with local knowledge, are being combined in rich collaborative efforts resulting in more rapid problem-solving, early warning, and prevention in global climate and health issues. These collaborative efforts are enabling increased understanding of the relationships among changes in temperature, rainfall, wind, soil moisture, solar radiation, vegetation, and the patterns of extreme weather events and health issues. This increased understanding and improved information and data sharing, in turn, empowers local health and environmental decision-makers to better predict climate-related health problems, decrease vulnerability, take preventive measures, and improve response actions. This paper provides a number of recent examples of how satellites - from their unique vantage point in space - can serve as sentinels for climate and health.

Maynard, Nancy G.↗
NASA NTRS2004

Variability in Morphology and Thermophysical Properties of Pitted Cones in Acidalia Planitia and Cydonia Mensae

The northern plains of Mars contain a number of unique landforms and are unique in terms of their topography and composition . Much of the speculation about the northern plains centers on whether there was ever a northern ocean, and if there was, was it long-lived or ephemeral? The northern plains also hosts the Vastitas Borealis Formation which has been variously interpreted as the residue from a northern ocean , and pre-existing material reworked by cold-weather processes . In this work we examine a set of unusual features resident on the northern plains, the pitted cones originally recognized in Viking data . Our focus is on the pitted cones in Acidalia and Cydonia regions. The pitted cones of the northern plains have been hypothesized as being equivalent to terrestrial cinder cones , rootless cones , pingos , and mud volcanoes . To examine the Acidalia and Cydonia regions, multispectral data from the Mars Odyssey THEMIS, gridded topography from Mars Global Surveyor (MGS) MOLA, images from MGS MOC, and mineralogic and thermal inertia information from MGS TES have been assembled in a Geographic Information System. Analysis of MOC Narrow Angle camera images

Farrand, W. H.↗
NASA NTRS2002

Software for Partly Automated Recognition of Targets

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user's tendencies while the user is selecting targets and to increase the user's productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Opitz, David↗
NASA NTRS2004

Mosquito Larval Habitats, Land Use, and Potential Malaria Risk in Northern Belize from Satellite Image Analyses

The distribution of Anopheles mosquito habitats and land use in northern Belize is examined with satellite data. -A land cover classification based on multispectral SPOT and multitemporal Radarsat images identified eleven land cover classes, including agricultural, forest, and marsh types. Two of the land cover types, Typha domingensis marsh and flooded forest, are Anopheles vestitipennis larval habitats. Eleocharis spp. marsh is the larval habitat for Anopheles albimanus. Geographic Information Systems (GIS) analyses of land cover demonstrate that the amount of T-ha domingensis in a marsh is positively correlated with the amount of agricultural land in the adjacent upland, and negatively correlated with the amount of adjacent forest. This finding is consistent with the hypothesis that nutrient (phosphorus) runoff from agricultural lands is causing an expansion of Typha domingensis in northern Belize. This expansion of Anopheles vestitipennis larval habitat may in turn cause an increase in malaria risk in the region.

Pope, Kevin↗
NASA NTRS2004

Communications: Mosquito Habitats, Land Use, and Malaria Risk in Belize from Satellite Imagery

Satellite imagery of northern Belize is used to examine the distribution of land use and breeding habitats of the malaria vector the Anopheles mosquito. A land cover classification based on multispectral SPOT and multitemporal Radarsat images identified eleven land cover classes, including agricultural, forest, and marsh types. Two of the land cover types, Typha domingensis marsh and flooded forest, are Anopheles vestitipennis larval habitats, and one, Eleocharis spp. marsh, is the larval habitat for Anopheles albimanus. Geographic Information Systems (GIS) analyses of land cover demonstrate that the amount of Typha domingensis in a marsh is positively correlated with the amount of agricultural land in the adjacent upland, and negatively correlated with the amount of adjacent forest. This finding is consistent with the hypothesis that nutrient (phosphorus) runoff from agricultural lands is causing an expansion of Typha domingensis in northern Belize. Thus, land use induced expansion of Anopheles vestitipennis larval habitat is potentially increasing malaria risk in Belize, and in other regions where Anopheles vestitipennis is a major malaria vector.

Pope, Kevin↗
NASA NTRS2004

The Role of Satellite Earth Observation Data in Monitoring and Verifying International Environmental Treaties

The term verification implies compliance verification in the language of treaty negotiation and implementation, particularly in the fields of disarmament and arms control. The term monitoring on the other hand, in both environmental and arms control treaties, has a much broader interpretation which allows for use of supporting data sources that are not necessarily acceptable or adequate for direct verification. There are many ways that satellite Earth observation (EO) data can support international environmental agreements, from national forest inventories to use in geographic information system (GIs) tools. Though only a few references to satellite EO data and their use exist in the treaties themselves, an expanding list of applications can be considered in support of multilateral environmental agreements (MEAs). This paper explores the current uses of satellite Earth observation data which support monitoring activities of major environmental treaties and draws conclusions about future missions and their data use. The scope of the study includes all phases of environmental treaty fulfillment - development, monitoring, and enforcement - and includes a multinational perspective on the use of satellite Earth observation data for treaty support.

Johnston, Shaida↗
NASA NTRS1997

Assessment of a remote sensing-based model for predicting malaria transmission risk in villages of Chiapas, Mexico

A blind test of two remote sensing-based models for predicting adult populations of Anopheles albimanus in villages, an indicator of malaria transmission risk, was conducted in southern Chiapas, Mexico. One model was developed using a discriminant analysis approach, while the other was based on regression analysis. The models were developed in 1992 for an area around Tapachula, Chiapas, using Landsat Thematic Mapper (TM) satellite data and geographic information system functions. Using two remotely sensed landscape elements, the discriminant model was able to successfully distinguish between villages with high and low An. albimanus abundance with an overall accuracy of 90%. To test the predictive capability of the models, multitemporal TM data were used to generate a landscape map of the Huixtla area, northwest of Tapachula, where the models were used to predict risk for 40 villages. The resulting predictions were not disclosed until the end of the test. Independently, An. albimanus abundance data were collected in the 40 randomly selected villages for which the predictions had been made. These data were subsequently used to assess the models' accuracies. The discriminant model accurately predicted 79% of the high-abundance villages and 50% of the low-abundance villages, for an overall accuracy of 70%. The regression model correctly identified seven of the 10 villages with the highest mosquito abundance. This test demonstrated that remote sensing-based models generated for one area can be used successfully in another, comparable area.

Insect Vectors/growth & development↗
NASA NTRS1994

GIS and RDBMS Used with Offline FAA Airspace Databases

A geographic information system (GIS) and relational database management system (RDBMS) were used in a Macintosh environment to access, manipulate, and display off-line FAA databases of airport and navigational aid locations, airways, and airspace boundaries. This proof-of-concept effort used data available from the Adaptation Controlled Environment System (ACES) and Digital Aeronautical Chart Supplement (DACS) databases to allow FAA cartographers and others to create computer-assisted charts and overlays as reference material for air traffic controllers. These products were created on an engineering model of the future GRASP (GRaphics Adaptation Support Position) workstation that will be used to make graphics and text products for the Advanced Automation System (AAS), which will upgrade and replace the current air traffic control system. Techniques developed during the prototyping effort have shown the viability of using databases to create graphical products without the need for an intervening data entry step.

air traffic control↗
NASA NTRS1997

Statistical Modeling of Landscape Pattern and the Effects of Coarse Spatial Resolution

Analysis of classified satellite imagery was conducted to characterize errors in estimates of area based on coarse resolution satellite imagery which are due to distortions in sizes of small fragments, and to explore the feasibility of correcting for these errors using a statistical modeling approach. Sizes of bodies of open water on European Remote-Sensing (ERS-1) synthetic aperture radar (SAR) and fire scars on Landsat Multispectral Scanner (MSS) imagery were measured using geographic information system (GIS) software. Statistical analysis of the smaller scars and ponds as observed with this imagery of relatively fine resolution demonstrated that the distribution of the sizes could be modeled by either of two types of statistical distributions-a power distribution related to fractal processes or a simple exponential distribution. A comparison of the size distribution of small burn scars as observed with Landsat with the distribution observed with the much coarser Advanced Very High Resolution Radiometer (AVHRR) imagery revealed effects of coarse resolution, each of which were associated with a particular size range, and whose net effect accounted for the bias in total burn area due to coarse spatial resolution. Size dependent area correction procedures are therefore feasible. A statistical modeling approach to area estimation, based models of the underlying and observed size distributions of fragments in the scene, may lead to a procedure which requires little or no ancillary data.

Hlavka, C. A.↗
NASA NTRS2007

Use of Satellite Remote Sensing Data in the Mapping of Global Landslide Susceptibility

Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIs-based weighted linear combination method. First , six relevant landslide-controlling factors are derived from geospatial remote sensing data and coded into a GIS system. Next, continuous susceptibility values from low to high are assigned to each of the six factors. Second, a continuous scale of a global landslide susceptibility index is derived using GIS weighted linear combination based on each factor's relative significance to the process of landslide occurrence (e.g., slope is the most important factor, soil types and soil texture are also primary-level parameters, while elevation, land cover types, and drainage density are secondary in importance). Finally, the continuous index map is further classified into six susceptibility categories. Results show the hot spots of landslide-prone regions include the Pacific Rim, the Himalayas and South Asia, Rocky Mountains, Appalachian Mountains, Alps, and parts of the Middle East and Africa. India, China, Nepal, Japan, the USA, and Peru are shown to have landslide-prone areas. This first-cut global landslide susceptibility map forms a starting point to provide a global view of landslide risks and may be used in conjunction with satellite-based precipitation information to potentially detect areas with significant landslide potential due to heavy rainfall. 1

Hong, Yang↗
NASA NTRS2005

Loggers and Forest Fragmentation: Behavioral Models of Road Building in the Amazon Basin

Although a large literature now exists on the drivers of tropical deforestation, less is known about its spatial manifestation. This is a critical shortcoming in our knowledge base since the spatial pattern of land-cover change and forest fragmentation, in particular, strongly affect biodiversity. The purpose of this article is to consider emergent patterns of road networks, the initial proximate cause of fragmentation in tropical forest frontiers. Specifically, we address the road-building processes of loggers who are very active in the Amazon landscape. To this end, we develop an explanation of road expansions, using a positive approach combining a theoretical model of economic behavior with geographic information systems (GIs) software in order to mimic the spatial decisions of road builders. We simulate two types of road extensions commonly found in the Amazon basin in a region: showing the fishbone pattern of fragmentation. Although our simulation results are only partially successful, they call attention to the role of multiple agents in the landscape, the importance of legal and institutional constraints on economic behavior, and the power of GIs as a research tool.

Arima, Eugenio Y.↗
NASA NTRS2007

Regional Sediment Management Experiment Using the Visible/Infrared Imager/Radiometer Suite and the Landsat Data Continuity Mission Sensor

The central aim of this RPC (Rapid Prototyping Capability) experiment is to demonstrate the use of VIIRS (Visible/Infrared Imager/ Radiometer Suite and LDCM (Landsat Data Continuity Mission) sensors as key input to the RSM (Regional Sediment Management) GIS (geographic information system) DSS (Decision Support System). The project affects the Coastal Management National Application.

Estep, Leland↗
NASA NTRS2007

Poly-Pattern Compressive Segmentation of ASTER Data for GIS

Pattern-based segmentation of multi-band image data, such as ASTER, produces one-byte and two-byte approximate compressions. This is a dual segmentation consisting of nested coarser and finer level pattern mappings called poly-patterns. The coarser A-level version is structured for direct incorporation into geographic information systems in the manner of a raster map. GIs renderings of this A-level approximation are called pattern pictures which have the appearance of color enhanced images. The two-byte version consisting of thousands of B-level segments provides a capability for approximate restoration of the multi-band data in selected areas or entire scenes. Poly-patterns are especially useful for purposes of change detection and landscape analysis at multiple scales. The primary author has implemented the segmentation methodology in a public domain software suite.

Myers, Wayne↗