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At least 235 records · Page 13

Integration of visible-through microwave-range multispectral image data sets for geologic mapping

Multispectral remote sensing data sets collected during the Geologic Remote Sensing Field Experiment (GRSFE) conducted during 1989 in the southwestern U.S. were used to produce thematic image maps showing details of the surface geology. LANDSAT TM (Thematic Mapper) images were used to map the distribution of clays, carbonates, and iron oxides. AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data were used to identify and map calcite, dolomite, sericite, hematite, and geothite, including mixtures. TIMS (Thermal Infrared Multispectral Scanner) data were used to map the distribution of igneous rock phases and carbonates based on their silica contents. AIRSAR (Airborne Synthetic Aperture Radar) data were used to map surface textures related to the scale of surface roughness. The AIRSAR also allowed identification of previously unmapped fault segments and structural control of lithology and minerology. Because all of the above data sets were geographically referenced, combination of different data types and direct comparison of the results with conventional field and laboratory data sets allowed improved geologic mapping of the test site.

Kruse, Fred A.↗

Separation of internal and external fields: A new technique of data screening

A method for eliminating transient variation from MAGSAT data is described. Instead of using the conventional Kp index, the Km index is used for the rejection of nonquiet data. To build the Km index, the surface of the Earth is divided in eight sectors. Each sector is defined by two or three magnetic observatories and its geographic limits. For each three hourly interval the MAGSAT tracks were drawn on a map showing the location of the station (the crosses), the limits of the sector, and the value of the mean K index inside each sector. No figure in a sector means that the activity level in this sector is lower than 5 nt; in a sector covered with number 1, the activity lies between 5 and 20 nt; 2 stands for any level greater than 20 nT.

Lemouel, J. L.↗

Threatened and Endangered Species Survey for Patrick Air Force Base, Florida

A review of previous environmental work conducted at Patrick Air Force Base (PAFB) indicated that several threatened, endangered, or species of special concern occurred or had the potential to occur there. This study was implemented to collect more information on protected species at PAFB. A map of landcover types was prepared for PAFB using aerial photography, groundtruthing, and a geographic information system (GIS). Herbaceous vegetation was the most common vegetation type. The second most abundant vegetation type was disturbed shrubs/exotics. The beach and associated dune vegetation comprised 3.2% of the land area, but was the most extensive natural community within PAFB. A few isolated mangrove communities exist along the Banana River. Seventy-seven species of vascular plants occurred on the dunes, including four species listed by state agencies: spider lily (Hymenocallis latifolia), prickly pear cactus (Opuntia stricta), beach star (Remirea maritima), and inkberry (Scaevola plumien). Surveys of other habitats revealed eighty-four species of vascular plants including two state-listed species: spider lily and prickly pear cactus. Many of these areas are dominated by invasive, exotic species, particularly Brazilian pepper (Schinus terebinthifolius) and Australian pine (Casuarina equisetifolia), and native species of open or disturbed sites such as camphorweed (Heterotheca subaxillaris) and beardgrass (Andropogon spp.). Due to the isolation of PAFB from other natural areas, most exotic plant populations on the base are not an immediate threat to intact native plant communities. Dune habitat was surveyed for the southeastem beach mouse (Peromyscus polionotus niveiventris) by quarterly trapping along eight 100 m transects. No beach mice were found. The limited extent of dune habitat, its fragmented condition, and the isolation of PAFB from extant populations of the beach mouse probably accounts for its absence. Surveys of birds on PAFB found an avifauna characteristic of species that occur in the Indian River Lagoon system. Twenty-five species of waterbirds were observed during quarterly surveys on PAFB, including five species listed as species of special concern by the state of Florida: Snowy Egret (Egretta thula), Little Blue Heron (Egretta caerulea), Tricolored Heron (Egretta tricolo4, White Ibis (Eudocimus albus), and Brown Pelican (Pelecanus occidentalis). The Golf Course was used extensively by almost all species of waterbirds on PAFB. Twenty-two species of shorebirds were observed on PAFB. Although no listed species were observed, the potential exists for several protected species of shorebirds to use the beach at PAFB during some parts of the year. The Airfield runways and associated grass areas were important sites at PAFB for loafing and feeding for some shorebirds. Surveys of rooftop nesting by Least Terns (Stema antillarum) on PAFB found a large colony on a rooftop in the PAFB Industrial Area. This colony produced some independent young. Two rooftop Least Tern colonies reported from previous years were inactive during 1996. A small number of Black Skimmers (Rhynchops nigee attempted to nest at the Least Ten colony but were unsuccessful. Surveys for the gopher tortoise (Gopherus polyphemus) revealed burrows and tortoises only at the Waste Study Site; five burrows and three tortoises were observed. No Florida scrub lizards (Sceloporus woodi), eastern indigo snakes (Drymarchon corais couperl), or diamondback terrapins (Malademys terrapin terrapin) were observed. American alligators (Alligator mississippiensis) were observed on the Golf Course and using ditches, ponds, and areas along the Banana River. The amount of dune habitat could be expanded by not mowing areas adjacent to the dunes to allow dune species to colonize and expand. Planting dune species as part of the beach renourishment project will also increase this habitat. Exotic plants dominate several areas on the base and are used by threatened, endangered, and species of special concern. However, the use of native vegetation in landscaping projects throughout the base would improve habitat for wildlife, and invasive, exotic plants should not be used in any horticultural plantings. Water quality of ponds, ditches, and canals is important for waterbirds; it should be maintained and protected from contamination. Nesting Least Terns are sensitive to disturbance; rooftops used for nesting should be protected from disturbance. Monitoring of Least Tern and Black Skimmer nesting should be continued to determine what roofs are being used and whether nesting is successful. Furthermore, based on the large numbers of waterbirds observed on PAFB, continued monitoring of them is recommended.

Oddy, Donna M.↗

Issues in Defining Software Architectures in a GIS Environment

The primary mission of the Pan-American Center for Earth and Environmental Studies (PACES) is to advance the research areas that are relevant to NASA's Mission to Planet Earth program. One of the activities at PACES is the establishment of a repository for geographical, geological and environmental information that covers various regions of Mexico and the southwest region of the U.S. and that is acquired from NASA and other sources through remote sensing, ground studies or paper-based maps. The center will be providing access of this information to other government entities in the U.S. and Mexico, and research groups from universities, national laboratories and industry. Geographical Information Systems(GIS) provide the means to manage, manipulate, analyze and display geographically referenced information that will be managed by PACES. Excellent off-the-shelf software exists for a complete GIS as well as software for storing and managing spatial databases, processing images, networking and viewing maps with layered information. This allows the user flexibility in combining systems to create a GIS or to mix these software packages with custom-built application programs. Software architectural languages provide the ability to specify the computational components and interactions among these components, an important topic in the domain of GIS because of the need to integrate numerous software packages. This paper discusses the characteristics that architectural languages address with respect to the issues relating to the data that must be communicated between software systems and components when systems interact. The paper presents a background on GIS in section 2. Section 3 gives an overview of software architecture and architectural languages. Section 4 suggests issues that may be of concern when defining the software architecture of a GIS. The last section discusses the future research effort and finishes with a summary.

Acosta, Jesus↗

Bounding Species Distribution Models

Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for "clamping" model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5): 642-647, 2011].

Stohlgren, Thomas J.↗

The verification of LANDSAT data in the geographical analysis of wetlands in west Tennessee

The reliability of LANDSAT imagery as a medium for identifying, delimiting, monitoring, measuring, and mapping wetlands in west Tennessee was assessed to verify LANDSAT as an accurate, efficient cartographic tool that could be employed by a wide range of users to study wetland dynamics. The verification procedure was based on the visual interpretation and measurement of multispectral imagery. The accuracy testing procedure was predicated on surrogate ground truth data gleaned from medium altitude imagery of the wetlands. Fourteen sites or case study areas were selected from individual 9 x 9 inch photo frames on the aerial photography. These sites were then used as data control calibration parameters for assessing the cartography accuracy of the LANDSAT imagery. An analysis of results obtained from the verification tests indicated that 1:250,000 scale LANDSAT data were the most reliable scale of imagery for visually mapping and measuring wetlands using the area grid technique. The mean areal percentage of accuracy was 93.54 percent (real) and 96.93 percent (absolute). As a test of accuracy, the LANDSAT 1:250,000 scale overall wetland measurements were compared with an area cell mensuration of the swamplands from 1:130,000 scale color infrared U-2 aircraft imagery. The comparative totals substantiated the results from the LANDSAT verification procedure.

Rehder, J.↗

Interdisciplinary research on the application of ERTS-1 data to the regional land use planning process

The author has identified the following significant results. Although the degree to which ERTS-1 imagery can satisfy regional land use planning data needs is not yet known, it appears to offer means by which the data acquisition process can be immeasurably improved. The initial experiences of an interdisciplinary group attempting to formulate ways of analyzing the effectiveness of ERTS-1 imagery as a base for environmental monitoring and the resolution of regional land allocation problems are documented. Application of imagery to the regional planning process consists of utilizing representative geographical regions within the state of Wisconsin. Because of the need to describe and depict regional resource complexity in an interrelatable state, certain resources within the geographical regions have been inventoried and stored in a two-dimensional computer-based map form. Computer oriented processes were developed to provide for the economical storage, analysis, and spatial display of natural and cultural data for regional land use planning purposes. The authors are optimistic that the imagery will provide revelant data for land use decision making at regional levels.

Clapp, J. L.↗

Interdisciplinary research on the application of ERTS-1 data to the regional land use planning process.

Although the degree to which ERTS-1 imagery can satisfy regional land use planning data needs is not yet known, it appears to offer means by which the data acquisition process can be immeasurably improved. This paper documents the initial experiences of an interdisciplinary group attempting to formulate ways of analyzing the effectiveness of ERTS-1 imagery as a base for environmental monitoring and the resolution of regional land allocation problems. Because of the need to describe and depict regional resource complexity in an interrelatable state, certain resources within the geographical regions have been inventoried and stored in a two-dimensional computer-based map form. Computer oriented processes were developed to provide for the economical storage, analysis and spatial display of natural and cultural data for regional land use planning purposes. Statistical programs have been developed that correlate interpreted data with stored data, both spatially and numerically.

Clapp, J. L.↗

Northern Great Plains Disasters: Using Earth Observations to Enhance Flood Monitoring on Tribal Lands in the Northern Great Plains

In 2019, the Great Plains experienced unprecedented catastrophic flooding. Large flood events are predicted to increase in frequency and severity, posing risks to communities in this region, particularly Tribal Nations. We used data from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), imagery from the Sentinel-2 MultiSpectral Instrument (MSI), and digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM) within Google Earth Engine to map historical floods in the region beginning in 2014 with particular attention to the Rosebud Sioux Reservation and the tribal lands of other Great Plains Tribal Water Alliance members. This historical mapping used C-SAR for a combined method approach with a Z-score algorithm in addition to an index for flooded short vegetation. We also developed a flood risk map by weighting different flood predictor variables according to flood risk literature. These variables included soil drainage from the Soil Survey Geographic Database (SSURGO); elevation, slope, and Topographic Wetness Index (TWI) derived from digital elevation models; precipitation from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS); land cover from the National Land Cover Database (NLDC); and Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 Operational Land Imager (OLI). From the flood extent and risk maps, we identified widespread flooding in short vegetation (including cropland) and noted flood susceptibility in regions exhibiting high social vulnerability and low community resilience (FEMA indices). We created an ArcGIS Online StoryMap to share project background, results, and data. Additionally, we provided a written tutorial so partners may replicate the flood mapping for future flood events.

Anna Ballasiotes↗

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

Segments↗

Processing Satellite Imagery To Detect Waste Tire Piles

A methodology for processing commercially available satellite spectral imagery has been developed to enable identification and mapping of waste tire piles in California. The California Integrated Waste Management Board initiated the project and provided funding for the method s development. The methodology includes the use of a combination of previously commercially available image-processing and georeferencing software used to develop a model that specifically distinguishes between tire piles and other objects. The methodology reduces the time that must be spent to initially survey a region for tire sites, thereby increasing inspectors and managers time available for remediation of the sites. Remediation is needed because millions of used tires are discarded every year, waste tire piles pose fire hazards, and mosquitoes often breed in water trapped in tires. It should be possible to adapt the methodology to regions outside California by modifying some of the algorithms implemented in the software to account for geographic differences in spectral characteristics associated with terrain and climate. The task of identifying tire piles in satellite imagery is uniquely challenging because of their low reflectance levels: Tires tend to be spectrally confused with shadows and deep water, both of which reflect little light to satellite-borne imaging systems. In this methodology, the challenge is met, in part, by use of software that implements the Tire Identification from Reflectance (TIRe) model. The development of the TIRe model included incorporation of lessons learned in previous research on the detection and mapping of tire piles by use of manual/ visual and/or computational analysis of aerial and satellite imagery. The TIRe model is a computational model for identifying tire piles and discriminating between tire piles and other objects. The input to the TIRe model is the georeferenced but otherwise raw satellite spectral images of a geographic region to be surveyed. The TIRe model identifies the darkest objects in the images and, on the basis of spatial and spectral image characteristics, discriminates against other dark objects, which can include vegetation, some bodies of water, and dark soils. The TIRe model can identify piles of as few as 100 tires. The output of the TIRe model is a binary mask showing areas containing suspected tire piles and spectrally similar features. This mask is overlaid on the original satellite imagery and examined by a trained image analyst, who strives to further discriminate against non-tire objects that the TIRe model tentatively identified as tire piles. After the analyst has made adjustments, the mask is used to create a synoptic, geographically accurate tire-pile survey map, which can be overlaid with a road map and/or any other map or set of georeferenced data, according to a customer s preferences.

Skiles, Joseph↗

More Efficient Precipitation Rate Data Acquisition with the STORM Swath-Based Analysis Tool

A multitude of locations exist for acquiring satellite-derived precipitation rate data. Because the volume of data exceeds what can reasonably be analyzed manually, online tools have been developed to help researchers make more informed data acquisition decisions. Some interfaces provide sample images generated from prioritized variables to enable efficient visual inspection, while others include the ability to subset geographically to reduce the volume of the data to the area of interest. Building upon such value-added services is the STORM (the NASA Precipitation Processing System (PPS) data product ordering system) Swath-Based Analysis Tool (https://storm.pps.eosdis.nasa.gov/storm/Analysis.jsp). With it, users can compare overflights of multiple precipitation satellites simultaneously and from this make determinations about which swaths will best serve their research. They can preview these overflights with two distinct visualization tools. Finally, they can then download geographically subset swaths that have precipitation rate characteristics matching their research needs. A user starts by making up to six selections. They then select their date range of interest going back to 1997. Finally, they select a geographical region either by inputting latitude-longitude corners of a rectangle or drawing that rectangle on an interactive map. The system processes each file, determining aggregate statistics about the precipitation rates within the selected region as observed by each instrument. These statistical values are added to a time series graph as a "time remaining" counter is continuously updated. The chart is fully interactive, with detailed values displayed upon mouseover, and numerous options available upon clicking each point. Since the user is likely to need the relevant files for their own research, they can generate an order from their request. All files are geographically subset to the region of interest, and the user can use the statistical values to limit which files are added to the order. This flexibility helps to ensure researchers are only downloading the files they need for their work, making for a more efficient process both from a time-consumption and a storage perspective. This paper will introduce the Swath-Based Analysis Tool and explore its numerous features. It will discuss several use cases for precipitation scientists.

remote sensing↗

Terrain profiling from Seasat altimetry

To determine their applicability for terrain profiling, Seasat altimeter measurements were analyzed for the following geographic areas: (1) Andean salars of southern Bolivia; (2) Alaska; (3) south-central Arizona; (4) imperial Valley of California; (5) Yuma Valley of Arizona; and (6) Great Salt Lake Desert. Analysis of the data over all of these geographic areas shows that the satellite altimeter servo did not respond quickly enough to changing terrain features. However, it is demonstrated that retracking of the archived surface return waveforms yields surface elevations over smooth terrain accurate to + or - 1 m when correlated with large scale maps. The retracking algorithm used and its verification over the salars of southern Bolivia are described. Results are presented for each of the six geographic areas.

Brooks, R. L.↗

Fusion Approach for Remotely-Sensed Mapping of Agriculture (FARMA): A Scalable Open Source Method for Land Cover Monitoring Using Data Fusion

The increasing availability of very-high resolution (VHR; <2 m) imagery has the potential to enable agricultural monitoring at increased resolution and cadence, particularly when used in combination with widely available moderate-resolution imagery. However, scaling limitations exist at the regional level due to big data volumes and processing constraints. Here, we demonstrate the Fusion Approach for Remotely-Sensed Mapping of Agriculture (FARMA), using a suite of open source software capable of efficiently characterizing time-series field-scale statistics across large geographical areas at VHR resolution. We provide distinct implementation examples in Vietnam and Senegal to demonstrate the approach using WorldView VHR optical, Sentinel-1 Synthetic Aperture Radar, and Sentinel-2 and Sentinel-3 optical imagery. This distributed software is open source and entirely scalable, enabling large area mapping even with modest computing power. FARMA provides the ability to extract and monitor sub-hectare fields with multisensor raster signals, which previously could only be achieved at scale with large computational resources. Implementing FARMA could enhance predictive yield models by delineating boundaries and tracking productivity of smallholder fields, enabling more precise food security observations in low and lower-middle income countries.

fusion↗

Earth radiation budget measurements from satellites and their interpretation for climate modeling and studies

The annual and seasonal averaged Earth atmosphere radiation budgets derived from the most complete set of satellite observations available are presented. The budgets were derived from a composite of 48 monthly mean radiation budget maps. Annually and seasonally averaged radiation budgets are presented as global averages and zonal averages. The geographic distribution of the various radiation budget quantities is described. The annual cycle of the radiation budget was analyzed and the annual variability of net flux was shown to be largely dominated by the regular semi and annual cycles forced by external Earth-Sun geometry variations. Radiative transfer calculations were compared to the observed budget quantities and surface budgets were additionally computed with particular emphasis on discrepancies that exist between the present computations and previous surface budget estimates.

Vonderhaar, T. H.↗

Needs for registration and rectification of satellite imagery for land use and land cover and hydrologic applications

The use of satellite imagery and data for registration of land use, land cover and hydrology was discussed. Maps and aggregations are made from existing the data in concert with other data in a geographic information system. Basic needs for registration and rectification of satellite imagery related to specifying, reformatting, and overlaying the data are noted. It is found that the data are sufficient for users who must expand much effort in registering data.

Gaydos, L.↗

Image-data-processing for earth resources - An overview

A total remote-sensing system comprises four distinct operations: data-acquisition, archiving, production, and dissemination of individual products, and extraction of the required information. The Landsat satellite system acquires data in several spectral bands, with a ground resolution of 80 meters (currently) or 30 meters (future). Radiometric and geometric corrections are normally applied, after which the data may be enhanced for photointerpretation or analyzed by computer. The accuracy of the analysis model for either is important. The extraction of information from remotely sensed data will generally be dependent on the use of it with other data such as maps or, perhaps, weather information. Methods are being developed to use the various data together in geographic data systems. The availability of remotely sensed data has encouraged the development of new models or analysis procedures for the use of this information.

Billingsley, F. C.↗

Urban Environment Initiative

The Urban Environment Initiative (UEI), has been established as part of a Cooperative Agreement with the National Aeronautics and Space Administration (NASA). The UEI is part of NASA's overall High Performance Computing and Communications (HPCC) and the Information Infrastructure Technology Applications (IITA) programs. The goal of the UEI is to provide public access to Earth Science information and promote its use with a focus on the environment of urban areas. This goal will be accomplished through collaborative efforts of the UEI team with both community-based and local/regional governmental organizations. The UEI team is comprised of four organizations representing private industry, NASA, and universities: Prime Technologies Service Corporation, NASA's Minority University Space Interdisciplinary Network (MU-SPIN) California State University, at Los Angeles, and Central State University (Wilberforce, OH). "Urban Environment" refers to the web of environmental, economic, and social factors that combine to create the urban world in which we live. Examples of these factors are population distribution, neighborhood demographic profiles, economic resources, business activities, location and concentration of environmental hazards and various pollutants, proximity and level of urban services, which form the basis of the urban environment and ultimately affect our lives and experiences. The use of Geographic Information Systems (GIS) and remote sensing allows data to be visualized in the forms of maps and spatial images. The use of these tools allow analysis of information about urban environments. Also included are descriptions of the four query types which will assist in understanding the maps.

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