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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Expanding the Operational Use of Total Lightning Ahead of GOES-R

NASA's Short‐term Prediction Research and Transition Center (SPoRT) has been transitioning real‐time total lightning observations from ground‐based lightning mapping arrays since 2003. This initial effort was with the local Weather Forecast Offices (WFO) that could use the North Alabama Lightning Mapping Array (NALMA). These early collaborations established a strong interest in the use of total lightning for WFO operations. In particular the focus started with warning decision support, but has since expanded to include impact‐based decision support and lightning safety. SPoRT has used its experience to establish connections with new lightning mapping arrays as they become available. The GOES‐R / JPSS Visiting Scientist Program has enabled SPoRT to conduct visits to new partners and expand the number of operational users with access to total lightning observations. In early 2014, SPoRT conducted the most recent visiting scientist trips to meet with forecast offices that will used the Colorado, Houston, and Langmuir Lab (New Mexico) lightning mapping arrays. In addition, SPoRT met with the corresponding Center Weather Service Units (CWSUs) to expand collaborations with the aviation community. These visits were an opportunity to learn about the forecast needs of each office visited as well as to provide on‐site training for the use of total lightning, setting the stage for a real‐time assessment during May‐July 2014. With five lightning mapping arrays covering multiple geographic locations, the 2014 assessment has demonstrated numerous uses of total lightning in varying situations. Several highlights include a much broader use of total lightning for impact‐based decision support ranging from airport weather warnings, supporting fire crews, and protecting large outdoor events. The inclusion of the CWSUs has broadened the operational scope of total lightning, demonstrating how these data can support air traffic management, particularly in the Terminal Radar Approach Control Facilities (TRACON) region around an airport. These collaborations continue to demonstrate, from the operational perspective, the utility of total lightning and the importance of continued training and preparation in advance of the Geostationary Lightning Mapper.

GLM↗
NASA NTRS2021

The Large Footprint of Small-scale Artisanal Gold Mining in Ghana

Gold mining has played a significant role in Ghana's economy for centuries. Regulation of this industry has varied over time and while industrial mining is prevalent in the country, the expansion of artisanal mining, or Galamsey has escalated in recent years. Many of these artisanal mines are not only harmful to human health due to the use of Mercury (Hg) in the amalgamation process, but also leave a significant footprint on terrestrial ecosystems, degrading and destroying forested ecosystems in the region. In this study, the Landsat image archive available through Google Earth Engine was used to quantify the total footprint of vegetation loss due to artisanal goldmines in Ghana from 2005 to 2019 and understand how conversion of forested regions to mining has changed over a decadal period from 2007 to 2017. A combination of machine learning and change detection algorithms were used to calculate different land cover conversions and the timing of conversion annually. Within the study area of southwestern Ghana, our results indicate that approximately 47,000 ha (⨦2218 ha) of vegetation were converted to mining at an average rate of ~2600 ha yr−1. The results indicate that a high percentage(~50%) of this mining occurred between 2014 and 2017. Around 700 ha of this mining occurred within protected areas as mapped by the World Database of Protected Areas. In addition to deforestation, increased artisanal mining activity in recent years has the potential to affect human health, access to drinking water resources and food security. This work expands upon limited research into the spatial footprint of Galamseyin Ghana, complements mapping efforts by local geographers, and will support efforts by the government of Ghana to monitor deforestation caused by artisanal mining.

Abigail Barenblitt↗
NASA NTRS2024

Landslide Hazard is Projected to Increase Across High Mountain Asia

High Mountain Asia has long been known as a hotspot for landslide risk, and studies have suggested that landslide hazard is likely to increase in this region over the coming decades. Extreme precipitation may become more frequent, with a nonlinear response relative to increasing global temperatures. However, these changes are geographically varied. This article maps probable changes to landslide hazard, as shown by a landslide hazard indicator (LHI) derived from downscaled precipitation and temperature. In order to capture the nonlinear response of slopes to extreme precipitation, a simple machine-learning model was trained on a database of landslides across High Mountain Asia to develop a regional LHI. This model was applied to statistically downscaled data from the 30 members of the Seamless System for Prediction and Earth System Research large ensembles to produce a range of possible outcomes under the Shared Socioeconomic Pathways 2-4.5 and 5-8.5. The LHI reveals that landslide hazard will increase in most parts of High Mountain Asia. Absolute increases will be highest in already hazardous areas such as the Central Himalaya, but relative change is greatest on the Tibetan Plateau. Even in regions where landslide hazard declines by year 2100, it will increase prior to the mid-century mark. However, the seasonal cycle of landslide occurrence will not change greatly across High Mountain Asia. Although substantial uncertainty remains in these projections, the overall direction of change seems reliable. These findings highlight the importance of continued analysis to inform disaster risk reduction strategies for stakeholders across High Mountain Asia.

Thomas A Stanley↗
NASA NTRS1991

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.↗
DOE OSTI2020

Scalable Data-Intensive Geocomputation: A Design for Real-Time Continental Flood Inundation Mapping

The convergence of data-intensive and extreme-scale computing enables an integrated software and data ecosystem for scientific discovery. Developments in this realm will fuel transformative research in data-driven interdisciplinary domains. Geocomputation provides computing paradigms in Geographic Information Systems (GIS) for interactive computing of geographic data, processes, models, and maps. Because GIS is data-driven, the computational scalability of a geocomputation workflow is directly related to the scale of the GIS data layers, their resolution and extent, as well as the velocity of the geo-located data streams to be processed. Unique in high user interactivity and low end-to-end latency requirements, geocomputation applications will dramatically benefit from the convergence of high-end data analytics (HDA) and high-performance computing (HPC). The application level challenge, however, is to identify and eliminate computational bottlenecks that arise along a geocomputation workflow. Indeed, poor scalability at any of the workflow components is detrimental to the entire end-to-end pipeline. Here, we study a large geocomputation use case in flood inundation mapping that handles multiple national-scale geospatial datasets and targets low end-to-end latency. We discuss benefits and challenges for harnessing both HDA and HPC for data-intensive geospatial data processing and intensive numerical modeling of geographic processes. We propose an HDA+HPC geocomputation architecture design that couples HDA (e.g., Spark)-based spatial data handling and HPC-based parallel data modeling. Key techniques for coupling HDA and HPC to bridge the two different software stacks are reviewed and discussed.

Liu, Yan↗
NASA NTRS2008

Providing Internet Access to High-Resolution Lunar Images

The OnMoon server is a computer program that provides Internet access to high-resolution Lunar images, maps, and elevation data, all suitable for use in geographical information system (GIS) software for generating images, maps, and computational models of the Moon. The OnMoon server implements the Open Geospatial Consortium (OGC) Web Map Service (WMS) server protocol and supports Moon-specific extensions. Unlike other Internet map servers that provide Lunar data using an Earth coordinate system, the OnMoon server supports encoding of data in Moon-specific coordinate systems. The OnMoon server offers access to most of the available high-resolution Lunar image and elevation data. This server can generate image and map files in the tagged image file format (TIFF) or the Joint Photographic Experts Group (JPEG), 8- or 16-bit Portable Network Graphics (PNG), or Keyhole Markup Language (KML) format. Image control is provided by use of the OGC Style Layer Descriptor (SLD) protocol. Full-precision spectral arithmetic processing is also available, by use of a custom SLD extension. This server can dynamically add shaded relief based on the Lunar elevation to any image layer. This server also implements tiled WMS protocol and super-overlay KML for high-performance client application programs.

Plesea, Lucian↗
NASA NTRS2008

Providing Internet Access to High-Resolution Mars Images

The OnMars server is a computer program that provides Internet access to high-resolution Mars images, maps, and elevation data, all suitable for use in geographical information system (GIS) software for generating images, maps, and computational models of Mars. The OnMars server is an implementation of the Open Geospatial Consortium (OGC) Web Map Service (WMS) server. Unlike other Mars Internet map servers that provide Martian data using an Earth coordinate system, the OnMars WMS server supports encoding of data in Mars-specific coordinate systems. The OnMars server offers access to most of the available high-resolution Martian image and elevation data, including an 8-meter-per-pixel uncontrolled mosaic of most of the Mars Global Surveyor (MGS) Mars Observer Camera Narrow Angle (MOCNA) image collection, which is not available elsewhere. This server can generate image and map files in the tagged image file format (TIFF), Joint Photographic Experts Group (JPEG), 8- or 16-bit Portable Network Graphics (PNG), or Keyhole Markup Language (KML) format. Image control is provided by use of the OGC Style Layer Descriptor (SLD) protocol. The OnMars server also implements tiled WMS protocol and super-overlay KML for high-performance client application programs.

Plesea, Lucian↗
NASA NTRS1979

LANDSAT's role in HUD 701 programs

A survey of states concerning the use of LANDSAT in support of the comprehensive planning assistance program (Title IV, section 701) of the Housing and Community Development Act (1974) which is aimed mostly at small communities and rural counties, shows: (1) state governments used or were aware of the application of LANDSAT for inventorying land use and land cover at the state and local level; (2) use of satellite data was associated with the development of automated geographic information systems and the computer capability of handling and analyzing mapped information and other data tied to geographic coordinates and boundaries; and (3) LANDSAT capabilities in states tend to be institutionalized within state government information services where they can be readily assessed by state agencies. A summary of the state program for New Jersey and South Dakota is presented along with the state development guide plans, the rationale for using the satellite, and potential applications.

Source record↗
NASA NTRS2007

Using MODIS and GLAS Data to Develop Timber Volume Estimates in Central Siberia

The boreal forest is the Earth's largest terrestrial biome, covering some 12 million km2 and accounting for about one third of this planet's total forest area. Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. Ground based forest inventories, have much uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse and/or lacking. In addition, many of the forest inventories that do exist for Siberia are now a decade or more old. Thus, available forest inventories fail to capture the current conditions. Changes in forest structure in a particular forest-type and region can change significantly due to changing environment conditions, and natural and anthropogenic disturbance. Remote sensing methods can potentially overcome these problems. Multispectral sensors can be used to provide vegetation cover maps that show a timely and accurate geographic distribution of vegetation types rather than decade old ground based maps. Lidar sensors can be used to directly obtain measurements that can be used to derive critical forest structure information (e.g., height, density, and volume). These in turn can used to estimate biomass components using allometric equations without having to use out dated forest inventory. Finally, remote sensing data is ideally suited to provide a sampling basis for a rigorous statistical estimate of the variance and error bound on forest structure measures. In this study, new remote sensing methods were applied to develop estimates timber volume using NASA's MODerate resolution Imaging Spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) for a 10 deg x 10 deg area in central Siberia. Using MODIS and GLAS data, maps were produced for cover type and timber volume for 2003, and a realistic variance (error bound) for timber volume was calculated for the study area. In this 'study we used only GLAS footprints that had a slope value of less than 10 deg. This was done to avoid large errors due to the effect of slope on the GLAS models. The method requires the integration of new remote sensing methods with available ground studies of forest timber volume conducted in Russian forests. The results were compared to traditional ground forest inventory methods reported in the literature and to ground truth collected in the study area.

Ranson, K. Jon↗
NASA NTRS1975

Low-cost data analysis systems for processing multispectral scanner data

A research-oriented data analysis system was developed which is used for evaluating complex remote sensor systems and for development of techniques for application of remotely sensed data. Some modular hardware components were developed which may be added to one's existing facilities to establish a low-cost data analysis system for processing multispectral scanner data. Software modules which are compatible with small general purpose digital computers process and analyze remote sensor data, and convert it to information needed by users. The software modules are written in FORTRAN IV language for ease of transfer to other computer systems. The basic hardware and software system requirements are defined for some low-cost data analysis systems consisting of an image display system, a small general purpose digital computer, and an output recording device. The hardware modules consist of: a LANDSAT MSS data reformatting program; a series of spectral pattern recognition programs required to generate surface classification maps and tabular information; programs to convert computer generated maps from image space to a geographically referenced base; programs to extract data and irregularly shaped areas and to produce thematic maps of the designated areas; and programs to tabulate acreages of selected classification categories. Some off-the-shelf, inexpensive digital image display systems are described.

Whitley, S. L.↗
NASA NTRS1979

Central atlantic regional ecological test site: A prototype regional environmental information system, volume 1

The Central Atlantic Regional Ecological Test Site (CARETS) project was a demonstration project for introducing data from Landsat and high-altitude aircraft sensors into regional land planning and management. This report summarizes the CARETS project results and describes its output of maps, reports, computer tapes, and other products. CARETS used a geographic information system model under which land use maps were prepared from sensor data, then digitized, processed, and linked to other environmental and social data sets, and to environmental consequences such as air pollution, stream runoff, local climatic factors, and coastal erosion. Landsat data showed the test region in 1972 to be nine percent urban and built-up land, 38 percent agriculture, 50 percent forest, three percent nonforested wetlands, and less than one percent barren land, exclusive of water-covered areas. User surveys, conferences, and workshops involving 65 agencies facilitated widespread distribution of data products and produced evaluations concerning their usefulness. We found a heterogeneous user community with diverse information needs largely preferring aerial photographs rather than satellite multispectral scanner data. Among project recommendations are establishment of a network of regional land resource information centers, working toward improved compatibility of Federal, State and local information programs supportive of land use decisions.

Land use↗
NASA NTRS1975

Radar for small-scale land-use mapping

Small-scale (1:250,000 and smaller) land-use maps are a major concern not only to geographers but also to national and regional planners. Unfortunately, such maps are usually out of date by the time they are printed. An interpretation key consisting of five physical and cultural characteristics of the environment evident on radar imagery is used to create land-use regions. Regions and borders interpreted from radar are compared with those found on two existing land-use maps created by traditional methods. Radar imagery can be used to create a small-scale land-use map with regions comparable to those found on existing land-use maps. However, the radar regions depict something more than land use and should be termed rural landscape regions.

Henderson, F. M.↗
NASA NTRS1982

Pilot study of the domestic information display system in state and local government

An interactive computer based system that can retrieve a wide range of data (demographic, environmental, socio-economic, etc.,) from a large data base and display these data for different geographic units in the form of choropleth maps was developed. The system was designed to display statistical information in a geographic format for national policy makers.

Source record↗
NASA NTRS1993

The effect of scene content on speed, time, and distance perception

Helicopter flights performed at low-levels place high demands on pilots; they must simultaneously control the vehicle, avoid obstacles, and navigate. Therefore, pilots must correlate cues viewed in the external scene with information on map in order to maintain their geographical orientation. This is a particularly difficult task when helicopter pilots fly through visually unfamiliar terrain without highly detailed maps. As a result, pilots must often use estimates of elapsed time, distance traveled, and/or average speed in order to maintain a flight path indicated on a map during flight segments when these cues are absent. Therefore, the current study is concerned with the perception of speed, time, and distance, which we assume underlies the ability to orient oneself during these types of flight segments.

Awe, Cynthia A.↗
NASA NTRS2003

Digital Images on the DIME

With NASA on its side, Positive Systems, Inc., of Whitefish, Montana, is veering away from the industry standards defined for producing and processing remotely sensed images. A top developer of imaging products for geographic information system (GIS) and computer-aided design (CAD) applications, Positive Systems is bucking traditional imaging concepts with a cost-effective and time-saving software tool called Digital Images Made Easy (DIME(trademark)). Like piecing a jigsaw puzzle together, DIME can integrate a series of raw aerial or satellite snapshots into a single, seamless panoramic image, known as a 'mosaic.' The 'mosaicked' images serve as useful backdrops to GIS maps - which typically consist of line drawings called 'vectors' - by allowing users to view a multidimensional map that provides substantially more geographic information.

Source record↗
NASA NTRS1998

Variability of Arctic Sea Ice as Viewed from Space

Over the past 20 years, satellite passive-microwave radiometry has provided a marvelous means for obtaining information about the variability of the Arctic sea ice cover and particularly about sea ice concentrations (% areal coverages) and from them ice extents and the lengths of the sea ice season. This ability derives from the sharp contrast between the microwave emissions of sea ice versus liquid water and allows routine monitoring of the vast Arctic sea ice cover, which typically varies in extent from a minimum of about 8,000,000 sq km in September to a maximum of about 15,000,000 sq km in March, the latter value being over 1.5 times the area of either the United States or Canada. The vast Arctic ice cover has many impacts, including hindering heat, mass, and y momentum exchanges between the oceans and the atmosphere, reducing the amount of solar radiation absorbed at the Earth's surface, affecting freshwater transports and ocean circulation, and serving as a vital surface for many species of polar animals. These direct impacts also lead to indirect impacts, including effects on local and perhaps global atmospheric temperatures, effects that are being examined in general circulation modeling studies, where preliminary results indicate that changes on the order of a few percent sea ice concentration can lead to temperature changes of 1 K or greater even in local areas outside of the sea ice region. Satellite passive-microwave data for November 1978 through December 1996 reveal marked regional and interannual variabilities in both the ice extents and the lengths of the sea ice season, as well as some statistically significant trends. For the north polar ice cover as a whole, maximum ice extents varied over a range of 14,700,000 - 15,900,000 km(2), while individual regions showed much greater percentage variations, e.g., with the Greenland Sea experiencing a range of 740,000 - 1,1110,000 km(2) in its yearly maximum ice coverage. Although variations from year to year and region to region are large, overall the Arctic ice extents did show a statistically significant, 2.8%/ decade negative trend over the 18.2-year period. Ice season lengths, which vary from only a few weeks near the ice margins to the full year in the large region of perennial ice coverage, also experienced interannual variability, and mapping their trends allows detailed geographic information on exactly where the ice season lengthened and where it shortened. Over the 18 years, ice season lengthening occurred predominantly in the western hemisphere and was strongest in the western Labrador Sea, while ice season shortening occurred predominantly in the eastern hemisphere and was strongest in the eastern Barents Sea. Much information about other important Arctic sea ice variables has also been obtained from satellite data, including information about melt ponding, temperature, snow cover, and ice velocities. For instance, maps of ice velocities have now been made from satellite scatterometry data, including information about melt ponding, temperature, snow cover, and ice velocities.

Parkinson, Claire L.↗
DOE OSTI2024

Upscaling Soil Organic Carbon Measurements at the Continental Scale Using Multivariate Clustering Analysis and Machine Learning

Abstract Estimates of soil organic carbon (SOC) stocks are essential for many environmental applications. However, significant inconsistencies exist in SOC stock estimates for the U.S. across current SOC maps. We propose a framework that combines unsupervised multivariate geographic clustering (MGC) and supervised Random Forests regression, improving SOC maps by capturing heterogeneous relationships with SOC drivers. We first used MGC to divide the U.S. into 20 SOC regions based on the similarity of covariates (soil biogeochemical, bioclimatic, biological, and physiographic variables). Subsequently, separate Random Forests models were trained for each SOC region, utilizing environmental covariates and SOC observations. Our estimated SOC stocks for the U.S. (52.6 ± 3.2 Pg for 0–30 cm and 108.3 ± 8.2 Pg for 0–100 cm depth) were within the range estimated by existing products like Harmonized World Soil Database, HWSD (46.7 Pg for 0–30 cm and 90.7 Pg for 0–100 cm depth) and SoilGrids 2.0 (45.7 Pg for 0–30 cm and 133.0 Pg for 0–100 cm depth). However, independent validation with soil profile data from the National Ecological Observatory Network showed that our approach ( R 2 = 0.51) outperformed the estimates obtained from Harmonized World Soil Database ( R 2 = 0.23) and SoilGrids 2.0 ( R 2 = 0.39) for the topsoil (0–30 cm). Uncertainty analysis (e.g., low representativeness and high coefficients of variation) identified regions requiring more measurements, such as Alaska and the deserts of the U.S. Southwest. Our approach effectively captures the heterogeneous relationships between widely available predictors and the current SOC baseline across regions, offering reliable SOC estimates at 1 km resolution for benchmarking Earth system models.

58 GEOSCIENCES↗
DOE OSTI2020

First Analysis of Earth's Stratospheric γ ‐Ray Emission in Geographical Coordinates With Fermi LAT

Abstract From low‐Earth orbit, the Earth is an extremely bright γ ‐ray source compared to distant astrophysical objects. The high‐energy γ ‐ray emission, from the Earth's upper atmosphere, is produced by the interactions between cosmic rays (CRs) and air molecules. As CRs are predominantly charged particles, the geomagnetic field acts as a spectrometer, forbidding CRs below a certain energy to arrive and interact with the atmosphere at a given geomagnetic location from a given direction. We use photon data between 0.2 and 20 GeV as observed by the Fermi Large Area Telescope (LAT) to create, for the first time, stratospheric γ ‐ray emission maps of the Earth in the geographical coordinate system, for different viewing directions from LAT altitude. These maps confirm a strong association between measured γ ‐ray fluxes and geomagnetic cutoffs for CRs. We also report the spectrum of the Earth's stratospheric γ ‐ray emission in cardinal directions and use the geomagnetic spectrometer effect to infer the atmosphere's yield function of γ rays per incoming CR proton as a function of CR rigidity at the altitude of the Fermi spacecraft. This work is relevant to the study of near‐Earth radiation exposure for astronauts and spacecraft, modeling the geomagnetic field, and CR‐air interactions.

Madlee, S.↗