Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “resource mapping”

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

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

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Mapping Inundation from Hurricane Florence (2018) with L-Band Synthetic Aperture Radar, Commercial Imagery, and Ancillary Data via Machine Learning Classification

During and after flooding events, mapping the extent of floodwaters aids in the distribution of resources, recovery efforts, and damage assessment practices. Development of a land cover classification system focused on mapping inundation after major hurricane events using synthetic aperture radar (SAR) data could allow for the production of near-real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of a developing situation. Complimentary optical and SAR images from domestic and foreign entities are brought together through activations of the International Charter: Space and Major Disasters to support response efforts, from true-color, near-infrared, and thermal remote sensing data obtained by NASA, NOAA, and international satellites to the collection of high-resolution true color aerial photography by NOAA and the National Geodetic Survey. In response to Hurricane Florence of 2018, NASA JPL collected numerous swaths of quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument observing the record-setting river stages across North and South Carolina. The resulting fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging stemming from the sensor’s ability to penetrate cloud cover and dense vegetation. In this study, true-color NOAA aerial and commercial satellite imagery are used in conjunction with four UAVSAR data swaths centered on the Lumberton and Cape Fear River basins in southeastern North Carolina to develop a Random Forest classification model focused on mapping open water and floodwater otherwise obscured by vegetation or lingering cloud cover. Ancillary building footprint, transportation route, and population data will also be incorporated into the classification scheme to estimate the societal impacts of flooding based on the proximity of features to detected inundation. Preliminary results from the Hurricane Florence case study will be discussed in addition to the limitations of available validation data for assessment of the classifier’s accuracy.

Alexander M Melancon↗
NASA NTRS1977

Statistical mapping of sheet aiquile SE-20-9 (national map) making use of ERTS images

New possibilities of remote sensing by means of satellites to do research on natural resources are reported. These images make it possible to carry out integrated studies of natural resources in the shortest time possible and with small investments. Various maps and a complete description of each are included. With the use of these satellites, scientists can hopefully plan development projects at the national level.

Torrez, J. G.↗
NASA NTRS1977

Reindeer range inventory in western Alaska from computer-aided digital classification of LANDSAT data

An inventory of reindeer-range resources was conducted for the USDA Soil Conservation Service of 1.6 million hectares of wildlands in western Alaska using clustering techniques with digital Landsat data. Computer-aided digital analysis produced a provisional map of rangeland types which was used to design the field collection of vegetation and soil types data. This field data facilitated refinement of the inventory map and was used to describe the map units. The informational classes important to range resources were wet, moist and alpine tundra, tidal marsh, brush and open spruce forest. A significant feature of the study was the extraction of acreage figures by administrative boundaries within the study area. In addition to soil and vegetation association map products (at scales of 1:250,000 and 1:63,360) acreage values were tallied from the digital data for each of the four grazing permit areas established by the Bureau of Land Management.

George, T. H.↗
NASA NTRS1982

Geographic Information System in Bolivia: a Case Study for Latin America

Bolivia's Geological Service is concluding a successful project designed to give the Department of Oruro the capability to evaluate its natural resources using data generated by three United States satellites. A permanent integrated geographic information system was created for preparing base maps of soil characteristics, land use, geomorphology, geology, water resources and hydrology. The information compiled through the project was stored on magnetic disks and tapes to permit periodic updating, retrieval of data on specific aspects of development projects, and obtaining various data mixes to analyze aspects of prospective development projects. This is the first digital information system developed in Latin America.

Adrien, P. M.↗
NASA NTRS2016

Extreme Mapping: Looking for Water on the Moon

There are many challenges when exploring extreme environments. Gathering accurate data to build maps about places that you cannot go is incredibly complex. NASA supports scientists by remotely operating robotic rovers to explore uncharted territories. One potential upcoming mission is to look for water near a lunar pole (the Resource Prospector mission). Learn about the technical hurdles and research steps that NASA takes before the mission. NASA practices on Earth with Mission Analogs which simulate the proposed mission. This includes going to lunar-type landscapes, building field networks, testing out rovers, instruments and operational procedures. NASA sets up remote science back rooms just as there are for actual missions. NASA develops custom Ground Data Systems software to support scientific mission planning and monitoring over variable time delays, and separate commanding software and infrastructure to operate the rovers.

MOON↗
NASA NTRS1973

Mapping of soil banks using ERTS-1 pictures

Earth Resources Technology Satellite (ERTS-1) pictures of different wavelengths (MSS 4,5,6,7) were used in the study of two strip mine areas in southeastern Ohio. The first area was near Piedmont Lake and the second area was near New Lexington. Prints were examined under a binocular microscope and the gray tone was correlated with the actual ground conditions at several sites. For the New Lexington area, color infrared pictures taken at an elevation of 18,000 feet were also used for correlation with the ERTS-1 imagery. The results indicate that MSS 5 and 7 are most useful in defining the stripped land and show that the hydrological and soil characteristics are remarkably different than the surrounding lands.

Ahmad, M. U.↗
NASA NTRS1973

Mapping Atlantic coastal marshlands, Maryland, Georgia, using ERTS-1 imagery

Eastern coastal marshes are the most extensive and productive in the United States. A relatively low cost, moderately accurate method is needed to map these areas for management and protection. Groundbased and low-altitude aircraft methods for mapping are time-consuming and quite expensive. The launch of NASA's Earth Resources Technology Satellite has provided an opportunity to test the feasibility of mapping wetlands using small scale imagery. The test sites selected were in Chesapeake Bay, Maryland, and Ossabaw Island, Georgia. Results of the investigation indicate that the following may be ascertained from ERTS imagery, enlarged to 1:250,000: (1) upper wetland boundary; (2) drainage pattern in the wetland; (3) plant communities; (4) ditching activities associated with agriculture; and (5) lagooning for water-side home development. Conclusions are that ERTS will be an excellent tool for many types of coastal wetland mapping.

Anderson, R. R.↗
NASA NTRS1992

Model-driven mapping onto distributed memory parallel computers

The author addresses the problem of exploiting the parallelism available in a program to efficiently employ the resources of the target machine in the context of building a mapping compiler for a distributed memory parallel machine. He demonstrates the effectiveness of using execution models to select the best mapping technique from among those available for a given program segment on a particular machine. Through analysis of the execution models for several mapping techniques for one class of programs on a linear processor array, it is shown that selecting the best technique for a particular program instance can make a significant difference in performance. On the other hand, the results of benchmarks from a mapping compiler for the Warp systolic array machine show that the execution models considered are accurate enough to select the best mapping technique for a given program.

Sussman, Alan↗
NASA NTRS2014

The Development of a Long-Term, Continually Updated Global Solar Resource at 10 km Resolution: Preliminary Results From Test Processing and Continuing Plans

Background: Considering the likelihood of global climatic weather pattern changes and the global competition for energy resources, there is an increasing need to provide improved and continuously updated global Earth surface solar resource information. Toward this end, a project was funded under the NASA Applied Science program involving the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC), National Renewable Energy Laboratory (NREL), the State University of New York/Albany (SUNY) and the NOAA National Climatic Data Center (NCDC) to provide NREL with a global long-term advanced global solar mapping production system for improved depiction of historical solar resources and variability and to provide a mechanism for continual updates of solar resource information. This new production system is made possible by the efforts of NOAA and NASA to completely reprocess the International Satellite Cloud Climatology Project (ISCCP) data set that provides satellite visible and infrared radiances together with retrieved cloud and surface properties on a 3-hourly basis beginning from July 1983. The old version of the ISCCP data provided this information for all the world TMs available geosynchronous satellite systems and NOAA TMs AVHRR data sets at a 30 km effective resolution. This new version aims to provide a new and improved satellite calibration at an effective 10 km resolution. Thus, working with SUNY, NASA will develop and test an improved production system that will enable NREL to continually update the Earth TM solar resource. Objective and Methods: In this presentation, we provide a general overview of this project together with samples of the new solar irradiance mapped data products and comparisons to surface measurements at various locations across the world. An assessment of the solar resource values relative to calibration uncertainty and assumptions are presented. Errors resulting assumptions in snow cover and background aerosol amount are described. These uncertainties and the statistics of the agreement between the measurements and new satellite estimates are also reviewed and compared to other solar data sets. Findings and Conclusions: Preliminary results show that insolation values show an overall small bias (less than 1%) with a RMS of 25% relative to surface measurements. Exceptions at certain locations were found and will be discussed relative to the uncertainties identified above. Lastly, we will identify the next steps in the development and improvement of this production system including some accuracy goals in preparation for ultimate delivery to NREL.

Stackhouse, P.↗
NASA NTRS2001

Lightning Detection in a Flash

In a joint project with NASA's Kennedy Space Center, Global Atmospherics, Inc. (GAI), participated in the upgrade and commercialization of the Lightning Detection and Ranging (LDAR) System. Under a Space Act Agreement, GAI and Kennedy agreed to the joint development of a new LDAR system that meets the needs of both NASA and private industry. The resulting development was a volumetric lightning mapping system. NASA operates a three- dimensional LDAR system capable of determining the exact location and altitude of in-cloud and cloud-to-cloud lightning. Under the Space Act Agreement, GAI contributed its wealth of experience and resources to update and improve the current lightning mapping system used by NASA. Previously, commercial systems were only capable of locating cloud-to-ground lightning. The resulting innovations allowed GAI to position the LDAR system for commercial applications. The upgraded product has the ability to measure in-cloud and cloud-to-cloud lightning. Notable improvements have also been made in the system's location accuracy and signal detection. The new product, known as LDAR II, is targeted for use by utility providers, aviation companies, airports, and commercial space vehicle launch facilities. Presently, forecasting services, research facilities, and a utility company are using the system.

Source record↗
NASA NTRS2019

Evaluating Combinations of Sentinel-2 Data and Machine-Learning Algorithms for Mangrove Mapping in West Africa

Creating a national baseline for natural resources, such as mangrove forests, and monitoring them regularly often requires a consistent and robust methodology. With freely available satellite data archives and cloud computing resources, it is now more accessible to conduct such large-scale monitoring and assessment. Yet, few studies examine the reproducibility of such mangrove monitoring frameworks, especially in terms of generating consistent spatial extent. Our objective was to evaluate a combination of image processing approaches to classify mangrove forests along the coast of Senegal and The Gambia. We used freely available global satellite data (Sentinel-2), and cloud computing platform (Google Earth Engine) to run two machine learning algorithms, random forest (RF), and classification and regression trees (CART). We calibrated and validated the algorithms using 800 reference points collected using high-resolution images. We further re-ran 10 iterations for each algorithm, utilizing unique subsets of the initial training data. While all iterations resulted in thematic mangrove maps with over 90% accuracy, the mangrove extent ranges between 827-2807 km2 for Senegal and 245-1271 km2 for The Gambia with one outlier for each country. We further report "Places of Agreement" (PoA) to identify areas where all iterations for both methods agree (506.6 km2 and 129.6 km2 for Senegal and The Gambia, respectively), thus have a high confidence in predicting mangrove extent. While we acknowledge the time- and cost-effectiveness of such methods for the landscape managers, we recommend utilizing them with utmost caution, as well as post-classification on-the-ground checks, especially for decision making.

Mondal, Pinki↗
NASA NTRS2015

Opportunities and Strategies for Testing and Infusion of ISRU in the Evolvable Mars Campaign

HE Evolvable Mars Campaign (EMC) is developing the plans and systems needed for a robust, evolutionary strategy to explore cis-lunar space, the Mars sphere of influence (including the moons of Mars), and the surface of Mars. Recently, the emphasis of NASA's plans has changed to focus on the prolonged pioneering of space, rather than focusing on a single crewed mission as the ultimate goal. A sustainable, pioneering vision of space would include in-situ resource utilization (ISRU) in multiple forms and at multiple destinations: atmospheric capture of Mars CO2 and/or volatiles for consumables and propellants, regolith for bulk and refined materials, and in-situ manufacturing at the Moon, Mars, and other bodies. These resources would enable a reduction in the logistical needs from Earth for future missions, thus preparing the way for a sustained presence on Mars. Although the EMC initially relies only on propellant production for the Mars ascent vehicle via ISRU, one of its primary objectives is to prospect at every EMC destination to understand the potential for ISRU; this will permit true pioneering to be enabled after the first crew arrives at Mars. Recent and ongoing analysis has considered the possible prospecting measurements that can be performed at the asteroid returned to cis-lunar space by the Asteroid Robotic Redirect Mission (ARRM), at the lunar surface, at Phobos and Deimos, and on the surface of Mars to identify available resources for future use. These opportunities will be available on missions currently in the Evolvable Mars Campaign construct, and will also facilitate the testing and demonstration of resource acquisition, processing, storage, and useage technologies that can play a role in later missions. This analysis has also led to the identification of several objectives that should be targeted during the missions building up to and including the initial crewed missions. These objectives are mapped to strategies for incorporating ISRU to support resource cycle closure and reduce mass requirements from Earth. This analysis has yielded engineering constraints, based on ISRU, that impact the evaluation of landing sites for missions to the surface of Mars. The terrain of a particular site must be sufficiently flat to permit ISRU systems, as well as ancillary systems such as power and propellant storage tanks, to be landed, moved into position, set up, and operated. Water must be accessible in a form that can be acquired via ISRU, in quantities that align with demands. The chosen method of acquiring and processing water should align with the available resources at a particular site, and that site must have sufficient quantities to meet the requirements (based on crew consumables and propellant demands). Lower altitude landing sites are preferred, as the increase in density can facilitate carbon dioxide acquisition from the atmosphere. Another preference is for sites with a greater ability to move regolith for civil engineering purposes; for example, this would be conducive to both bulk regolith uses (such as the manufacture of berms), and processed regolith uses (such as microwave sintering).

Evolvable Mars Campaign↗
NASA NTRS2003

Applications of UAVs for Remote Sensing of Critical Infrastructure

The surveillance of critical facilities and national infrastructure such as waterways, roadways, pipelines and utilities requires advanced technological tools to provide timely, up to date information on structure status and integrity. Unmanned Aerial Vehicles (UAVs) are uniquely suited for these tasks, having large payload and long duration capabilities. UAVs also have the capability to fly dangerous and dull missions, orbiting for 24 hours over a particular area or facility providing around the clock surveillance with no personnel onboard. New UAV platforms and systems are becoming available for commercial use. High altitude platforms are being tested for use in communications, remote sensing, agriculture, forestry and disaster management. New payloads are being built and demonstrated onboard the UAVs in support of these applications. Smaller, lighter, lower power consumption imaging systems are currently being tested over coffee fields to determine yield and over fires to detect fire fronts and hotspots. Communication systems that relay video, meteorological and chemical data via satellite to users on the ground in real-time have also been demonstrated. Interest in this technology for infrastructure characterization and mapping has increased dramatically in the past year. Many of the UAV technological developments required for resource and disaster monitoring are being used for the infrastructure and facility mapping activity. This paper documents the unique contributions from NASA;s Environmental Research Aircraft and Sensor Technology (ERAST) program to these applications. ERAST is a UAV technology development effort by a consortium of private aeronautical companies and NASA. Details of demonstrations of UAV capabilities currently underway are also presented.

Wegener, Steve↗
NASA NTRS1974

The first earth resources technology satellite /ERTS 1/

The present work describes the ERTS 1 spacecraft and data collection system and reviews the operation of the system since the satellite was launched in July, 1972. Perhaps the most significant result of the ERTS 1 mission is the realization that features related to land resources or to environmental processes can be mapped synoptically for very large areas on scales up to 1:250,000 without substantial loss of definition. Examples of color composite images obtained by ERTS 1 are shown.

Nordberg, W.↗
NASA NTRS1975

Seasonal streamflow estimation employing satellite snowcover observations

Low resolution meteorological satellite and high resolution earth resources satellite data have been used to map snow covered area over the upper Indus River and the Wind River Mountains of Wyoming, respectively. For the Indus River early spring snow covered area was extracted and related to April through June stream flow from 1967-1971 using a regression equation. Prediction of the April-June 1972 stream flow from the satellite data was within three percent of the actual total. Composited results from two years of data over seven Wind River Mountain watersheds indicated that LANDSAT-1 snow cover observations, separated on the basis of watershed elevation, could also be related to runoff in significant regression equations.

Rango, A.↗
NASA NTRS1977

The utility of short wavelength (1mm) remote sensing techniques for the monitoring and assessment of hydrologic parameters

Remote sensing programs that respond to the requirements of the water resources management and hydrologic communities are reviewed. The major areas where the needs of water resources management are being met involve the mapping and monitoring of snowcovered areas, hydrologic landuse, and surface water area. In the case of snowcovered area mapping the transfer of technology process is now being accomplished in the Western United States in a cooperative effort involving 6 federal agencies and 3 state agencies along with NASA. A new collaborative effort of the U.S. Army Corps of Engineers and NASA involves the mapping of landuse by Landsat and its use in hydrologic engineering watershed models employed in flood control/waterworks planning, design, and management. Improved systems planned for implementation in the 1978-1981 time frame can be expected to result in increased utilization of visible and near infrared remote sensing observations.

Rango, A.↗
NASA NTRS1978

Remote sensing of strippable coal reserves and mine inventory in part of the Warrior Coal Field in Alabama

Methods by which estimates of the remaining reserves of strippable coal in Alabama could be made were developed. Information acquired from NASA's Earth Resources Office was used to analyze and map existing surface mines in a four-quadrangle area in west central Alabama. Using this information and traditional methods for mapping coal reserves, an estimate of remaining strippable reserves was derived. Techniques for the computer analysis of remotely sensed data and other types of available coal data were developed to produce an estimate of strippable coal reserves for a second four-quadrangle area. Both areas lie in the Warrior coal field, the most prolific and active of Alabama's coal fields. They were chosen because of the amount and type of coal mining in the area, their location relative to urban areas, and the amount and availability of base data necessary for this type of study.

Joiner, T. J.↗
NASA NTRS1981

Use of MAGSAT anomaly data for crustal structure and mineral resources in the US midcontinent

While the preliminary magnetic anomaly map for the centra midcontinent is only in the hand-drawn stage, it agrees in broad aspects with the preliminary global MAGSAT map provided by NASA. Because of data evaluation and finer scale averaging, there are more detailed features which hold promise for eventual geological/crustal interpretation. Some current analysis is directed at examining whether a map data feature such as an elongated anomaly or trend, which seems parallel to satellite data tracks, is likely of crustal origin or is an artifact of the data set.

Carmichael, R. S.↗