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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Michigan resource inventories: Characteristics and costs of selected projects using high altitude color infrared imagery. Remote Sensing Project

The procedures and costs associated with mapping land cover/use and forest resources from high altitude color infrared (CIR) imagery are documented through an evaluation of several inventory efforts. CIR photos (1:36,000) were used to classify the forests of Mason County, Michigan into six species groups, three stocking levels, and three maturity classes at a cost of $4.58/sq. km. The forest data allow the pinpointing of marketable concentrations of selected timber types, and facilitate the establishment of new forest management cooperatives. Land cover/use maps and area tabulations were prepared from small scale CIR photography at a cost of $4.28/sq. km. and $3.03/sq. km. to support regional planning programs of two Michigan agencies. procedures were also developed to facilitate analysis of this data with other natural resource information. Eleven thematic maps were generated from Windsor Township, Michigan at a cost of $1,500 by integrating grid-geocoded land cover/use, soils, topographic, and well log data using an analytical computer program.

Enslin, W. R.↗
NASA NTRS1976

Optical vs. electronic enhancement of remote sensing imagery

Basic aspects of remote sensing are considered and a description is provided of the methods which are employed in connection with the optical or electronic enhancement of remote sensing imagery. The advantages and limitations of various image enhancement methods and techniques are evaluated. It is pointed out that optical enhancement methods and techniques are currently superior to electronic ones with respect to spatial resolution and equipment cost considerations. Advantages of electronic procedures, on the other hand, are related to a greater flexibility regarding the presentation of the information as an aid for the interpretation by the image analyst.

Colwell, R. N.↗
NASA NTRS2023

Automated Global-Scale Detection and Characterization of Anthropogenic Activity using Multi-Source Satellite-Based Remote Sensing Imagery

Satellite-based remote sensing imagery is an effective means for detecting objects and structures in support of many applications. However, detecting the spatial and temporal bounds of a specific activity in satellite imagery is inherently more complex and research in this area is nascent. One reason for this is that describing an activity implies defining both spatial and temporal bounds and while activity is inherently continuous in nature, the geospatial (imagery) time series for any particular swath of ground provided by satellite imagery is relatively sparse and discrete in comparison. The IARPA Space-Based Machine Automated Recognition Technique (SMART)1 program is the first large-scale research program to target advancing the state of the art for automatically detecting, characterizing, and monitoring large-scale anthropogenic activity in global, multispectral satellite imagery. The program has two primary research objectives: 1) the “harmonization” of multiple imagery sources and 2) automated reasoning at scale to detect, characterize, and monitor activities of interest. This paper provides details on the goals, dataset, metrics, and lessons learned of the IARPA SMART program. By releasing the annotated dataset, the program aims to foster additional research in this area by the community at large.

Hirsh R Goldberg↗
NASA NTRS2018

Image Station Matching, Preprocessing, Spatial Registration and Change Detection with Multi-Temporal Remotely-Sensed Imagery

A method for collecting and processing remotely sensed imagery in order to achieve precise spatial co-registration (e.g., matched alignment) between multi-temporal image sets is presented. Such precise alignment or spatial co-registration of imagery can be used for change detection, image fusion, and temporal analysis/modeling. Further, images collected in this manner may be further processed in such a way that image frames or line arrays from corresponding photo stations are matched, co-aligned and if desired merged into a single image and/or subjected to the same processing sequence. A second methodology for automated detection of moving objects within a scene using a time series of remotely sensed imagery is also presented. Specialized image collection and preprocessing procedures are utilized to obtain precise spatial co-registration (image registration) between multitemporal image frame sets. In addition, specialized change detection techniques are employed in order to automate the detection of moving objects.

Coulter, Lloyd Lawrence Arthur↗
NASA NTRS1973

Geological evaluation of remote sensing imagery of the Mesabi Range, Minnesota.

Remote sensing imagery of Precambrian sedimentary, metasedimentary, and intrusive rocks of the Mesabi Range, Minnesota area was analyzed to determine how much geologic information was inherent in each type of imagery. High altitude panchromatic photography, radar, ultraviolet, and day and night thermal infrared imagery were examined. Geologic sketch maps were produced for each type of imagery. Radar appears to be the best imagery for mapping rock units and for locating regional faults. Few rock units could be found on the infrared imagery or on the panchromatic photography. Several previously unmapped faults were located, and the surface traces of some faults were extended.

Walker, A. S.↗
NASA NTRS2003

Fractals and Spatial Methods for Mining Remote Sensing Imagery

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

Lam, Nina↗
NASA NTRS1979

Map-guided interpretation of remotely-sensed imagery

A map-guided approach to interpretation of remotely sensed imagery is described, with emphasis on applications involving continuous monitoring of predetermined ground sites. Geometric correspondence between a sensed image and a symbolic reference map is established in an initial stage of processing by adjusting parameters of a sensor model so that image features predicted from the map optimally match corresponding features extracted from the sensed image. Information in the map is then used to constrain where to look in an image and what to look for. With such constraints, previously intractable remote sensing tasks can become feasible, even easy, to automate. Four illustrative examples are given, involving the monitoring of reservoirs, roads, railroad yards, and harbors.

Tenenbaum, J. M.↗
NASA NTRS1977

Integration of socioeconomic data and remotely sensed imagery for land use applications

The Image Based Information System (IBIS) uses techniques of digital image processing to interface geocoded data sets, information management systems, thematic maps, and remotely sensed imagery. For two cases IBIS has been used to integrate remotely sensed imagery and socioeconomic data. In the first case thematically classified Landsat imagery covering Orange County, California is combined with census tracts and municipalities. In the second case, thematically classified Landsat imagery over Los Angeles, California is combined with census tracts.

Bryant, N. A.↗
NASA NTRSDate not supplied

Neural Network Atmospheric Correction of Remote Sensing Imagery Over Water Using a Synthetic Dataset

Remote sensing atmospheric correction methods have primarily focused on imagery over land. However, accurate correction over water is important for monitoring and research of aquatic environments. More research in this area is ongoing, though one of the biggest challenges is enough quality data to develop and validate correction methods. This is especially true for neural network (NN) -based models which have shown promise in this area given enough quality data. To address this deficiency of data, we are leveraging a synthetic dataset produced by a model called SWIPE that uses radiative transfer modeling to simulate the atmospheric effects on water-leaving (WL) reflectance to estimate top-of-atmosphere (TOA) reflectance. This allows us to produce almost unlimited pairs of WL reflectance and corresponding TOA reflectance for model training across a variety of atmospheric conditions. We use two approaches for our atmospheric correction model. One uses a conditional variational autoencoder (VAE) to estimate a single WL reflectance value from a single TOA reflectance value. The second is based on a UNET architecture and estimates an array of WL reflectance values from an array of TOA reflectance values. The goal of the second method is to capture atmospheric effects that occur spatially between values within the array as compared to the first method.

deep learning↗
NASA NTRS2007

Operational Use of Remote Sensing within USDA

A viewgraph presentation of remote sensing imagery within the USDA is shown. USDA Aerial Photography, Digital Sensors, Hurricane imagery, Remote Sensing Sources, Satellites used by Foreign Agricultural Service, Landsat Acquisitions, and Aerial Acquisitions are also shown.

Bethel, Glenn R.↗
NASA NTRS1972

Considerations and techniques for incorporating remotely sensed imagery into the land resource management process.

Development of a scheme for utilizing remote sensing technology in an operational program for regional land use planning and land resource management program applications. The scheme utilizes remote sensing imagery as one of several potential inputs to derive desired and necessary data, and considers several alternative approaches to the expansion and/or reduction and analysis of data, using automated data handling techniques. Within this scheme is a five-stage program development which includes: (1) preliminary coordination, (2) interpretation and encoding, (3) creation of data base files, (4) data analysis and generation of desired products, and (5) applications.

Brooner, W. G.↗
NASA NTRS2011

Visualizing Airborne and Satellite Imagery

Remote sensing is a process able to provide information about Earth to better understand Earth's processes and assist in monitoring Earth's resources. The Cloud Absorption Radiometer (CAR) is one remote sensing instrument dedicated to the cause of collecting data on anthropogenic influences on Earth as well as assisting scientists in understanding land-surface and atmospheric interactions. Landsat is a satellite program dedicated to collecting repetitive coverage of the continental Earth surfaces in seven regions of the electromagnetic spectrum. Combining these two aircraft and satellite remote sensing instruments will provide a detailed and comprehensive data collection able to provide influential information and improve predictions of changes in the future. This project acquired, interpreted, and created composite images from satellite data acquired from Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper plus (ETM+). Landsat images were processed for areas covered by CAR during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCT AS), Cloud and Land Surface Interaction Campaign (CLASIC), Intercontinental Chemical Transport Experiment-Phase B (INTEXB), and Southern African Regional Science Initiative (SAFARI) 2000 missions. The acquisition of Landsat data will provide supplemental information to assist in visualizing and interpreting airborne and satellite imagery.

Bierwirth, Victoria A.↗
NASA NTRS1997

Landscape characterization of peridomestic risk for Lyme disease using satellite imagery

Remotely sensed characterizations of landscape composition were evaluated for Lyme disease exposure risk on 337 residential properties in two communities of suburban Westchester County, New York. Properties were categorized as no, low, or high risk based on seasonally adjusted densities of Ixodes scapularis nymphs, determined by drag sampling during June and July 1990. Spectral indices based on Landsat Thematic Mapper data provided relative measures of vegetation structure and moisture (wetness), as well as vegetation abundance (greenness). A geographic information system (GIS) was used to spatially quantify and relate the remotely sensed landscape variables to risk category. A comparison of the two communities showed that Chappaqua, which had more high-risk properties (P < 0.001), was significantly greener and wetter than Armonk (P < 0.001). Furthermore, within Chappaqua, high-risk properties were significantly greener and wetter than lower-risk properties in this community (P < 0.01). The high-risk properties appeared to contain a greater proportion of broadleaf trees, while lower-risk properties were interpreted as having a greater proportion of nonvegetative cover and/or open lawn. The ability to distinguish these fine scale differences among communities and individual properties illustrates the efficiency of a remote sensing/GIS-based approach for identifying peridomestic risk of Lyme disease over large geographic areas.

Topography, Medical↗
NASA NTRS1997

Application of High Resolution Topography and Remote Sensing: Imagery to the Kinematics of Fold-and-Thrust Belts

This report summarizes one year of funding for NASA contract NAGW-3691, Application of High Resolution Topography and Remote Sensing: Imagery to the Kinematics of Fold-and-Thrust Belts. I never received year three from NASA. The funds were to support on going tectonic and topographic studies along the front of the central Transverse Ranges and expand the topographic studies to the north. Below are results from the first two years of actual funds that I received from NASA (see attached Federal Cash Transaction Reports). The main focus of this contract was to define and understand the major tectonic processes affecting the formation and evolution of the topography in convergent tectonic settings. The results will be used to test ongoing space-based geodetic measurements and will be compared with present-day seismicity in the central Transverse Ranges and adjacent basins. Two major factors that controls topography in active regions are (1) tectonic uplift due to fault-normal compression and (2) subsequent erosion. The central Transverse and Temblor Ranges are excellent regions for these focused topographic studies. The tectonic processes leading to the mountain building are relatively straightforward and thus are easy to model. Available evidence suggests that the topography in this region is relatively young, - 3.5 Ma or less. In addition,, erosional processes may be relatively easier to model compared to larger and more ancient mountain belts. For example, in larger mountain belts, topographic relief may cause significant orographic effects and high elevation may result in part of the topography located above snowline. Both factors complicate interpretation of erosional processes that may be controlled by elevation. Mountain ranges that are significantly older may have experienced a much wider variety of erosional or climatic conditions over their lifetime. While erosion rates have certainly not been consistent in the Transverse or Temblor ranges over its 3.5 Ma lifetime, we are sure that the region was spared the Pleistocene glaciation that affected parts of the Sierra Nevada Range.

Rubin, Charles↗
NASA NTRS1977

Preliminary analysis of remote infrared imagery of shuttle during entry: An aerothermodynamic flight experiment

The preliminary feasibility of remote high-resolution infrared imagery of the space shuttle orbiter lower surface during entry to obtain accurate measurements of aerodynamic heat transfer to that vehicle was examined. In general, it was determined that such such images can be taken from an existing aircraft/telescope system (the C-141 AIRO) with a minimum modification or addition of systems using available technology. These images will have a spatial resolution of about 0.3 m and a temperature resolution much better than 2.5 percent. The data from these images will be at conditions and at a scale not reproducible in ground based facilities and should aid in the reduction of the prudent factors of safety required to account for phenomenological uncertainties on the thermal protection system design. Principal phenomena to be observed include laminar heating, boundary-layer transition, turbulent heating, surface catalysis, and flow separation and reattachment.

Swenson, B. L.↗