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At least 55 records · Page 3

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NASA NTRS1972

Utilization of ERTS data to detect plant diseases and nutrient deficiencies, soil types and moisture levels

The author has identified the following significant results. A significant finding is the identification and delineation of a large soil association in Obion County, West Tennessee. These data are now being processed through the scanner and computer and will be included in the next report along with pictures of printout and imagery. Channel 7 appears to provide the most useful imagery related to soil differences. Soil types have been identified through the use of aircraft imagery. However, a soil association map appears to be the best that space imagery will provide. The exception to this will be large areas of a uniform soil type as occurs in the great plains.

Parks, W. L.↗

NASA NTRS1973

Effective use of ERTS multisensor data in the Great Plains

The author has identified the following significant results. It appears that identification of corn and soybeans as separate classes may not be feasible for the part of the growing season around August 15. It is hoped that at other points in the growing season separation of corn from soybeans will be possible. Visual examination of September 5 imagery indicates that later in the growing season, it is possible. The resolution of the 1:300,000 scale enlargement remained sharp enough to distinguish features important for making soil association maps. The land use pattern (range vs cultivated) was sharp as were the stream bottoms, stream valley sides, and stock ponds. The resolution of the 1:1,000,000 scale enlargement was less sharp on detail but it appears that some features could be quantitatively analyzed. Among these are the hydrologic features present such as stock ponds and the streams. It would appear that the total area of stock pond water on a frame could be measured, and, after ground truth established their average depth, the volume of water stored could be calculated and be monitored.

Myers, V. I.↗

NASA NTRS1973

A study of the utilization of ERTS-1 data from the Wabash River Basin

The author has identified the following significant results. In soil association mapping, computerized analysis of ERTS-1 MSS data has yielded images which will prove useful in the ongoing Cooperative Soil Survey program, involving the Soil Conservation Service of USDA and other state and local agencies. In the present mode of operation, a soil survey for a county may take up to 5 years to be completed. Results indicate that a great deal of soils information can be extracted from ERTS-1 data by computer analysis. This information is expected to be very valuable in the premapping conference phase of a soil survey, resulting in more efficient field operations during the actual mapping. In the earth surface features mapping effort it was found that temporal data improved the classification accuracy of forest classification in Tippecanoe County, Indiana. In water resources study a severe scanner look angle effect was observed in the aircraft scanner data of a test lake which was not present in ERTS-1 data of the same site. This effect was greatly accentuated by surface roughness caused by strong winds. Quantitative evaluation of urban features classification in ERTS-1 data was obtained. An 87.1% test accuracy was obtained for eight categories in Marion County, Indiana.

Landgrebe, D. A.↗

NASA NTRS1974

An evaluation of machine processing techniques of ERTS-1 data for user applications

A broad study is described to evaluate a set of machine analysis and processing techniques applied to ERTS-1 data. Based on the analysis results in urban land use analysis and soil association mapping together with previously reported results in general earth surface feature identification and crop species classification, a profile of general applicability of this procedure is beginning to emerge. Put in the hands of a user who knows well the information needed from the data and also is familiar with the region to be analyzed it appears that significantly useful information can be generated by these methods. When supported by preprocessing techniques such as the geometric correction and temporal registration capabilities, final products readily useable by user agencies appear possible. In parallel with application, through further research, there is much potential for further development of these techniques both with regard to providing higher performance and in new situations not yet studied.

Landgrebe, D.↗

NASA NTRS1974

A study of the utilization of ERTS-1 data from the Wabash River Basin

The author has identified the following significant results. The identification and area estimation of crops experiment tested the usefulness of ERTS data for crop survey and produced results indicating that crop statistics could be obtained from ERTS imagery. Soil association mapping results showed that strong relationships exist between ERTS data derived maps and conventional soil maps. Urban land use analysis experiment results indicate potential for accurate gross land use mapping. Water resources mapping demonstrated the feasibility of mapping water bodies using ERTS imagery.

Landgrebe, D. A.↗

NASA NTRS1985

Preliminary Evaluation of TM for Soils Information

The capability of the LANDSAT TM for providing information for soil association maps and for detecting soil properties (variability within vegetated fields) was assessed using TM imagery of fields in Mississippi County, Arkansas that were planted with rice, cotton, and soybeans. Results indicate that the TM bands are providing information that is related to the soil properties within the field. Over large areas, these bands also appear to provide information that is related to the soil properties that are important to plant condition. While these results are only an indication of the information that TM can provide, they do indicate the TM data--especially, the mid-TR and thermal bands--show the capability for separating vegetated soil landscapes on a broad basis. The analysis at the field level with a growing crop also indicates that TM, with its additional and narrower bands and improved spatial and radiometric resolution is influenced by within field variability due to soils that has to be accounted for in the analysis of TM data.

Thompson, D. R.↗

NASA NTRS1983

Evaluation of Landsat Thematic Mapper for vegetated alluvium soils information

Landsat Thematic Mapper data acquired over Mississippi County, Arkansas, on August 22, 1982, were evaluated whether TM provides information that could be used for soil association maps and if soil properties (variability within vegetated fields) can be detected with the new bands on TM. It was found that TM data - especially the mid-IR and thermal bands - show the capability for separating vegetated soil landscapes on a broad basis. Analysis at the field level with a crop growing indicates that TM, with its additional and narrower bands and improved spatial resolution is influenced by within-field variability due to soils.

Thompson, D. R.↗

NASA NTRS1991

S-R compatibility effects with orthogonal stimulus and response dimensions

An experiment was conducted to assess the relative influence of several factors on performance with orthogonal stimulus-response arrays. Subjects responded to the onset of one of three aligned light circles with a press of one of three aligned response keys. The response array was aligned parallel, angled, or orthogonal to the stimulus array. The results indicated that performance with orthogonal arrays is worse than with parallel or angled S-R arrays. For the orthogonal arrangements, the results also indicate that each hand prefers a mapping directly opposite to the other hand, and that this mapping reverses when the orientation of the stimulus and response arrays are transposed. In addition, the results also revealed that the relative costs of orthogonal S-R arrangements are somewhat attenuated when the assigned mapping associates (i.e., colocates) a given display with its closest control.

Andre, Anthony D.↗

NASA NTRS1992

Quantitative modeling of soil genesis processes

For fine spatial scale simulation, a model is being developed to predict changes in properties over short-, meso-, and long-term time scales within horizons of a given soil profile. Processes that control these changes can be grouped into five major process clusters: (1) abiotic chemical reactions; (2) activities of organisms; (3) energy balance and water phase transitions; (4) hydrologic flows; and (5) particle redistribution. Landscape modeling of soil development is possible using digitized soil maps associated with quantitative soil attribute data in a geographic information system (GIS) framework to which simulation models are applied.

Levine, E. R.↗

NASA NTRS2005

Vision and "Hand-Eye" Coordination for the Fujitsu HOAP-2 Humanoid Robot

Software was developed for a Fujitsu HOAP-2 humanoid robot to demonstrate that such "human form" robots can be used to perform useful tasks in an unknown environment; specifically, that they can operate with or in the place of humans to carry out construction operations necessary for space exploration, such as building or maintaining planetary surface habitats for humans. This paper describes the autonomous vision and hand-eye coordination software that enables the HOAP-2 to locate and manipulate objects. Simple vision and pattern detection algorithms including color filtering, noise filtering, image segmentation, orientation filters, and a feedback controlled tracking system enable the robot to locate marked building materials in the workspace. Experimentally determined spatial mappings associate locations in the visual field with the arm joint angles and trajectories necessary to reach these locations, allowing the robot to reach for and manipulate the building materials. These capabilities, when combined with locomotion capabilities, enable the robot to operate autonomously in an unknown workspace.

Moore, Jeffrey D.↗

NASA NTRS2015

Expression of Genes Involved in Drosophila Wing Morphogenesis and Vein Patterning Are Altered by Spaceflight

Imaginal wing discs of Drosophila melanogaster (fruit fly) defined during embryogenesis ultimately result in mature wings of stereotyped (specific) venation patterning. Major regulators of wing disc development are the epidermal growth factor receptor (EGF), Notch, Hedgehog (Hh), Wingless (Wg), and Dpp signaling pathways. Highly stereotyped vascular patterning is also characteristic of tissues in other organisms flown in space such as the mouse retina and leaves of Arabidopsis thaliana. Genetic and other adaptations of vascular patterning to space environmental factors have not yet been systematically quantified, despite widespread recognition of their critical importance for terrestrial and microgravity applications. Here we report changes in gene expression with space flight related to Drosophila wing morphogenesis and vein patterning. In addition, genetically modified phenotypes of increasingly abnormal ectopic wing venation in the Drosophila wing1 were analyzed by NASA's VESsel GENeration Analysis (VESGEN) software2. Our goal is to further develop insightful vascular mappings associated with bioinformatic dimensions of genetic or other molecular phenotypes for correlation with genetic and other molecular profiling relevant to NASA's GeneLab and other Space Biology exploration initiatives.

venation↗

NASA NTRS2016

On the VHF Source Retrieval Errors Associated with Lightning Mapping Arrays (LMAs)

This presentation examines in detail the standard retrieval method: that of retrieving the (x, y, z, t) parameters of a lightning VHF point source from multiple ground-based Lightning Mapping Array (LMA) time-of-arrival (TOA) observations. The solution is found by minimizing a chi-squared function via the Levenberg-Marquardt algorithm. The associated forward problem is examined to illustrate the importance of signal-to-noise ratio (SNR). Monte Carlo simulated retrievals are used to assess the benefits of changing various LMA network properties. A generalized retrieval method is also introduced that, in addition to TOA data, uses LMA electric field amplitude measurements to retrieve a transient VHF dipole moment source.

inversion↗

NASA NTRS1983

Landsat mapping of rocks associated with copper mineralization, northern Bahia State, Brazil

This project has applied Landsat digital data to a study of the geology of a mineralized zone in northern Bahia State, Brazil. The study accomplished two tasks: (1) production of a 1:100,000 geologic map of approximately 3300 sq km and (2) development of a two tiered geobotanical index that exploits increased vegetation density and decreased soil brightness on the mafic rock units.

Stone, T. A.↗

DOE OSTI2026

Vegetation classification map and covariates associated with NEON AOP survey, East River, CO 2018

This package includes geospatial data layers developed to investigate how environmental gradients—specifically topography and near-surface soil properties—drive the spatial arrangement of dominant plant communities in mountainous watersheds. The geospatial products, which support the analysis of these ecological relationships, are derived from airborne hyperspectral and LiDAR datasets acquired by the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP), in conjunction with an extensive ground field campaign conducted in summer 2018. This work is part of the DOE Watershed Function Science Focus Area (SFA) and features geospatial datasets developed based on observations and ground data collected at East River, Colorado, in collaboration with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey in June 2018. Classification Map: - Classification Map (PNG, GeoTIFF): Derived from hyperspectral and LiDAR airborne data using a machine learning approach. - Class Code Mapper (CSV): Associates pixel values with corresponding vegetation/non-vegetation classes. - Classification Reference Data (CSV): Reference data used in the machine learning procedure. LiDAR-Derived Products: - Topographical Metrics (GeoTIFFs): Elevation, slope, curvature, TWI, TPI, solar insolation, and canopy height model (CHM), smoothed with a 5x5 pixel window. Vegetation Indices: - GeoTIFFs of NDVI, NDNI, NDWI: Vegetation indices derived from hyperspectral data. Urban Masks: - Urban Mask (GeoTIFF): Applied to the mapping to convert bare soil classes to urban classes. Software Compatibility: GeoTIFFs: Can be visualized with GIS software or libraries that support GeoTIFF images. CSV Files: Can be opened with any software that handles comma-separated values. The FLMD file provides details and links to the source datasets used to derive the products. The manuscript (in the Method session) provides details on how each product was derived. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Update on 2026-03-25: Since the original dataset publication date of 02/28/2020, this package has a new classification map derived by an improved methodology. This update also includes additional ground data that improved the representation of some of the communities. See the methods for further details on what has changed between versions.

2018 NEON and 2025 CHESS Campaigns↗

DOE OSTI2022

The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

1. LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. 2. In this study, we show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open-source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large-scale fire experiment in the Brazilian Amazon region. 3. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape-level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top-of-the-canopy information (e.g. canopy height models based on LiDAR data). 4. By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad utility to the ecological research community.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Road Lidar Dataset for the TxDOT Austin District

This is a road lidar data collection for developing road elevation models and road inundation mapping methodologies, a joint work between ORNL and The University of Texas at Austin. This dataset is generated as part of the flood transportation infrastructure, partly funded by the NOAA CIROH project. ORNL is a project partner for high-performance computing-empowered flood inundation mapping methodology R&D. The dataset is computed using a GPU-accelerated lidar data processing workflow developed at ORNL. The lidar data source is from TxGIO, the state lidar data collection site. The output dataset is in two formats: laz and copc. It is organized by TxDOT's maintenance sections, covering the Austin District. Data size: 3.86 billion road lidar points, 1.67% of the entire lidar data input Projection: EPSG:32614 (WGS84/UTM zone 14N) Website: https://web.corral.tacc.utexas.edu/nfiedata/road3d/austin_district/AustinMaintenanceSections_H_epsg6343_V_epsg5703/ LICENSE FOR USE -- MAPS AND DATA DISCLAIMER This resource is shared under the Creative Commons Attribution CC BY, http://creativecommons.org/licenses/by/4.0/ MAPS AND DATA DISCLAIMER The Oak Ridge National Laboratory (ORNL) shall not be held liable for improper or incorrect use of the data described or information contained on this map or associated series of maps. The data and related map graphics are not legal, land survey or engineering documents and are not intended to be used as such. ORNL gives no warranty, express or implied, as to the accuracy, reliability, utility or completeness of this information. The user of these maps and data assumes all responsibility and risk for the use of the maps and data. ORNL disclaims all warranties, representations or endorsements either express or implied, with regard to the information contained in this map product, including, but not limited to, all implied warranties of merchantability, fitness for a particular purpose or non-infringement. This preliminary map product is for research and review purposes only. It is not intended to be used for emergency management operational or life safety decisions at the local or regional governmental level or by the general public. Users requiring information regarding hazardous conditions or meteorological conditions for specific geographic areas should consult directly with their city or county emergency management office.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Genome-wide association analysis of the strength of the MAMP-elicited defense response and resistance to target leaf spot in sorghum

Abstract Plants have the capacity to respond to conserved molecular features known as microbe-associated molecular patterns (MAMPs). The goal of this work was to assess variation in the MAMP response in sorghum, to map loci associated with this variation, and to investigate possible connections with variation in quantitative disease resistance. Using an assay that measures the production of reactive oxygen species, we assessed variation in the MAMP response in a sorghum association mapping population known as the sorghum conversion population (SCP). We identified consistent variation for the response to chitin and flg22—an epitope of flagellin. We identified two SNP loci associated with variation in the flg22 response and one with the chitin response. We also assessed resistance to Target Leaf Spot (TLS) disease caused by the necrotrophic fungus Bipolaris cookei in the SCP. We identified one strong association on chromosome 5 near a previously characterized disease resistance gene. A moderately significant correlation was observed between stronger flg22 response and lower TLS resistance. Possible reasons for this are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1973

The identification of selected vegetation types in Arizona through the photointerpretation of intermediate scale aerial photography

The author has identified the following significant results. Nine photography interpretation tests were performed with a total of 19 different interpreters. Three tests were conducted with black and white intermediate scale photography and six tests with color infrared intermediate scale photography. The black and white test results show that the interpretation of vegetation mapped at the association level of classification is reliable for all the classes used at 61%. The color infrared tests indicate that the association level of mapping is unsatisfactory for vegetation interpretation of classes 1 and 6. Students' t-test indicated that intermediate scale black and white photography is significantly better than this particular color infrared photography for the interpretation of southeastern Arizona vegetation mapped at the association level.

Ross, G. F.↗