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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Comparison of Landsat MSS and merged MSS/RBV data for analysis of natural vegetation

Improved resolution could make satellite remote sensing data more useful for surveys of natural vegetation. Although improved satellite/sensor systems appear to be several years away, one potential interim solution to the problem of achieving greater resolution without sacrificing spectral sensitivity is through the merging of Landsat RBV and MSS data. This paper describes the results of a study performed to obtain a preliminary evaluation of the usefulness of two types of products that can be made by merging Landsat RBV and MSS data. The products generated were a false color composite image and a computer recognition map. Of these two products, the false color composite image appears to be the most useful.

Roller, N. E. G.↗
NASA NTRS1977

Multi-seasonal data analysis and some extensions for environmental monitoring

Multispectral data analysis was incorporated with multiseasonal data analysis based on a spectral radiance data-set. Concepts include comparing data types, exploring relationships between periodicity of LANDSAT and the seasonal sense of the Orientals, and derivation of a method to register the acquired data. Examples include a quality investigation of a paddy field by seasonal LANDSAT data, a progress check of the field in harvest season, and a detailed survey of the vegetational environment by summer and winter LANDSAT data.

Tanaka, S.↗
NASA NTRS2021

NASA's Surface Biology and Geology Designated Observable: A Perspective on Surface Imaging Algorithms

The 2017–2027 National Academies’ Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a “Designated Targeted Observable” (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380–2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3–5 μm; TIR: 8–12 μm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algo-rithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. This effort synthesizes the findings of more than 130 scientists.

Aquatic↗
NASA NTRS1973

Remote sensing techniques for support of coastal zone resource management.

Description of remote sensing studies carried out for the purpose of developing and/or demonstrating techniques which can be employed for land use inventory, marsh vegetation classification, and water characteristics surveys. Attention is given to results obtained with (1) photo interpretation techniques and procedures for the development of land use information from high-altitude aircraft and satellite imagery, (2) computer based pattern recognition techniques utilizing multispectral scanner data for marsh vegetation classification, and (3) infrared and microwave techniques for the monitoring and surveying of coastal water temperature and salinity characteristics.

Piland, R. O.↗
NASA NTRS1977

Investigation of environmental change pattern in Japan. Investigation of the ecological environment index from observation of the regional vegetation cover and their growing condition

The author has identified the following significant results. Practical use of recognition results of LANDSAT data as the base map of the field survey or the retouching work of vegetation and land use has the effective benefit to cut down the cost, labor, and time lower than 10% of a conventional method. Correct and detailed vegetation maps were prepared using combined interpretation of repetition of data of different seasons at warm and temperate forested areas.

Maruyasu, T.↗
NASA NTRS1976

Effects of environmental changes on marsh vegetation with special reference to salinity

A literature survey primarily concerned with brackish and salt marshes located along the eastern coast of North America and the Gulf Coast was presented. The review concentrated upon the vegetation of the marshes, particularly in regard to distribution, composition, succession, and productivity. Special efforts were made to include major works concerned with the Louisiana and Mississipi coastal marshes. It appears that spring to early summer (weeks 18-34 of the year; April - mid-July) is the best period of time to categorize the communities. It is during this time of the year that the communities appear most stable in regard to species composition. This allows a strong correlation to be drawn between the salinity of the region and the dominant species of the community. As such, this would seem to be best period in which to sample the marsh via air or land for differences in vegetation and salinity.

Smalley, A. E.↗
NASA NTRS1974

Reflectance of vegetation, soil, and water

The author has identified the following significant results. The majority of the rangelands of Hidalgo County, Texas are used in cow-calf operations. Continuous year-long grazing is practiced on about 60% of the acreage and some type of deferred system on the rest. Mechanical brush control is used more than chemical control. Ground surveys gave representative estimates for 15 vegetable crops produced in Hidalgo County. ERTS-1 data were used to estimate the acreage of citrus in the county. Combined Kubleka Munk and regression models, that included a term for shadow areas, gave a higher correlation of composite canopy reflectance with ground truth than either model alone.

Wiegand, C. L.↗
NASA NTRS2020

Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data

Crop phenology represents an integrative indicator of climate change and plays a vital role in terrestrial carbon dynamics and sustainable agricultural development. However, spatiotemporal variations of crop phenology remain unclear at large scales. This knowledge gap has hindered our ability to realistically quantify the biogeochemical dynamics in agroecosystems, predict future climate, and make informed decisions for climate change mitigation and adaptation. In this study, we improved an EVI-curve-based approach and used it to detect spatiotemporal patterns in cropping intensity and five major phenological stages over North America during 2000–2016 using vegetation index in combination with agricultural survey data and other ancillary maps. Our predicted crop phenological stages showed strong linear relationships with the survey-based datasets, with R(exp 2), RMSEs, and MAEs in the ranges of 0.35 –0.99, three to ten days, and two to eight days, respectively. During the study period, the planting dates were advanced by 0.60 days/year (p < 0.01), and harvesting dates were delayed by 0.78 days/year (p < 0.01) over North America. A minimum temperature increase by 1 °C caused a 4.26-day planting advance (r = −0.50, p < 0. 01) or a 0.66-day harvest delay (r = 0.10, p < 0.01). While, a higher maximum temperature resulted in a planting advance by 4.48 days/°C (r = −0.62, p < 0.01) or a harvest advance by 2.22 days/°C (r = −0.40, p < 0.01). Our analysis illustrated evident spatiotemporal variations in crop phenology in response to climate change and management practices. The derived crop phenological datasets and cropping intensity maps can be used in regional climate assessments and in developing adaptation strategies.

North America↗
NASA NTRS1975

Hydrogeological investigations in the Pampa of Argentina

In large areas of the Argentinian Pampa the salinization of ground water creates water supply difficulties. Investigations of satellite imagery (Landsat-1 and Skylab) which were based on an extensive ground survey revealed that differences in the vegetation cover are closely related to depth and salinity of ground water. Narrow elongated depressions called bajos are often the only indication of fresh ground water. They can be easily detected on the imagery. Due to their high resolution, Skylab photos even allow a quantitative estimation of fresh ground water situated below the bajos. In general however Landsat-1 imagery sufficed for evaluation. In the area of the Rio Tercero a fossil drainage pattern was discovered and in Corrientes province, soil types could be discriminated and compared to the Soil Map of the World.

Kruck, W.↗
NASA NTRS2000

BOREAS RSS-19 1994 Seasonal Understory Reflectance Data

The BOREAS RSS-19 team collected airborne remotely sensed images and ground reflectance data for characterizing the radiometric properties of the boreal forest landscape. One objective of BOREAS is to further the understanding of the spectral bidirectional reflectance of typical boreal ecosystem stands in the visible/near-infrared regime. An essential input for any canopy BRDF model is an accurate estimate of the average understory reflectance, both for sunlit and shaded conditions. These variables can be expected to vary seasonally because of species-dependent differences in the phenological cycle of foliar display. In response to these requirements, the average understory reflectance for the flux tower sites of both the NSA (Thompson, Manitoba) and the SSA (Candle Lake, Saskatchewan) was observed throughout the year during five field campaigns. This was done by measuring the nadir reflectance (400 to 850 nm) of sunlit and shaded understory (vegetation and snow cover) along a surveyed LAI transect line (Chen, RSS-07) at each site near solar noon and documenting an average site reflectance. Comparisons between sites reveal differences in the green and infrared regions of the spectra, because of the differing species in the understory for each site. Temporal (seasonal) variation for each site was also observed (06-Feb-1994 to 16-Sep-1994), indicating the changing flora mixtures and changing spectral signatures as the understory matures during the growing season. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Miller, John R.↗
NASA NTRSDate not supplied

Remote Sensing of Lineage Functional Types for Modeling and Monitoring Biodiversity

Hyperspectral remote sensing has the potential to continuously scale plant function and plant diversity information from landscape to global extents. Numerous studies have indicated that VSWIR (400-2500 nm) reflectance properties of vegetation capture evolutionarily conserved biochemical, structural, and other functional attributes of plant species. Spectral properties conserved in plants provide the opportunity to both 1) aggregate species into lineages with improved classification accuracy and 2) link those lineages directly to plant traits. Full realization of this goal will enable parameterization of Land Surface Models (LSMs) with remotely sensed information, e.g., canopy nitrogen, and better representations of biodiversity and functional diversity in biogeographic studies. In this study, we use hyperspectral AVIRIS data from the 2013 HyspIRI campaign over the Southern Sierra Nevada, California flight box to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from roughly 1372 surveys and a phylogeny representing 1361 species. We aggregate species into lineages ranging from species level groups down to similar number of Plant Functional Types as often used in LSMs. We assessed the ability of Random Forest and Partial Least Squares Discriminant Analysis to discriminate across these different phylogenetic scales and determine the optimal number of lineages to classify. Although there are some temporal and spatial differences in our training data, our best approaches achieved moderate classification accuracy (Kappa > 0.65). Given an optimal number of lineages, we explored approaches to improve classifications including machine learning and unmixing approaches. This work suggests that lineage-based methods may be a promising way to leverage the huge amounts of data that will come from high resolution and high return interval hyperspectral data planned for the Surface Biology and Geology mission with sparsely sampled existing ground-based ecological data.

Hyperspectral↗
NASA NTRS1981

Use of LANDSAT for land use and habitat inventories for the New Jersey Pinelands

The New Jersey Heritage program surveyed available mapping information on landcover and vegetative communities and found that most commonly used sources, such as local land use maps and aerial photographs, were useful for individual sites, but either varied in their classifications or could not be used over extensive areas. A demonstration project using LANDSAT satellite information for the Great Egg Harbor/Tuckahoe watersheds was initiated with the goals of application (providing an inventory of vegetative communities and land use) flexibility (providing a method of collecting data which can be updated or modified in the future); and efficiency (allowing for an acceptable cost level by having staff undertake the project and avoid the more costly methods from air photo interpretation or on-site surveying. The classification procedure used is described and the spatial distributions of the 10 landcover classes determined are listed.

Tracy, C.↗
NASA NTRS1975

An assessment of the impact of water impoundment and diversion structures on vegetation in Southern Arizona

High-altitude color infrared photography was used to survey existing conditions, both upstream and downstream, from nineteen diversion structures in Southern Arizona to determine their effect upon vegetation health, vigor, and cover. A diversion structure is defined as a man/made feature constructed to control storm runoff. The results are used to determine the policy for future structure design.

Conn, J. S.↗
NASA NTRS2023

The Earth in Living Color - NASA’s Surface Biology and Geology Designated Observable

The Surface Biology and Geology (SBG) Designated Observable will transform our understanding of the global land surface, inland and coastal aquatic ecosystems through visible-to-shortwave infra-red imaging (VSWIR) spectroscopy and thermal infra-red (TIR) imaging. SBG is one of four high-priority observables recommended in the 2017 NASA Earth Science Decadal Survey t o address science questions on vegetation and aquatic ecosystem health, snow-cover dynamics, volcanic activity, and minerology. With a planned launch readiness date of 2028, SBG is currently in Pre-Phase A, with Level 1 requirements being developed for a two-spacecraft architecture, including an additional constellation pathfinder. The recommended architecture emerged from an extensive study (2018-2021) that engaged the research and applications community to consider the science questions and measurement objectives of the Decadal Survey. A Science and Applications Traceability Matrix was used as a basis for scoring candidate architectures, with inputs from four working groups that covered algorithms, applications, calibration and validation, and modeling. Two pathfinder studies, Modeling End-to-End Traceability in support of SBG (MEET-SBG) and Space-based Imaging Spectroscopy and Thermal pathfindER (SISTER) are providing pre-launch modeling tools and data for algorithm development to support science value trades. The architecture consists of one spacecraft hosting a wide-swath VSWIR imaging spectrometer providing 30-m ground-sample distance (GSD), a spectral range of 380-2500 nm (at 10 nm resolution), 16-day revisit with 400 signal-to-noise for VNIR and 250 for SWIR (at 25% reflectance). A separate spacecraft will host a wide swath thermal imager, with five to seven bands placed between 4-12 μm), with 60-m (GSD), 3- day revisit, and 0.2K noise-equivalent differential temperature (NeDT). A VNIR compact camera will be hosted on the TIR spacecraft to enable coincident TIR and VNIR observations. A constellation pathfinder will evaluate options for enabling VSWIR mission continuity using Small Sats or data buys. Partnerships with international space agencies contribute technology as well as improvements to temporal revisit. SBG, when launched, will be the first dedicated mission collecting the full spectra of the Earth’s ‘living color’ and will play a critical role in NASA’s Earth System Observatory.

David S Schimel↗
NASA NTRSDate not supplied

Assessing the Feasibility of Using Various Earth Observations to Monitor Environmental Trends Associated with River Flow Impediments Near Energy Intake Structures

Grassing events, characterized by the release of river vegetation in large quantities, are often responsible for major flow impediments surrounding industrial water intake structures. These sudden flow impediments halt critical municipal functions, such as cooling at energy generating facilities, leading to widespread energy disruptions for surrounding communities. Because the origin and cause of grassing events in rivers are largely unknown, employees at these facilities can only reactively respond after they occur by pausing energy generation to manually remove the accumulation of aquatic vegetation. In 2023, the Dresden Generating Station, in collaboration with the United States Geological Survey, began looking into using remote sensing methodologies to locate floating aquatic vegetation surrounding their intake structure located along the Kankakee River in northern Illinois. This project contributed to this effort by conducting a case study that compared the performance, practicality, and feasibility of using various Earth observations (Landsat 9 OLI-2, Landsat 8 OLI, Sentinel-2 MSI, and DOVE PlanetScope) and vegetation indices (NDVI, EVI, SAVI, and GCI) to monitor aquatic vegetation in the Kankakee River. Additionally, this study incorporated several environmental metrics to identify potential triggers for grassing events. Results from this project found that while Landsat sensors provide a lower spatial resolution than commercial satellite Earth observations, areas of aquatic vegetation were similarly identified; therefore, it may not be necessary to acquire expensive, high-resolution datasets for continued monitoring. Finally, preliminary correlation analyses showed a potential negative relationship between the river discharge and the presence of aquatic vegetation (-0.875 correlation coefficient), suggesting that periods of low flow could lead to large releases in aquatic vegetation.

Marisa Smedsrud↗
NASA NTRS1975

Remote Sensing of Earth Resources (1970 - 1973 supplement): A literature survey with indexes. Section 2: Indexes

Documents related to the identification and evaluation by means of sensors in spacecraft and aircraft of vegetation, minerals, and other natural resources, and the techniques and potentialities of surveying and keeping up-to-date inventories of such riches are cited. These documents were announced in the NASA scientific and technical information system between March 1970 and December 1973.

Source record↗
NASA NTRS2015

Dissemination of Earth Remote Sensing Data for Use in the NOAA/NWS Damage Assessment Toolkit

The National Weather Service has developed the Damage Assessment Toolkit (DAT), an application for smartphones and tablets that allows for the collection, geolocation, and aggregation of various damage indicators that are collected during storm surveys. The DAT supports the often labor‐intensive process where meteorologists venture into the storm‐affected area, allowing them to acquire geotagged photos of the observed damage while also assigning estimated EF‐scale categories based upon their observations. Once the data are collected, the DAT infrastructure aggregates the observations into a server that allows other meteorologists to perform quality control and other analysis steps before completing their survey and making the resulting data available to the public. In addition to in‐person observations, Earth remote sensing from operational, polar-orbiting satellites can support the damage assessment process by identifying portions of damage tracks that may be missed due to road limitations, access to private property, or time constraints. Products resulting from change detection techniques can identify damage to vegetation and the land surface, aiding in the survey process. In addition, higher resolution commercial imagery can corroborate ground‐based surveys by examining higher‐resolution commercial imagery. As part of an ongoing collaboration, NASA and NOAA are working to integrate near real‐time Earth remote sensing observations into the NOAA/NWS Damage Assessment Toolkit. This presentation will highlight recent developments in a streamlined approach for disseminating Earth remote sensing data via web mapping services and a new menu interface that has been integrated within the DAT. A review of current and future products will be provided, including products derived from MODIS and VIIRS for preliminary track identification, along with conduits for higher‐resolution Landsat, ASTER, and commercial imagery as they become available. In addition to tornado damage assessments, the team is also investigating the use of near real‐time imagery for identifying hail damage to vegetation, which also results in large swaths of damage, particularly in the central United States during the peak growing season months of June, July, and August. This presentation will present an overview of recent activities, challenges and successes, best practices, and opportunities for future work and collaboration

Molthan, Andrew↗