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At least 37 records · Page 2

First results from the crop identification technology assessment for remote sensing /CITARS/

The CITARS task design, including objectives, analysis methodology and experimental procedures, is described and first results from this effort are presented. The extensive ground truth data set acquired for the CITARS task is described and discussed in some detail. Results of the accuracy tests for the photo interpretative CITARS ground truth are given. Results of the assessment of the ERTS MSS data for cloud cover and electronic quality are presented. Some results of the geometric correction and registration of the time sequential CITARS ERTS data are given. Finally, the field boundary selection problem is addressed and the results of the use of new technology for boundary selection are presented.

Hall, F. G.↗

Remote Sensing Assessment of Lunar Resources: We Know Where to Go to Find What We Need

The utilization of space resources is necessary to not only foster the growth of human activities in space, but is essential to the President s vision of a "sustained and affordable human and robotic program to explore the solar system and beyond." The distribution of resources will shape planning permanent settlements by affecting decisions about where to locate a settlement. Mapping the location of such resources, however, is not the limiting factor in selecting a site for a lunar base. It is indecision about which resources to use that leaves the location uncertain. A wealth of remotely sensed data exists that can be used to identify targets for future detailed exploration. Thus, the future of space resource utilization pre-dominantly rests upon developing a strategy for resource exploration and efficient methods of extraction.

Gillis, J. J.↗

Results from the Crop Identification Technology Assessment for Remote Sensing (CITARS) project

The author has identified the following significant results. It was found that several factors had a significant effect on crop identification performance: (1) crop maturity and site characteristics, (2) which of several different single date automatic data processing procedures was used for local recognition, (3) nonlocal recognition, both with and without preprocessing for the extension of recognition signatures, and (4) use of multidate data. It also was found that classification accuracy for field center pixels was not a reliable indicator of proportion estimation performance for whole areas, that bias was present in proportion estimates, and that training data and procedures strongly influenced crop identification performance.

Bauer, M. E.↗

Crop identification technology assessment for remote sensing (CITARS). Volume 10: Interpretation of results

The CITARS was an experiment designed to quantitatively evaluate crop identification performance for corn and soybeans in various environments using a well-defined set of automatic data processing (ADP) techniques. Each technique was applied to data acquired to recognize and estimate proportions of corn and soybeans. The CITARS documentation summarizes, interprets, and discusses the crop identification performances obtained using (1) different ADP procedures; (2) a linear versus a quadratic classifier; (3) prior probability information derived from historic data; (4) local versus nonlocal recognition training statistics and the associated use of preprocessing; (5) multitemporal data; (6) classification bias and mixed pixels in proportion estimation; and (7) data with differnt site characteristics, including crop, soil, atmospheric effects, and stages of crop maturity.

Bizzell, R. M.↗

Detection and identification of Arctic landforms - An assessment of remotely sensed data

The use of remote sensing data to monitor and analyze the arctic environment is examined. Landsat MSS, TM simulated, NS001, Seasat, and airborne radar are employed to investigate the Strand and Dune areas on the Arctic Coastal Plain in Alaska. The Strand area contains landforms associated with permafrost and the Dune area is dominated by eolian deposits consisting of large longitudinal dunes. The remote sensing data are compared to baseline geomorphic maps derived from aerial photography. It is observed that the multispectral data are better than the radar data for the detection and recognition of arctic landforms, and the NS001 data provided the highest spatial resolution and correlated well with the high-altitude aerial photography.

Dean, Kenneson G.↗

Assessment of Remote Sensing Technologies for Location of Hydrogen and Helium Leaks

In Phase 1 of this project, a hierarchy of techniques for H2 and He leak location was developed. A total of twelve specific remote sensing techniques were evaluated; the results are summarized. A basic diffusion model was also developed to predict the concentration and distribution of H2 or He resulting from a leak. The objectives of Phase 2 of the project consisted of the following four tasks: Advance Rayleigh Doppler technique from TRL 1 to TRL 2; Plan to advance Rayleigh Doppler technique from TRL 2 to TRL 3; Advance researchers and resources for further advancement; Extend diffusion model.

Sellar, R. Glenn↗

Assessment of Remote Sensing Technologies for Location of Hydrogen and Helium Leaks

The objective of this initial phase of this research effort is to: 1) Evaluate remote sensing technologies for location of leaks of gaseous molecular hydrogen (H2) and gaseous helium (He) in air, for space transportation applications; and 2) Develop a diffusion model that predicts concentration of H2 or He gas as a function of leak rate and distance from the leak.

Sellar, R. Glenn↗

Competing effects of soil fertility and toxicity on tropical greening

Tropical forests are expected to green up with increasing atmospheric CO 2 concentrations, but primary productivity may be limited by soil nutrient availability. However, rarely have canopy-scale measurements been assessed against soil measurements in the tropics. Here, we sought to assess remotely sensed canopy greenness against steep soil nutrient gradients across 50 1-ha mature forest plots in Panama. Contrary to expectations, increases in in situ extractable soil phosphorus (P) and base cations (K, Mg) corresponded to declines in remotely sensed mean annual canopy greenness (r 2 = 0.77– 0.85; p < 0.1), controlling for precipitation. The reason for this inverse relationship appears to be that litterfall also increased with increasing soil P and cation availability (r 2 = 0.88–0.98; p < 0.1), resulting in a decline in greenness with increasing annual litterfall (r 2 = 0.94; p < 0.1). As such, greater soil nutrient availability corresponded to greater leaf turnover, resulting in decreased greenness. However, these decreases in greenness with increasing soil P and cations were countered by increases in greenness with increasing soil nitrogen (N) (r 2 = 0.14; p < 0.1), which had no significant relationship with litterfall, likely reflecting a direct effect of soil N on leaf chlorophyll content, but not on litterfall rates. In addition, greenness increased with extractable soil aluminum (Al) (r 2 = 0.97; p < 0.1), but Al had no significant relationship with litterfall, suggesting a physiological adaptation of plants to high levels of toxic metals. Thus, spatial gradients in canopy greenness are not necessarily positive indicators of soil nutrient scarcity. Using a novel remote sensing index of canopy greenness limitation, we assessed how observed greenness compares with potential greenness. We found a strong relationship with soil N only (r 2 = 0.65; p < 0.1), suggesting that tropical canopy greenness in Panama is predominantly limited by soil N, even if plant productivity (e.g., litterfall) responds to rock-derived nutrients. Moreover, greenness limitation was also significantly correlated with fine root biomass and soil carbon stocks (r 2 = 0.62–0.71; p < 0.1), suggesting a feedback from soil N to canopy greenness to soil carbon storage. Altogether, these data point to the potential utility of a remote sensing product for assessing belowground properties in tropical ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Update and review of accuracy assessment techniques for remotely sensed data

Research performed in the accuracy assessment of remotely sensed data is updated and reviewed. The use of discrete multivariate analysis techniques for the assessment of error matrices, the use of computer simulation for assessing various sampling strategies, and an investigation of spatial autocorrelation techniques are examined.

Congalton, R. G.↗

Inferring plant–plant interactions using remote sensing

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis . Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Energy and remote sensing

Exploration for uranium, thorium, oil, gas and geothermal activity through remote sensing techniques is considered; satellite monitoring of coal-derived CO2 in the atmosphere, and the remote assessment of strip mining and land restoration are also mentioned. Reference is made to color ratio composites based on Landsat data, which may aid in the detection of uranium deposits, and to computer-enhanced black and white airborne scanning imagery, which may locate geothermal anomalies. Other applications of remote sensing to energy resources management, including mapping of transportation networks and power plant siting, are discussed.

Summers, R. A.↗

Remote Sensing of Solar-Induced Chlorophyll Fluorescence (SIF) in Vegetation: 50 Years of Progress

Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF – especially from space – is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using highly-resolved spectral sensors and state-of-the-art algorithms to distinguish the emission from reflected and/or scattered ambient light. Because the red to far-red SIF emission is detectable non-invasively, it may be sampled repeatedly to acquire spatio-temporally explicit information about photosynthetic light responses and steady-state behaviour in vegetation. Progress in this field is accelerating with innovative sensor developments, retrieval methods, and modelling advances. This review distills the historical and current developments spanning the last several decades. It highlights SIF heritage and complementarity within the broader field of fluorescence science, the maturation of physiological and radiative transfer modelling, SIF signal retrieval strategies, techniques for field and airborne sensing, advances in satellite-based systems, and applications of these capabilities in evaluation of photosynthesis and stress effects. Progress, challenges, and future directions are considered for this unique avenue of remote sensing.

Review↗

Field Insights: Strengthening Digital Assurance Through On-Site Network Monitoring

The accelerating deployment of digital energy infrastructure, ranging from inverter-based resources (IBRs), battery energy storage systems (BESS), to advanced grid control platforms, has brought unprecedented visibility, flexibility, and efficiency to the electric grid. However, this digital transformation also introduces new cybersecurity challenges, particularly in the form of supply chain risks and operational blind spots at the grid edge. Over the past year, the Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER), through its Rapid Risk Assessment initiative, along with the Grid Deployment Office (GDO), through its Technical Assistance for Digital Assurance (TADA) initiative, have supported a series of on-site network engagements led by Idaho National Laboratory (INL). These engagements, conducted in partnership with asset owners across the country, have focused on identifying real-world vulnerabilities and misconfigurations in operational environments, many of which are not detectable through remote assessments or traditional compliance audits. The goal of this report is to distill key findings and lessons learned during network hunt engagements from INL’s fiscal year (FY) 2024 - 2025. It is intended to help asset owners—regardless of their participation in the program—better understand the evolving threat landscape and adopt practical measures to secure their digital energy infrastructure.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Laser Induced Fluorescence (LIF) as a Remote Sensing Tool: A Review

Vegetational changes are primary indicators of the present and future ecological status of the globe. These are changes which not only impact upon the primary productivity, but the total of the biogeochemical processes occurring on the planet. The impacts of global climatic and other environmental changes on vegetation must be monitored by some means in order to develop models which will allow us to predict long term effects. Large scale monitoring is now possible only with remote sensing systems, primarily passive reflectance, obtained by the use of satellite and aircraft platforms. However, passive reflectance techniques at this time are limited in their ability to detect subtle changes in the concentration and oxidation states of the many compounds involved in the light reactions of photosynthesis. Knowledge of these changes we consider to be fundamental in the remote assessment of both the rate and efficiency of photosynthesis and also the early detection of stress damage. The above factors pointed to the desirability of a sensing technique with the sensitivity and specificity necessary for detecting and quantifying those biological entities involved in photosynthesis. Another optical technique for vegetation monitoring is fluorescence. Previously, the lack of adequate excitation light sources and detector technologies have limited the use of fluorescence on intact plant leaves in the field. It is only recently with the advent of lasers with short pulse duration and advanced detector technologies that fluorescence measurements in the remote mode have become possible in the presence of ambient light.

Chappelle, E. W.↗

Lithologic mapping of silicate rocks using TIMS

Common rock-forming minerals have thermal infrared spectral features that are measured in the laboratory to infer composition. An airborne Daedalus scanner (TIMS) that collects six channels of thermal infrared radiance data (8 to 12 microns), may be used to measure these same features for rock identification. Previously, false-color composite pictures made from channels 1, 3, and 5 and emittance spectra for small areas on these images were used to make lithologic maps. Central wavelength, standard deviation, and amplitude of normal curves regressed on the emittance spectra are related to compositional information for crystalline igneous silicate rocks. As expected, the central wavelength varies systematically with silica content and with modal quartz content. Standard deviation is less sensitive to compositional changes, but large values may result from mixed admixture of vegetation. Compression of the six TIMS channels to three image channels made from the regressed parameters may be effective in improving geologic mapping from TIMS data, and these synthetic images may form a basis for the remote assessment of rock composition.

Gillespie, A. R.↗

Use of vegetation indices to estimate intercepted solar radiation and net carbon dioxide exchange of a grass canopy

Results are presented from field experiments relating spectral reflectance to intercepted photosynthetically active radiation (PAR) and net CO2 exchange in a natural canopy composed of the marsh cordgrass (Spartina alterniflora). Reflectance measurements made by a hand-held radiometer with Landsat TM spectral wavebands are used to compute remote sensing indices such as the normalized difference vegetation index. Consideration is given to the impact of standing dead canopy material on the relationship between intercepted PAR and spectral vegetation indices and the impact of changes in photosynthetic efficiency on the relationship between vegetation indices and CO2 exchange rates. The results suggest that quantitative remote assessment of photosynthesis and net gas exchange in natural vegetation is feasible, especially if the analysis incorporates information on biological responses to environmental variables.

Bartlett, David S.↗