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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Remote sensing of snowpack with microwave radiometers for hydrologic applications

A microwave remote sensing of snowpack experiment is described and some preliminary data presented. A mobile field laboratory consisting of a four-frequency (5, 10.7, 18 and 37 GHz), all with dual linear (vertical and horizontal) polarizations, microwave radiometer system attached to a truck-mounted aerial lift was used to study the microwave emission characteristics of snowpacks in the Colorado Rocky Mountains during the winter of 1977-78. The influence of snowpack physical parameters such as water equivalent, grain size, and melt-freeze cycle on its microwave brightness temperature and its implications to the application of microwave radiometric technique to remote sensing of snowpack for runoff prediction are discussed.

Shiue, J. C.↗
DOE OSTI2019

Remote sensing and geophysical characterization of a floodplain-hillslope system in the East River watershed, Colorado

This package is part of the Watershed Function SFA Data Collection and contains remote sensing data and geophysical measurements acquired at the Pumphouse hillslope-floodplain site, in the East River, Colorado. The remote sensing dataset includes: a) a WorldView-2 (WV-2) pan-sharpened multi-spectral remote sensing image, and b) LiDAR derived products. The WV-2 image was acquired on September 24th, 2015, and it is composed of eight spectral bands (coastal, blue, green, yellow, red, red edge, NIR1, and NIR2) with a spatial resolution of 0.5 m, covering an area of 750x750 m. The LiDAR products are a digital surface model (DSM), representing the top-of-canopy elevation, and a digital terrain model (DTM), representing the bare-ground elevation, at the spatial resolution of 0.5 m. Such data are extracted from the LiDAR point-cloud dataset acquired over the entire watershed on August 2015 (http://dx.doi.org/10.21952/WTR/1412542). The geophysical dataset is composed of the electrical resistivity tomography (ERT) data acquired along a 158.75 m long transect, spanning the hillslope topographical gradient with 1.25 m electrode spacing. The dataset also includes soil water content measured with a TDR system. The package provides also polygons of different vegetation communities, which were used as reference data for mapping plant community distributions. The spatial polygons are based on plant locations acquired during the field campaign of June-July 2017 using an RTK DGPS system. The reference dataset is composed by 11 vegetation classes, namely, deciduous forest, evergreen forest, riparian shrubland, sagebrush, shrubland, potentilla, frasera, lupine meadow, veratrum, bunchgrass meadow, and forb, as well as four non-vegetation classes, such as water-river, water-lake, man-made, bare area, and shadow. The vegetation classes are determined based on distinct spectral and/or structural signatures of dominant species. The package includes products derived by these datasets, such as: a) a plant height map, computed by subtracting the DTM from the DSM, and b) a plant community distribution map, obtained by using a data-fusion machine-learning-based framework that exploit the WV-2 image and plant height information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Performance of Landsat-8 and Sentinel-2 surface reflectance products for river remote sensing retrievals of chlorophyll-a and turbidity

Rivers and other freshwater systems play a crucial role in ecosystems, industry, transportation and agriculture. Despite the > 40 years of inland water observations made possible by optical remote sensing, a standardized reflectance product for inland waters is yet forthcoming. The aim of this work is to compare the standard USGS land surface reflectance product to two Landsat-8 and Sentinel-2 aquatic remote sensing reflectance products over the Amazon, Columbia and Mississippi rivers. Landsat-8 reflectance products from all three routines are then evaluated for their comparative performance in retrieving chlorophyll-a and turbidity in reference to ship- borne, underway in situ validation measurements. The land surface product shows the best agreement (4% Mean Absolute Percent Difference) with field measurements of radiometry collected on the Amazon River and gen- erates 36% higher reflectance values in the visible bands compared to aquatic methods (ACOLITE and SeaDAS) with larger differences between land and aquatic products observed in Sentinel-2 (0.01sr-1) compared to Landsat-8 (0.001 sr-1). Choice of atmospheric correction routine can bias Landsat-8 retrievals of chlorophyll-a and turbidity by as much as 59% and 35% respectively. Using a more restrictive time window for matching in situ and satellite imagery can reduce differences by 5–31% depending on correction technique. This work highlights the challenges of satellite retrievals over rivers and underscores the need for future optical and biogeochemical research aimed at improving our understanding of the absorbing and scattering properties of river water and their relationships to remote sensing reflectance.

Amazon↗
NASA NTRS1999

The Use of Remote Sensing to Resolve the Aerosol Radiative Forcing

Satellites are used for remote sensing of aerosol optical thickness and optical properties in order to derive the aerosol direct and indirect radiative forcing of climate. Accuracy of the derived aerosol optical thickness is used as a measure of the accuracy in deriving the aerosol radiative forcing. Several questions can be asked to challenge this concept. Is the accuracy of the satellite-derived aerosol direct forcing limited to the accuracy of the measured optical thickness? What are the spectral bands needed to derive the total aerosol forcing? Does most of the direct or indirect aerosol forcing of climate originate from regions with aerosol concentrations that are high enough to be detected from space? What should be the synergism ground-based and space-borne remote sensing to solve the problem? We shall try to answer some of these questions, using AVIRIS airborne measurements and simulations.

Kaufman, Y. J.↗
NASA NTRS2004

Malaria Modeling using Remote Sensing and GIS Technologies

Malaria has been with the human race since the ancient time. In spite of the advances of biomedical research and the completion of genomic mapping of Plasmodium falciparum, the exact mechanisms of how the various strains of parasites evade the human immune system and how they have adapted and become resistant to multiple drugs remain elusive. Perhaps because of these reasons, effective vaccines against malaria are still not available. Worldwide, approximately one to three millions deaths are attributed to malaria annually. With the increased availability of remotely sensed data, researchers in medical entomology, epidemiology and ecology have started to associate environmental and ecological variables with malaria transmission. In several studies, it has been shown that transmission correlates well with certain environmental and ecological parameters, and that remote sensing can be used to measure these determinants. In a NASA project, we have taken a holistic approach to examine how remote sensing and GIs can contribute to vector and malaria controls. To gain a better understanding of the interactions among the possible promoting factors, we have been developing a habitat model, a transmission model, and a risk prediction model, all using remote sensing data as input. Our objectives are: 1) To identify the potential breeding sites of major vector species and the locations for larvicide and insecticide applications in order to reduce costs, lessen the chance of developing pesticide resistance, and minimize the damage to the environment; 2) To develop a malaria transmission model characterizing the interactions among hosts, vectors, parasites, landcover and environment in order to identify the key factors that sustain or intensify malaria transmission, and 3) To develop a risk model to predict the occurrence of malaria and its transmission intensity using epidemiological data and satellite-derived or ground-measured environmental and meteorological data.

Kiang, Richard↗
NASA NTRS2000

Remote Sensing of Global Wetland Dynamics

Although natural wetlands only cover about 4% of the earth's ice-free land surface, they are the world's largest methane (CH4) source and the only one dominated by climate. In addition, wetlands affect climate by modulating temperatures and heat fluxes, storing water, increasing evaporation, and altering the seasonality of runoff and river discharge to the oceans. Current CH4 emissions from wetlands are relatively well understood but the sensitivity of wetlands and their emissions to climate variations remains the largest uncertainty in the global CH4 cycle and could strongly influence predictions of future climate. Therefore, characterizing climate-sensitive processes prevailing in the world's wetlands is crucial to understanding and predicting physical and biogeochemical responses of wetlands to interannual and longer-term climate variations. Recent research has resulted in the first generation of models to predict methane emissions from wetlands but the models must still be applied to static data on wetland distributions. Moreover, no models currently exist to realistically predict the distribution and dynamics of wetlands themselves for the current, or any other, climate. The dominant obstacle to modeling wetland dynamics has been lack of remote sensing techniques and data useful for characterizing quantitatively the seasonal and interannual variations of wetlands. We report on initial remote sensing studies undertaken to validate a global hydrological model linking rivers, takes and wetlands. Using a combination of SSM/I microwave and TOPEX Poseidon altimetry data sets, we developed and applied techniques to quantify inundation extent and duration for several large wetlands in tropical Africa and South America. Our initial results indicate that seasonally-inundated wetlands can be well characterized over large spatial scales and at monthly time scales using these remote sensing data. The results also confirm that currently available remote sensing products can be applied to provide crucial data to the research community modeling global hydrological and biogeochemical cycles.

Matthews, Elaine↗
NASA NTRS1991

Satellite remote sensing of surface energy and mass balance - Results from FIFE

Results obtained from the FIFE experiments conducted in 1987 and 1989 are summarized. Data analyses indicate that the hypotheses linking energy balance components to surface biology and remote sensing are reasonable at a point level, and that satellite remote sensing can potentially provide useful estimates of the surface energy budget. An investigation of atmospheric scattering and absorption effects on satellite remote sensing of surface radiance shows that the magnitude of atmospheric opacity variations within the FIFE site and with season can have a large effect on satellite measured values of surface radiances. Comparisons of atmospherically corrected TM radiances with surface measured radiances agreed to within about two percent at the visible and near-infrared wavelengths and to 6 percent in the midinfrared.

Hall, F. G.↗
NASA NTRS1988

The California Cooperative Remote Sensing Project

The USDA, the California Department of Water Resources (CDWR), the Remote Sensing Research Program of the University of California (UCB) and NASA have completed a 4-yr cooperative project on the use of remote sensing in monitoring California agriculture. This report is a summary of the project and the final report of NASA's contribution to it. The cooperators developed procedures that combined the use of LANDSAT Multispectral Scanner imagery and digital data with good ground survey data for area estimation and mapping of the major crops in California. An inventory of the Central Valley was conducted as an operational test of the procedures. The satellite and survey data were acquired by USDA and UCB and processed by CDWR and NASA. The inventory was completed on schedule, thus demonstrating the plausibility of the approach, although further development of the data processing system is necessary before it can be used efficiently in an operational environment.

Hlavka, Christine A.↗
NASA NTRS2013

The Solar Spectrum: An Atmospheric Remote Sensing Perspective

The solar spectrum not only contains information about the composition and structure of the sun, it also provides a bright and stable continuum source for earth remote sensing (atmosphere and surface). Many types of remote sensors use solar radiation. While high-resolution spaceborne sensors (e.g. ACE) can largely remove the effects of the solar spectrum by exo-atmospheric calibration, this isn't an option for sub-orbital sensors, such as the FTIR spectrometers used in the NDACC and TCCON networks. In this case the solar contribution must be explicitly included in the spectral analysis. In this talk the methods used to derive the solar spectrum are presented, and the underlying solar physics are discussed. Implication for remote sensing are described.

sunlight↗
DOE OSTI2024

Towards Diverse and Representative Global Pretraining Datasets for Remote Sensing Foundation Models

The design of a pretraining dataset is emerging as a critical component for the generality of foundation models. In the remote sensing realm, large volumes of imagery and benchmark datasets exist that can be leveraged to pretrain foundation models, however using this imagery in absence of a well-crafted sampling strategy is inefficient and has the potential to create biased and less generalizable models. Here, we provide a discussion and vision for the curation and assessment of pretraining datasets for remote sensing geospatial foundation models. We highlight the importance of geographic, temporal, and image acquisition diversity and review possible strategies to enable such diversity at global scale. In addition to these characteristics, support for various spatial-temporal pretext tasks within the dataset is also critical. Ultimately, our primary objective is to place emphasis on and draw attention to the data curation stage of the foundation model development pipeline. By doing so, we think it is possible to reduce biases of geospatial foundation models, as well as enable broader generalization to downstream remote sensing tasks and applications.

Arndt, Jacob↗
NASA NTRS1988

The earth observing system - A mission for lidar remote sensing technology

NASA plans an earth observing system (EOS) to address low earth orbit remote sensing satellite requirements. EOS will incorporate three active remote-sensing instruments employing some form of lidar: (1) the Lidar Atmospheric Sounder and Altimeter (LASA), the Laser Atmospheric Wind Sounder (LAWS), and the Geodynamics Laser Ranging System (GLRS). LASA will deepen understanding of atmospheric composition and structure; LAWS will measure winds using Doppler lidar technology; GLRS will be used to ascertain the position of strategically placed retroreflectors to an accuracy of several cm.

Sokoloski, Martin M.↗
NASA NTRS1982

Remote sensing and hydrologic models

Hydrology moels are reviewed in order to provide information for evaluating the use of remote sensing capabilities. Strategies for using remotely sensed data in hydrology moels are also discussed.

Peck, E. L.↗
NASA NTRS1983

Passive remote sensing of ocean optical propagation parameters

A method is described for producing a global data of ocean optical properties through the exploitation of optical remote sensing techniques. The diffuse attenuation, K, and the radiance reflectance factor R sub L, of the ocean surface waters can be derived from the radiance data provided by the Coastal Zone Color Scanner and compiled into a computer based atlas of these properties. While these remotely sensed values can only be directly related to the water properties in the first or upper attenuation length, extensive in water measurements have demonstrated that a useful correlation exists between the K that applies to the upper attenuation length, for example, and the mean K over the upper 100 or 200 meters of the ocean. Such an empirical finding greatly enhances the usefulness of this remotely sensed propagation parameter. Examples of the type of information being produced and archived for the atlas are presented.

Austin, R. W.↗
DOE OSTI2023

From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I—Harnessing theory

Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three-dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi-sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5-10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous yet practically applicable analytical framework. Guided by this framework, we offer theoretical perspectives on three overarching questions: (1) The forward (mechanism) question—How are the dynamics of SIF affected by terrestrial ecosystem structure and function? (2) The inference question: What aspects of terrestrial ecosystem structure, function, and service can be reliably inferred from remotely sensed SIF and how? (3) The innovation question: What innovations are needed to realize the full potential of SIF remote sensing for real-world applications under climate change? In conclusion, the analytical framework elucidates that process complexity must be appreciated in inferring ecosystem structure and function from the observed SIF; this framework can serve as a diagnosis and inference tool for versatile applications across diverse spatial and temporal scales.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2011

Estar to SMOS: Development of Interferometric Radiometry for Remote Sensing from Space

ESTAR is an L-band radiometer that employs synthesis (interferometry) to obtain resolution in the across track dimension. It was designed as an aircraft prototype to demonstrate the technology of aperture synthesis for remote sensing of the earth from space. ESTAR was successful in several soil moisture and ocean salinity remote sensing experiments and demonstrated the potential of aperture synthesis for remote sensing. Among the lessons learned during the development of ESTAR are the scene dependence of calibration, that RFI is a problem, and the robustness of noise injection for the zero spacing radiometer. ESTAR was the first step in a path toward realizing aperture synthesis technology in space (e.g. SMOS). ESTAR was followed by a new instrument, 2D-STAR, which employs synthesis in both dimensions. 2D-STAR was tested in 2002 and participated in the SMEX field campaigns in 2003 and 2004.

LeVine, David M.↗
NASA NTRS2016

Validation of Ocean Color Remote Sensing Reflectance Using Autonomous Floats

The use of autonomous proling oats for observational estimates of radiometric quantities in the ocean is explored, and the use of this platform for validation of satellite-based estimates of remote sensing reectance in the ocean is examined. This effort includes comparing quantities estimated from oat and satellite data at nominal wavelengths of 412, 443, 488, and 555 nm, and examining sources and magnitudes of uncertainty in the oat estimates. This study had 65 occurrences of coincident high-quality observations from oats and MODIS Aqua and 15 occurrences of coincident high-quality observations oats and Visible Infrared Imaging Radi-ometer Suite (VIIRS). The oat estimates of remote sensing reectance are similar to the satellite estimates, with disagreement of a few percent in most wavelengths. The variability of the oatsatellite comparisons is similar to the variability of in situsatellite comparisons using a validation dataset from the Marine Optical Buoy (MOBY). This, combined with the agreement of oat-based and satellite-based quantities, suggests that oats are likely a good platform for validation of satellite-based estimates of remote sensing reectance.

In Situ Oceanic Observations↗
DOE OSTI2023

Seeing the Disturbed Forest for the Trees: Remote Sensing Is Underutilized to Quantify Critical Zone Response to Unprecedented Disturbance

Understanding the severity and extent of near surface critical zone (CZ) disturbances and their ecosystem response is a pressing concern in the face of increasing human and natural disturbances. Predicting disturbance severity and recovery in a changing climate requires comprehensive understanding of ecosystem feedbacks among vegetation and the surrounding environment, including climate, hydrology, geomorphology, and biogeochemistry. Field surveys and satellite remote sensing have limited ability to effectively capture the spatial and temporal variability of disturbance and CZ properties. Technological advances in remote sensing using new sensors and new platforms have improved observations of changes in vegetation canopy structure and productivity; however, integrating measures of forest disturbance from various sensing platforms is complex. By connecting the potential for remote sensing technologies to observe different CZ disturbance vectors, we show that lower severity disturbance and slower vegetation recovery are more difficult to quantify. Case studies in montane forests from the western United States highlight new opportunities, including evaluating post-disturbance forest recovery at multiple scales, shedding light on understory vegetation regrowth, detecting specific physiological responses, and refining ecohydrological modeling. Learning from regional CZ disturbance case studies, we propose future directions to synthesize fragmented findings with (a) new data analysis using new or existing sensors, (b) data fusion across multiple sensors and platforms, (c) increasing the value of ground-based observations, (d) disturbance modeling, and (e) synthesis to improve understanding of disturbance.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

The Spectrum Outlook for Earth Remote Sensing Post WRC-19

Every three to four years the International Telecommunication Union (ITU), a specialized agency of the United Nations, holds a treaty level meeting known as the World Radiocommunication Conference (WRC) to set international regulations on the use of the radio frequency spectrum. These regulations include protections for critical remote sensing bands. This paper presents the background information on, and the outcomes of, WRC-19. It also provides an examination of the potential regulatory actions that could impact the remote sensing community at the next WRC slated to be held in 2023. Lastly, the paper discusses the need for coordinated, intercalibrated interference monitoring and reporting within the remote sensing community.

radio frequency interference↗