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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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11 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Future of Land Remote Sensing: What is Needed

A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do. A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do.

Goward, Samuel N.↗
DOE OSTI2026

CHESS 2025: Orthorectified airborne RGB imagery from NEON AOP surveys

This dataset provides Level 1 (L1) and Level 3 (L3) orthorectified Red-Green-Blue (RGB) imagery collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). This high-resolution imagery is a photographic record of red, green, and blue visible light from sunlight reflected off of the Earth’s surface. The data comprise full-color images of the ground surface and are primarily intended to provide context to imaging spectroscopy and light detection and ranging (LiDAR) data. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. RGB images were acquired using the PhaseOne IXM-RS150F high-resolution digital camera onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). The package data include both an L1 product comprising one camera frame per file and an L3 mosaic aligned to the Universal Transverse Mercator (UTM) Zone 13N grid and the World Geodetic System (WGS) 84 projection. Both products are provided in geotif (.tif) format at 0.1 m ground resolution. The bulk of the imagery was collected during the main CHESS field campaign from June 13 to July 15, 2025. Additional images of a portion of the Upper Taylor (UPTA) domain were collected on September 18, 2025, to fill gaps in imagery identified after the main campaign was complete. RGB camera imagery is not radiometrically calibrated, and therefore pixel values should not be exploited for scientific analysis. Pixel values have undergone a manual adjustment to enhance feature identification. The imagery is rigorously geolocated which does allow for reliable geometric information to be retrieved. To generate the orthorectified imagery, the NEON AOP camera captured visible spectrum in red, green, and blue bands. The raw images were then processed using NEON’s camera orthorectification workflow. A boresight calibration flight was made to build a complete camera, distortion, and alignment model. Color balance/white balance and exposure correction were applied to the raw RGB images. The corrected images were orthorectified by ray-tracing image pixels to a lidar-derived digital surface model (DSM) mesh using the refined camera model, outputting orthorectified raster pixels on a regular grid. Flightline-level data were mosaicked by selecting per-pixel contributions from overlapping orthorectified images using line-of-sight (LOS) zenith angle minimization to reduce edge distortions. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also 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.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2024

Dual-Image Color Normalization to Enable High-Performance Concentrating Solar Optical Metrology

Concentrating Solar Power (CSP) requires precision mirrors, and these in turn require metrology systems to measure their optical slope. In this project we studied a color-based approach to the correspondence problem, which is the association of points on an optical target with their corresponding points seen in a reflection. This is a core problem in deflectometry-based metrology, and a color solution would enable important new capabilities. We modeled color as a vector in the [R,G,B] space measured by a digital camera, and explored a dual-image approach to compensate for inevitable changes in illumination color. Through a series of experiments including color target design and dual-image setups both indoors and outdoors, we collected reference/measurement image pairs for a variety of configurations and light conditions. We then analyzed the resulting image pairs by selecting example [R,G,B] pixels in the reference image, and seeking matching [R,G,B] pixels in the measurement image. Modulating a tolerance threshold enabled us to assess both match reliability and match ambiguity, and for some configurations, orthorectification enabled us to assess match accuracy. Using direct-direct imaging, we demonstrated color correspondence achieving average match accuracy values of 0.004 h, where h is the height of the color pattern. We found that wide-area two-dimensional and linear one-dimensional color targets outperformed hybrid linear/lateral gradient targets in the cases studied. Introducing a mirror degraded performance under our current techniques, and we did not have time to evaluate whether matches could be reliably achieved despite varying light conditions. Nonetheless, our results thus far are promising.

14 SOLAR ENERGY↗
NASA NTRS1992

Geometric ortho-rectification and generation of sigma(0) image products from multiple incidence synthetic aperture radar images

The results of the first phase of a cooperative effort in geometric orthorectification and generation of sigma(0) images of multiple incidence SAR images are presented. The geometric accuracy of the final image products is approximately 18 m or 1.5 pixels. A method for registering radar imagery collected from an airborne platform to an existing digital elevation model despite the effects of unmodeled variations in the flight path of the platform is demonstrated. The results indicate the requirements for a more detailed digital elevation model.

Curlander, James↗
NASA NTRS2004

Geopositional Accuracy Assessment of EarthSat Geocover Landsat Orthorectified Imagery

NASA purchased EarthSat GeoCover orthorectified Landsat imagery of global land areas covering three historical frames: (1) mid-1970's imagery from the Landsat Multispectral Scanner (MSS); (2) late 1980's-early 1990's imagery from the Landsat Thematic Mapper (TM); and (3) year 2000 imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+). Because of the distinct time frames covered by these datasets, this imagery is valuable to land cover change research. Because geopositional accuracy plays a critical role in this area of scientific research. NASA performed an independent assessment of the geopositional accuracy of each EarthSat dataset using an independent set of government-provided ground control points (GCPs). These points were instrumental in the geopositional accuracy assessment of the TM imagery. Because of the orthorectification processes of the MSS imagery and the MSS pixel size, the aforementioned GCPs could not be used, and an alternate relative assessment procedure using the previously validated TM imagery as a "truth" dataset was used for the MSS data. Finally, the ETM data specification was defined in both an absolute sense with respect to ground coordinated and relative to the previously validated TM dataset. Therefore, two separate methods were used in validating the ETM-data. Results of the NASA independent assessments showed that the accuracies of the EarthSat GeoCover datasets met the defined specifications or were within the error and limitations of the verification methods employed.

Smith, Charles M.↗
NASA NTRS2006

An improved method for precise automatic co-registration of moderate and high-resolution spacecraft imagery

Improvements to the automated co-registration and change detection software package, AFIDS (Automatic Fusion of Image Data System) has recently completed development for and validation by NGA/GIAT. The improvements involve the integration of the AFIDS ultra-fine gridding technique for horizontal displacement compensation with the recently evolved use of Rational Polynomial Functions/ Coefficients (RPFs/RPCs) for image raster pixel position to Latitude/Longitude indexing. Mapping and orthorectification (correction for elevation effects) of satellite imagery defies exact projective solutions because the data are not obtained from a single point (like a camera), but as a continuous process from the orbital path. Standard image processing techniques can apply approximate solutions, but advances in the state-of-the-art had to be made for precision change-detection and time-series applications where relief offsets become a controlling factor. The earlier AFIDS procedure required the availability of a camera model and knowledge of the satellite platform ephemeredes. The recent design advances connect the spacecraft sensor Rational Polynomial Function, a deductively developed model, with the AFIDS ultrafine grid, an inductively developed representation of the relationship raster pixel position to latitude /longitude. As a result, RPCs can be updated by AFIDS, a situation often necessary due to the accuracy limits of spacecraft navigation systems. An example of precision change detection will be presented from Quickbird.

co-registration↗
NASA NTRS2020

The New Landsat Collection-2 Digital Elevation Model

The Landsat Collection-2 distribution introduces a new global Digital Elevation Model (DEM) for scene orthorectification. The new global DEM is a composite of the latest and most accurate freely available DEM sources and will include reprocessed Shuttle Radar Topographic Mission (SRTM) data (called NASADEM), high-resolution stereo optical data (ArcticDEM), a new National Elevation Dataset(NED) and various publicly available national datasets including the Canadian Digital Elevation Model (CDEM) and DEMs for Sweden, Norway and Finland (SNF). The new DEM will be available world-wide with few exceptions. It is anticipated that the transition from theCollection-1 DEM at 3 arcsecond to the new DEM will be seamless because processing methods to maintain a seamless transition were employed, void filling techniques were used, where persistent gaps were found, and the pixel spacing is the same between the two collections. Improvements to the vertical accuracy were realized by differencing accuracies of other elevation datasets to the new DEM. The greatest improvement occurred where ArcticDEM data were used, where an improvement of 35 meters was measured. By using theses improved vertical values in a line of sight algorithm, horizonta improvements were noted in some of the most mountainous regions over multiple 30-meter Landsat pixels. This new DEM will be used to process all of the scenes from Landsat 1-8 in Collection-2 processing and will be made available to the public by the end of 2020.

Shannon Franks↗
NASA NTRS2021

The New Landsat Global Land Survey (GLS) DEM

The Landsat project, for its Collection 2 distribution, is going to introduce a new global Digital Elevation Model (DEM) for scene orthorectification. The new global DEM is a composite of the latest and greatest available DEM sources and will include reprocessed SRTM (called NASADEM), hi-resolution stereo optical data (ArcticDEM), and various nationally produced datasets. With exception of a few places, most of the world will have the updated DEM, with improvements in absolute vertical accuracy and horizontal improvements of up to 360 meters (12 Landsat 30m pixels). This new DEM will be used to process all the scenes from Landsat 1-8 in Collection 2 processing and will be made available to public in Summer 2020.

Landsat↗
NASA NTRS2012

Automated Data Production For A Novel Airborne Multiangle Spectropolarimetric Imager (AIRMSPI)

A novel polarimetric imaging technique making use of rapid retardance modulation has been developed by JPL as a part of NASA's Instrument Incubator Program. It has been built into the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) under NASA's Airborne Instrument Technology Transition Program, and is aimed primarily at remote sensing of the amounts and microphysical properties of aerosols and clouds. AirMSPI includes an 8-band (355, 380, 445, 470, 555, 660, 865, 935 nm) pushbroom camera that measures polarization in a subset of the bands (470, 660, and 865 nm). The camera is mounted on a gimbal and acquires imagery in a configurable set of along-track viewing angles ranging between +67 deg and -67 deg relative to nadir. As a result, near simultaneous multi-angle, multi-spectral, and polarimetric measurements of the targeted areas at a spatial resolution ranging from 7 m to 20 m (depending on the viewing angle) can be derived. An automated data production system is being built to support high data acquisition rate in concert with co-registration and orthorectified mapping requirements. To date, a number of successful engineering checkout flights were conducted in October 2010, August-September 2011, and January 2012. Data products resulting from these flights will be presented.

Multi-angle↗