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NASA NTRS2012

Development of RGB Composite Imagery for Operational Weather Forecasting Applications

The NASA Short-term Prediction Research and Transition (SPoRT) Center, in collaboration with the Cooperative Institute for Research in the Atmosphere (CIRA), is providing red-green-blue (RGB) color composite imagery to several of NOAA s National Centers and National Weather Service forecast offices as a demonstration of future capabilities of the Advanced Baseline Imager (ABI) to be implemented aboard GOES-R. Forecasters rely upon geostationary satellite imagery to monitor conditions over their regions of responsibility. Since the ABI will provide nearly three times as many channels as the current GOES imager, the volume of data available for analysis will increase. RGB composite imagery can aid in the compression of large data volumes by combining information from multiple channels or paired channel differences into single products that communicate more information than provided by a single channel image. A standard suite of RGB imagery has been developed by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), based upon the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The SEVIRI instrument currently provides visible and infrared wavelengths comparable to the future GOES-R ABI. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the NASA Terra and Aqua satellites can be used to demonstrate future capabilities of GOES-R. This presentation will demonstrate an overview of the products currently disseminated to SPoRT partners within the GOES-R Proving Ground, and other National Weather Service forecast offices, along with examples of their application. For example, CIRA has used the channels of the current GOES sounder to produce an "air mass" RGB originally designed for SEVIRI. This provides hourly imagery over CONUS for looping applications while demonstrating capabilities similar to the future ABI instrument. SPoRT has developed similar "air mass" RGB imagery from MODIS, and through a case study example, synoptic-scale features evident in single-channel water vapor imagery are shown in the context of the air mass product. Other products, such as the "nighttime microphysics" RGB, are useful in the detection of low clouds and fog. Nighttime microphysics products from MODIS offer some advantages over single-channel or spectral difference techniques and will be discussed in the context of a case study. Finally, other RGB products from SEVIRI are being demonstrated as precursors to GOES-R within the GOES-R Proving Ground. Examples of "natural color" and "dust" imagery will be shown with relevant applications.

Molthan, Andrew L.↗

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↗

NASA NTRS1973

Application of ERTS-1 Imagery to Flood Inundation Mapping

Ground data and a variety of low-altitude multispectral imagery were acquired for the East Nishnabotna River on September 14 and 15. This successful effort concluded that a near-visible infrared sensor could map inundated areas in late summer for at least three days after flood recession. ERTS-1 multispectral scanner subsystem (MSS) imagery of the area was obtained on September 18 and 19. Analysis of MSS imagery by IGSRSL, USGS, and NASA reinforced the conclusions of the low-altitude study while increasing the time period critical for imagery acquisition to at least 7 days following flood recession. The capability of satellite imagery to map late summer flooding at a scale of 1:250,000 is exhibited by the agreement of interpreted flood boundaries obtained from ERTS-1 imagery to boundaries mapped by low-altitude imagery and ground methods.

Hallberg, G. R.↗

NASA NTRS2001

The ASPRS Digital Imagery Product Guideline Project

The American Society for Photogrammetry and Remote Sensing (ASPRS) Primary Data Acquisition Division is developing a Digital Imagery Product Guideline in conjunction with NASA, the U.S. Geological Survey (USGS), the National Imagery and Mapping Agency (NIMA), academia, and industry. The goal of the guideline is to offer providers and users of digital imagery a set of recommendatons analogous those defined by the ASPRS Aerial Photography 1995 Draft Standard for film-based imagery. This article offers a general outline and description of the Digital Imagery Product Guideline and Digital Imagery Tutorial/Reference documents for defining digital imagery requirements.

Ryan, Robert↗

NASA NTRS2019

Rapidly Connecting You to the World: Improving NASA’s Worldview to Enhance Discovery and Access to Near Real-Time Imagery

The world around us is constantly in motion. Storms swirl, fires rage, volcanoes erupt and icebergs calve. NASA’s fleet of Earth Observing System (EOS) satellites are there to capture this. Within hours of satellite overpass, NASA’s Worldview (https://worldview.earthdata.nasa.gov) delivers this global, near-real time imagery through an interactive web map application. Provided through NASA’s Land Atmosphere Near real-time Capability for EOS (LANCE) (https://earthdata.nasa.gov/lance) via NASA’s Global Imagery Browse Services (GIBS) (https://earthdata.nasa.gov/gibs), the near real-time satellite imagery provides a launching point to discover where the latest wildfires, severe storms, volcanic eruptions, and calving ice shelves are happening. This poster will explore the newest near real-time satellite imagery and soon-to-be available imagery in Worldview, including imagery from geostationary satellites - GOES-East/West and Himawari-8. The poster will cover recent and future improvements to Worldview aimed to enhance the discovery and interaction with near real-time imagery and show how it is used by people from researchers, to meteorologists to the science-minded public around the world.

Wong, Min Minnie↗

NASA NTRSDate not supplied

Keeping Up With the Time(s): Advancing NASA’s Worldview to Facilitate Quick Access to Global Near Real-Time Imagery

Striving to keep up with the constantly changing environment, whether physical or computing, NASA Worldview’s interactive web mapping application continues to make improvements to ensure that avenues to near-real time imagery are quick, easy and accessible. This poster will explore recent additions to NASA Worldview and the Global Imagery Browse Services (GIBS) of near real-time imagery and imagery visualizations - from geostationary to flood mapping visualizations; improvements to access to imagery - from granule swath visualizations to vector interactions with fires and other types of vectors; and improvements to imagery discovery - from enhancements to the timeline to providing more ways to locate relevant imagery in the layer picker.

Min Minnie Wong↗

NASA NTRS2016

Improvements and Additions to NASA Near Real-Time Earth Imagery

For many years, the NASA Global Imagery Browse Services (GIBS) has worked closely with the Land, Atmosphere Near real-time Capability for EOS (Earth Observing System) (LANCE) system to provide near real-time imagery visualizations of AIRS (Atmospheric Infrared Sounder), MLS (Microwave Limb Sounder), MODIS (Moderate Resolution Imaging Spectrometer), OMI (Ozone Monitoring Instrument), and recently VIIRS (Visible Infrared Imaging Radiometer Suite) science parameters. These visualizations are readily available through standard web services and the NASA Worldview client. Access to near real-time imagery provides a critical capability to GIBS and Worldview users. GIBS continues to focus on improving its commitment to providing near real-time imagery for end-user applications. The focus of this presentation will be the following completed or planned GIBS system and imagery enhancements relating to near real-time imagery visualization.

near real time↗

NASA NTRS1973

Geological evaluation of remote sensing imagery of the Mesabi Range, Minnesota.

Remote sensing imagery of Precambrian sedimentary, metasedimentary, and intrusive rocks of the Mesabi Range, Minnesota area was analyzed to determine how much geologic information was inherent in each type of imagery. High altitude panchromatic photography, radar, ultraviolet, and day and night thermal infrared imagery were examined. Geologic sketch maps were produced for each type of imagery. Radar appears to be the best imagery for mapping rock units and for locating regional faults. Few rock units could be found on the infrared imagery or on the panchromatic photography. Several previously unmapped faults were located, and the surface traces of some faults were extended.

Walker, A. S.↗

NASA NTRS1973

Application of thermal imagery to the development of a Great Lakes ice information system

Recent measurements and analysis have shown that thermal infrared imagery (wavelength, 8-14 microns) can be employed to delineate the relative thicknesses of various regions of freshwater ice, as well as, differentiate new ice from both open water areas and thicker (young)ice. Thermal imagery was observed to be generally superior to visual (0.4 - 0.7 microns) and our SLAR (3.3 cm) imagery for estimating relative ice thicknesses and delineating open water from new ice growth. In a real-time Great Lakes Ice Information System, thermal imagery can not only provide supplementary imagery but also aid in developing interpretative methods for all-weather SLAR imagery, as well as, establishing the areal extent of spot thickness measurements.

Schertler, R. J.↗

NASA NTRS1973

Application of thermal imagery to the development of a Great Lakes ice information system

Recent measurements and analysis have shown that thermal infrared imagery can be employed to delineate the relative thicknesses of various regions of freshwater ice and to differentiate new ice from both open water areas and thicker (young) ice. Thermal imagery was observed to be generally superior to visual (0.4 - 0.7 micron) and SLAR (3.3 cm) imagery for estimating relative ice thicknesses and delineating open water from new ice growth. In a real-time Great Lakes ice information system, thermal imagery can not only provide supplementary imagery but can also aid in developing interpretative methods for all-weather SLAR imagery.

Schertler, R. J.↗

NASA NTRS1974

Use of ERTS-1 imagery in forest inventory

The utility of ERTS-1 imagery when combined with field observations and with aircraft imagery and field observations is evaluated. Satellite imagery consisted of 9-1/2 inch black and white negatives of four multispectral scanner bands taken over Polk County, Tennessee. Aircraft imagery was obtained by a C-130 flying at 23,000 ft over the same area and provided the basis for locating ground plots for field observations. Correspondence between aircraft and satellite imagery was somewhat inaccurate due to seasonal differences in observations and lack of good photogrammetry with the data processing system used. Better correspondence was found between satellite imagery and ground observations. Ways to obtain more accurate data are discussed, and comparisons between aircraft and satellite observations are tabulated.

Rennie, J. C.↗

NASA NTRS1975

Skylab imagery: Application to reservoir management in New England

The author has identified the following significant results. S190B imagery is superior to the LANDSAT imagery for land use mapping and is as useful for level 1 and 2 land use mapping as the RB-57/RC8 high altitude imagery. Detailed land use mapping at levels 3 and finer from satellite imagery requires better resolution. For evaluating factors that are required to determine volume runoff potentials in a watershed, the S190B imagery was found to be as useful as the RB-57/RC8 high altitude aircraft imagery.

Cooper, S.↗

NASA NTRS1980

Applications of radar imagery to arctic and subarctic problems

Radar imagery provides year around data acquisition of areas in the Arctic and the Subarctic. The foremost factor influencing the choice of radar imagery as the major data source was the demand for neotric data. The weather is so adverse in parts of Alaska that radar imagery was the only remote sensing technique which could meet the demand. The major map products derived from radar imagery are landform maps and lineament maps. These maps are used to make environmental assessments of areas and to reconstruct the geomorphic history of certain regions or features. Since radar imagery provides information about geologic structure and geomorphic features, it can be used to determine the relationship which exists between geologic structure and geomorphology. Important geologic information related to surface roughness can be obtained through a dry snow cover. Radar imagery is the only remote sensing technique which can provide information needed about sea ice through a cloud cover and dry snow, during strong wind conditions, and throughout the Arctic night.

Cannon, P. J.↗

NASA NTRS1981

Training site statistics from Landsat and Seasat satellite imagery registered to a common map base

Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.

Clark, J.↗

NASA NTRS1981

Utilization of Meteorological Satellite Imagery for World-Wide Environmental Monitoring the Lower Mississippi River Flood of 1979 - Case 1

The 1979 Lower Mississippi River flood was selected as a test case of environmental disaster monitoring utilizing NOAA-n imagery. A small scale study of the St. Louis Missouri area comparing ERTS-1 (LANDSAT) and NOAA-2 imagery and flood studies using only LANDSAT imagery for mapping the Rad River of the North, and Nimbus-5 imagery for East Australia show the nonmeteorological applications of NOAA satellites. While the level of NOAA-n imagery detail is not that of a LANDSAT image, for operational environmental monitoring users the NOAA-n imagery may provide acceptable linear resolution and spectral isolation.

Helfert, M. R.↗

NASA NTRS1982

LANDSAT imagery: Description of products available from the CSIR Satellite Remote Sensing Centre

An overview of the LANDSAT system is provided along with information to assist prospective users in establishing whether imagery for their areas of interest is available and how to obtain such imagery. Spectral bands, spatial resolution, and digital data are explained as well as worldwide reference system indexing and the identification number assigned to images. The sizes and scales of standard black and white imagery and of false color composite imagery are listed. The format is given for computer compatible tapes and standard enhanced imagery is described. Other information available to users include LANDSAT index maps, catalogs of available imagery, a schedule of overpass dates, and a list of product prices.

Source record↗

NASA NTRS2002

Ikonos Imagery Product Nonuniformity Assessment

During the early stages of the NASA Scientific Data Purchase (SDP) program, three approximately equal vertical stripes were observable in the IKONOS imagery of highly spatially uniform sites. Although these effects appeared to be less than a few percent of the mean signal, several investigators requested new imagery. Over time, Space Imaging updated its processing to minimize these artifacts. This however, produced differences in Space Imaging products derived from archive imagery processed at different times. Imagery processed before 2/22/01 is processed with one set of coefficients, while imagery processed after that date requires another set. Space Imaging produces its products from raw imagery, so changes in the ground processing over time can change the delivered digital number (DN) values, even for identical orders of a previously acquired scene. NASA Stennis initiated studies to investigate the magnitude and changes in these artifacts over the lifetime of the system and before and after processing updates.

Ryan, Robert↗

NASA NTRS2003

The Joint Agency Commercial Imagery Evaluation Team and Product Characterization Approach

The Joint Agency Commercial Imagery Evaluation (JACIE) team is a collaborative interagency group focused on the characterization of commercial remote sensing data products. The team members - the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA), and the U.S. Geological Survey (USGS) - each have a vested interest in the purchase and use of commercial imagery to support government research and operational applications. For both research and applications, commercial products must be well characterized for precision, accuracy, and repeatability. Since commercial systems are built and operated with no government insight or oversight, the JACIE team provides an independent product characterization of delivered image and image-derived end products. End product characterization differs from the systems calibration approach that is typically used with government systems, where detailed system design information is available. The product characterization approach addresses three primary areas of product performance: geopositional accuracy, image quality, and radiometric accuracy. The JACIE team utilizes well-characterized test sites to support characterization activities. To characterize geopositional accuracy, the team utilizes sites containing several "photo-identifiable" targets and compares their precisely known locations with those defined by the commercial image product. In the area of image quality, spatial response is characterized using edge targets and pulse targets to measure edge response and to estimate image modulation transfer function. Additionally, imagery is also characterized using the National Imagery Interpretability Rating Scale, a means of quantifying the ability to identify certain targets (e.g., rail-cars, airplanes) within an image product. Radiometric accuracy is characterized using reflectance-based vicarious calibration methods at several uniform sites. Each JACIE agency performs an aspect of product characterization based on its area of expertise, thus minimizing duplication of effort. The JACIE team collaborated to perform comprehensive characterization of products from Space Imaging Inc.'s IKONOS satellite and from DigitalGlobe's QuickBird satellite and is currently characterizing products from OrbImage s OrbView-3. JACIE assessments have resulted in several improvements to commercial image product quality and have enhanced working relationships between government and industry. Assessment results are presented at an annual JACIE High Spatial Resolution Commercial Imagery Workshop.

Zanoni, Vicki↗