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NASA NTRSDate not supplied

Publishing Variables Archived at GES DISC to Earth System Grid Federation (ESGF)

We present a straightforward and low-cost approach to publish variables archived at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) to the Earth System Grid Federation (ESGF). An ESGF publication requires a single standard-name variable aggregated over time to facilitate data inter-comparison. It also contains significant metadata to enable searching in ESGF. We look up standard names on high demand in ESGF search history, and using OPeNDAP and NcML technologies we aggregate the corresponding variables available in the GES DISC archive with augmented metadata required by CMIP6 and obs4MIPs Data Specification version 2.1. At this writing 10 variables from a standard product of the Atmospheric Infrared Sounder along with the Tech Notes are published in ESGF by NASA Center for Climate Simulation (NCCS). Users can view, analyze, and subset remotely, and download these aggregated variables via links in any ESGF node after searching. We plan to work on and publish more variables and data from different NASA missions and experiments in our archive.

Fan Fang↗
NASA NTRS2019

Far-infrared room-temperature focal plane modules for polar radiant energy in the Far InfraRed experiment

This work presents focal plane modules for Polar Radiant Energy in the Far InfraRed Experiment, a passive remote-sensing instrument aimed to determine errors in the estimated outgoing longwave radiation in the Earth’s polar regions to reduce uncertainties in surface emissivity, mass balance, and ice flux. The focal plane arrays are micromachined at JPL and integrated into sub-assembly modules to be mounted on the optical telescope of the instrument.

White, Mary↗
DOE OSTI2026

CHESS 2025: Leaf Area Index (LAI) for meadow, shrub, tree, and understory vegetation

This dataset contains Leaf Area Index (LAI) measurements made as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Data were collected in the Upper Gunnison Basin, Colorado, across three study domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). Field observations of LAI were collected within 72 hours of airborne data collection by the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. LAI measurements were collected using the LICOR LAI-2200C Plant Canopy Analyzer following protocols outlined in the instrument manual (LI-COR 2019). Sampling targeted four distinct vegetation types: meadows, shrubs, trees, and aspen forest understory. We have archived data separately by site type because different field methods were used for each. At meadow sites, measurements were made at the four corners of 1m x 1m plots, with the instrument moving inward toward the center of the plot. At shrub sites, we measured the canopies of individual shrubs. At tree sites, we made measurements within a 10m x 10m subplot centered around a focal tree, with 30 observations taken on a regular grid. At aspen understory sites, we measured overstory trees following the tree protocol and understory herbaceous vegetation following the meadow protocol. All measurements included above-canopy (A) and below-canopy (B) readings, with specific protocols for scattering correction measurements in direct-sun conditions. Data were processed using the R package `rlai` (Worsham 2025). This package includes functions to calculate LAI, gap fraction, apparent clumping factor (Ω), scattering correction, and other canopy metrics. Package contents: Full file descriptions appear in ‘flmd.csv’. Files named according to the convention ‘lai_*_summary_data_cleaned.csv’ contain summary values of LAI, apparent clumping factor (Ωapp), and scattering correction factors for each site. These are the analysis-ready products that most data users will work with. Files named ‘lai_*_metadata_cleaned.csv’ contain additional site-level observations made during field collection. We have also archived intermediate and supplementary data for users who wish to check our processing approach or apply alternative methods. ‘raw_lai_2200C.zip’ contains the raw files as read from the LI-COR instrument, with no processing applied, in TXT format. The zip archive contains subdirectories by site type, which are further subdivided by sampling area. Filenames correspond to the sampling site number. ‘intermediate_results.zip’ contains detailed output from the processing routines, in JSON format. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘scattering_correction_logs.zip’ contains logfiles from the implementation of Kobayashi et al.'s (2013) scattering correction algorithm. The logfiles report values of several parameters at each iteration of the algorithm, as the model converges toward a stable solution. They are intended for users who want to verify scattering correction performance. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘spot_checks.csv’ reports LAI and other values for a small number of files processed with LI-COR FV2200 software (LI-COR 2013) using the same control parameters as in our R-based approach. Additional metadata are provided in a data dictionary describing column names and definitions (dd.csv), and in a file-level metadata file (flmd.csv). All zip files can be expanded with common archive utilities. TXT, CSV, and JSON files can be ingested into R or Python computing environments or read in common text editor utilities. Geospatial information: Geospatial data for mapping measurement site locations are in the files CHESS_polygons_lai_UTM.geojson, CHESS_polygons_shrub_UTM.geojson, and CHESS_polygons_meadow_UTM.geojson in the companion geospatial package for the 2025 CHESS campaign, ‘CHESS 2025: Location data for field observations and sampling’ (Henderson et al., 2026). 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. * Todorov and Worsham are co–first authors.

2018 NEON and 2025 CHESS Campaigns↗
NASA NTRS1991

Virtual reality at work

The utility of virtual reality computer graphics in telepresence applications is not hard to grasp and promises to be great. When the virtual world is entirely synthetic, as opposed to real but remote, the utility is harder to establish. Vehicle simulators for aircraft, vessels, and motor vehicles are proving their worth every day. Entertainment applications such as Disney World's StarTours are technologically elegant, good fun, and economically viable. Nevertheless, some of us have no real desire to spend our lifework serving the entertainment craze of our sick culture; we want to see this exciting technology put to work in medicine and science. The topics covered include the following: testing a force display for scientific visualization -- molecular docking; and testing a head-mounted display for scientific and medical visualization.

Brooks, Frederick P., Jr.↗
NASA NTRS1997

Remote Sensing Applications for Antrim Shale Fracture Characterization, Michigan Basin

Advanced Research International (ARI) sent seven staff members to the 1997 International Coalbed Methane Symposium, held in Tuscaloosa, Alabama from May 12-17. ARI gave a short course on risk reduction strategies, including remote fracture detection, for coalbed methane exploration and development that was attended by about 25 coalbed methane industry professionals; and presented a paper entitled 'Optimizing coalbed methane cavity completion operations with the application of a new discrete element model.' We met with many potential clients and discussed our fracture detection services. China has vast coalbed methane resources, but is still highly dependent on coal-and wood-burning. This workshop, sponsored by the United Nations, was intended to help China develop its less-polluting energy reserves. ARI is successfully finding new applications for its fracture detection services. Coalbed methane exploration became an important market in this quarter, with the inception of a joint industry/government collaboration between ARI, Texaco and DOE to use remote fracture detection to identify areas with good potential for coalbed methane production in the Ferron Coal Trend of central Utah. Geothermal energy exploration is another emerging market for ARI, where fracture detection is applied to identify pathways for groundwater recharge, movement, and the locations of potential geothermal reservoirs. Ari continued work on two industry/government collaborations to demonstrate fracture detection to potential clients. Also completed the technical content layout for multimedia CD-ROM that describes our remote fracture detection services.

Kuuskraa, Vello↗
DOE OSTI2023

Disrupting EV Charging Sessions and Gaining Remote Code Execution with DoS, MITM, and Code Injection Exploits using OCPP 1.6

Open Charge Point Protocol (OCPP) 1.6 is widely used in the electric vehicle (EV) charging industry to communicate between Charging System Management Services (CSMSs) and Electric Vehicle Supply Equipment (EVSE). Unlike OCPP 2.0.1, OCPP 1.6 uses unencrypted websocket communications to exchange information between EVSE devices and an onpremise or cloud-based CSMS. In this work, we demonstrate two machine-in-the-middle (MITM) attacks on OCPP sessions to terminate charging sessions and gain root access to the EVSE equipment via remote code execution (RCE). Second, we demonstrate a malicious firmware update with a code injection payload to compromise an EVSE. Lastly, we demonstrate two methods to prevent availability of the EVSE or CSMS. One of these, originally reported by SaiFlow, prevents traffic to legitimate EVSE equipment using a DoS-like attack on CSMSs by repeatedly connecting and authenticating several CPs with the same identities as the legitimate CP. These vulnerabilities were demonstrated with proof-of-concept exploits in a virtualized Cyber Range at Wright State University and/or with a 350 kW Direct Current Fast Charger (DCFC) at Idaho National Laboratory. The team found that OCPP 1.6 could be protected from these attacks by adding secure shell (SSH) tunnels to the protocol, if upgrading to OCPP 2.0.1 was not an option. Index Terms—Electric vehicle charging, cybersecurity, OCPP, cyberattack, cyber-resilience. INSPEC Accession Number: 23981565

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1981

VTOL as it applies to resource development in the Canadian north

It is pointed out that, for many of the natural resource development projects planned in Canada between now and the end of the century, it may be necessary for the work force to commute to the site by air. Examples of successful operations, including those involving VTOL, are given. A computer program developed for determining the least expensive type of aircraft for commuting to remote projects is described. It is noted that the program can select both fixed-wing and helicopter aircraft types for a specific project, employing such variables as the size and shift schedules of the work force and the commuting distance. Capital and operating costs of existing and proposed aircraft types, as well as groundside infrastructure operations and maintenance costs, are compared for competing aircraft.

Lightfoot, R. N.↗
NASA NTRS2017

Non-Classical Stress Concentration Behavior in a Radically Stretched Hyperelastic Sheet Containing a Circular Hole

Non-classical stress concentration behavior in a stretched circular hyperelastic sheet (outer radius b = 10 in., thickness t = 0.0625 in.) containing a central hole (radius a = 0.5 in.) was analyzed. The hyperelastic sheet was subjected to different levels of remote radial stretchings. Nastran large-strain large-deformation analysis and the Blatz-Ko large deformation theory were used to calculate the equal-biaxial stress concentration factors K. The results show that the values of K calculated from the Blatz-Ko theory and Nastran are extremely close. Unlike the classical linear elasticity theory, which gives the constant K = 2 for the equal-biaxial stress field, the hyperelastic K values were found to increase with increased stretching and can exceed the value K = 6 at a remote radial extension ratio of 2.35. The present K-values compare fairly well with the K-values obtained by previous works. The effect of the hole-size on K-values was investigated. The values of K start to decrease from a hole radius a = 0.125 in. down to K = 1 (no stress concentration) as a shrinks to a = 0 in. (no hole). Also, the newly introduced stretch and strain magnification factors {K(sub λ),K(sub ε) } are also material- and deformation-dependent, and can increase from linear levels of {1.0, 4.0} and reaching {3.07, 4.61}, respectively at a remote radial extension ratio of 2.35.

stress concentration↗
NASA NTRS2018

GEONEX: Challenges in Producing MODIS-Like Land Products from a New Generation of Geostationary Sensors

The new generation geostationary (GEO) remote sensors (GOES-R ABI, Himawari AHI, and FY4 AGRI) provide high frequency (5-15 minute) observations spatially/spectrally similar to MODIS/VIIRS for land monitoring. These new features of GEO satellite sensors make producing MODIS like land products for terrestrial monitoring possible. The NASA Earth Exchange (NEX) team developed the GEONEX pipeline that is containerized, deployable on NASA Pleiades supercomputer as well as public cloud platforms (e.g. AWS). The processing pipeline is designed to take Himawari Standard Data (HSD) and GOES-16 L1b to generate surface reflectance (SR) and other high-level land remote sensing products. In order to produce low-Earth-orbiting (LEO) remote sensing compatible land products, inter-comparison between Himawari AHI and MODIS Terra/Aqua has been conducted in this research work. Comparisons of TOA reflectance and surface reflectance between AHI and Terra/Aqua are presented. Ray-Matching method was used to locate the co-located pixels, where GEO and LEO sensors look at the land target with similar Viewing Zenith Angle (VZA) and Viewing Azimuth Angle (VAA) simultaneously. Here, we address challenges associated with the selection of qualified pixels of similar solar illumination condition and atmosphere path. We used strict criterion to constrain the pixel selection: the time difference between GEO and LEO observations is less than +-2.5 mins, the cosine of VZA difference is less than 1%, and the VAA difference is less than 10 deg. We also discuss the strong radiometric consistency that the new generation GEO sensors along with the popular LEO sensors would benefit the environmental remote sensing community.

Li, Shuang↗
NASA NTRS2015

Earth Science Informatics - Overview

Over the last 10-15 years, significant advances have been made in information management, there are an increasing number of individuals entering the field of information management as it applies to Geoscience and Remote Sensing data, and the field of informatics has come to its own. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of science data, information, and knowledge. Informatics also includes the use of computers and computational methods to support decision making and applications. Earth Science Informatics (ESI, a.k.a. geoinformatics) is the application of informatics in the Earth science domain. ESI is a rapidly developing discipline integrating computer science, information science, and Earth science. Major national and international research and infrastructure projects in ESI have been carried out or are on-going. Notable among these are: the Global Earth Observation System of Systems (GEOSS), the European Commissions INSPIRE, the U.S. NSDI and Geospatial One-Stop, the NASA EOSDIS, and the NSF DataONE, EarthCube and Cyberinfrastructure for Geoinformatics. More than 18 departments and agencies in the U.S. federal government have been active in Earth science informatics. All major space agencies in the world, have been involved in ESI research and application activities. In the United States, the Federation of Earth Science Information Partners (ESIP), whose membership includes nearly 150 organizations (government, academic and commercial) dedicated to managing, delivering and applying Earth science data, has been working on many ESI topics since 1998. The Committee on Earth Observation Satellites (CEOS)s Working Group on Information Systems and Services (WGISS) has been actively coordinating the ESI activities among the space agencies. Remote Sensing; Earth Science Informatics, Data Systems; Data Services; Metadata

Remote Sensing; Earth Science Informatics↗
NASA NTRS2006

Use of In Situ Cloud Condensation Nuclei, Extinction, and Aerosol Size Distribution Measurements to Test a Method for Retrieving Cloud Condensation Nuclei Profiles From Surface Measurements

If the aerosol composition and size distribution below cloud are uniform, the vertical profile of cloud condensation nuclei (CCN) concentration can be retrieved entirely from surface measurements of CCN concentration and particle humidification function and surface-based retrievals of relative humidity and aerosol extinction or backscatter. This provides the potential for long-term measurements of CCN concentrations near cloud base. We have used a combination of aircraft, surface in situ, and surface remote sensing measurements to test various aspects of the retrieval scheme. Our analysis leads us to the following conclusions. The retrieval works better for supersaturations of 0.1% than for 1% because CCN concentrations at 0.1% are controlled by the same particles that control extinction and backscatter. If in situ measurements of extinction are used, the retrieval explains a majority of the CCN variance at high supersaturation for at least two and perhaps five of the eight flights examined. The retrieval of the vertical profile of the humidification factor is not the major limitation of the CCN retrieval scheme. Vertical structure in the aerosol size distribution and composition is the dominant source of error in the CCN retrieval, but this vertical structure is difficult to measure from remote sensing at visible wavelengths.

Ghan, Stephen J.↗
NASA NTRS1982

Remote Sensing Applications to the Pennsylvania Abandoned Mine Reclamation Program

Pennsylvania Abandoned Mine Land Inventory demonstrated the effective use of remote sensing techniques within the context of the Surface Mining Control and Reclamation Act of 1977. The inventory combined data from field work, a literature search, and photointerpretation to fulfill both State and Federal requirements. A primary project objective was to accurately identify and map all surface features and disturbances from abandoned surface and underground mining. Black-and-white aerial photographs were used to record pits, contour benches, highwalls, spoil material, graded and recontoured areas, impounded water, and serious erosion and slide prone areas. In addition, vegetation cover estimates and surrounding land uses were noted. The inventory data base provides Pennsylvania with a valuable resource management tool that should be systematically updated. The utilization of remotely sensed data from SPOT or LANDSAT-D satellites may prove valuable in the anticipated updating and monitoring of the Pennsylvania AML inventory over the next several years.

Clemens, E.↗
NASA NTRS2004

Balanced Expertise Distribution in Remote Ultrasound Imaging Aboard The International Space Station (ISS)

Astronaut training for ISS operations usually ensures independent performance. With small crew size same crews also conduct all science work onboard. With diverse backgrounds, a good "match" between the existing and required skills can only be anecdotal. Furthermore, full proficiency in most of the complex tasks can be attained only through long training and practice, which may not be justified and may be impossible given the scarcity of training time. To enable a number of operational and science advancements, authors have developed a new approach to expertise distribution in time and among the space and ground personnel. Methods: As part of NASA Operational Ultrasound Project (1998-2003) and the NASA-solicited experiment "Advanced Diagnostic Ultrasound in Microgravity-ADUM" (P.I. -S.D., ongoing), the authors have created a "Balanced Expertise Distribution" approach to perform complex ultrasound imaging tasks on ISS for both operational and science use. The four components of expertise are a) any pre-existing pertinent expertise; b) limited preflight training c) adaptive onboard proficiency enhancement tools; d) real-time ' guidance from the ground. Throughout the pre-flight training and flight time preceding the experiments, the four components are shaped in a dynamic fashion to meet in an optimum combination during the experiment sessions. Results: Procedure validation sessions and feasibility studies have given encouraging results. While several successful real-time remote guidance sessions have been conducted on ISS, Expedition 8 is the first to use an "on-orbit proficiency enhancement" tool. Conclusions: In spite of severely limited training time, daring peer-reviewed research and operational enhancements are feasible through a balanced distribution of expertise in time, as well as among the crewmembers and ground personnel. This approach shows great promise for biomedical research, but may be applicable for other areas of micro gravity-based science

Sargsyan, Ashot↗
DOE OSTI2024

Power Supply Options for the Marpi Landfill, Saipan: Comprehensive Feasibility Study

The Marpi Landfill (“Marpi” or “the landfill”), located on the northern end of the island of Saipan in the Commonwealth of the Northern Mariana Islands (CNMI), is powered by a single on-site diesel generator that only operates when the landfill is open and staffed. The project team, composed of representatives of the Department of Public Works and the Office of Planning and Development (OPD), aspires to provide the Marpi Landfill with 24-hour power availability despite its remote location to increase the use of sustainable energy and to ensure environmentally compliant landfill operations. This is consistent with the sustainable development goals documented in the 2021–2030 Comprehensive Sustainable Development Plan (OPD 2021), including Goal #12 (ensure environmentally compliant waste management facilities) and Goal #7 (renewable energy deployment). Further, the CNMI has a 20% target for renewable energy consumption by 2030, as documented in the 2021–2030 Comprehensive Sustainable Development Plan (OPD 2021) and the renewable portfolio standard (Public Law 18-62). To accomplish these goals, the Federal Emergency Management Agency, through its Interagency Reimbursable Work Agreement with the U.S. Department of Energy, funded a feasibility study and follow-up study in 2023–2024 to assess and prioritize power supply options for the landfill. This report combines the results from both feasibility studies.

14 SOLAR ENERGY↗
DOE OSTI2020

Automated, Unmanned Detection and Quantification of Fugitive Methane Emissions

Compressor stations used to move natural gas are one of the largest sources of fugitive methane emissions in the midstream sector, accounting for approximately 50% of all fugitive emissions (Zimmerle et al., 2015). This problem is most widespread at reciprocating compressors (Subramanian et al., 2015) where faulty seals are a key contributor to methane emissions (Johnson et al., 2015). As such, there is a significant need for a robust technology that could provide an early indication of an unexpected emission. Equally important, the technology needs to be able to account for biogenic versus anthropogenic sources of methane. One means of indirectly making this determination, is to leverage optical technologies that can autonomously pinpoint the source of such leaks. This presentation discusses recent work funded by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), focused on the development of an innovative remote sensing technology that can reliably and autonomously detect fugitive methane emissions in near real-time, using computer vision and deep learning. The technology called the Smart Methane Leak Detection (SLED/M) system was initially developed to monitor facilities such as compressor stations in a stationary, pan-tilt-zoom configuration. The system has recently been adapted to monitor facilities from an unmanned aerial system (UAS). The speed and maneuverability of UAS platforms are attractive to leak detection and repair program operators, but introduce several challenges. Many existing methane detection algorithms rely on mostly static backgrounds becoming unusable with motion. In addition, top-down views of fugitive methane emissions present differently in Optical Gas Imagers (OGI) compared to looking across the plume. Our work has focused on overcoming these challenges, enhancing the operators ability to detect methane emissions, and pinpoint their sources. Another recent adaptation to SLED/M is the ability to quantify methane emissions using passive sensors (OGI, thermal camera), environmental conditions, plume modeling, and deep learning. SLED/M advances the state-of-the-art for methane emission detection and quantification by focusing on three key critical criteria for effective methane emission mitigation: (1) autonomy (no need for a human to be in the loop), (2) high reliability (low false alarm rates), and (3) real-time performance. Results from this work will be presented.

03 NATURAL GAS↗
DOE OSTI2021

Optimizing the surface distribution of acid sites for cooperative catalysis in condensation reactions promoted by water

Addition of small amounts of water to the organic solvent may result in different promoting or inhibiting effects in aldol condensation reactions depending on the distribution of active sites on the surface. In a combination of liquid-phase catalytic activity measurements, spectroscopies and theoretical calculations, we have shown that water clusters around the acid site can form bridges with a ketone molecule located close to the activated carbonyl, on another site. When the distance between the two acid sites is greater than a distance corresponding to about 2 water molecules, the efficiency of the bond polarization of the ketone by a remotely located acid site decreases significantly, and the presence of water no longer promotes the reaction. Furthermore, this work provides a quantitative assessment of how solvent molecules can bridge isolated active sites to enable cooperative catalysis, which offers an additional dimension for engineering catalysis at the nanoscale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

CHESS 2025: Field-collected vegetation attributes and site photos

This dataset represents field observations of vegetation samples collected as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Samples were collected in the field using tablet computers and digital forms, with target data differing by sample type (individual trees, individual shrubs, or 1-meter square plots of meadow and subshrub vegetation). Field samples were collected within 72 hours of airborne data collection using the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. Remote sensing data for the project is available on ESS-DIVE (DOI and citation to be added upon publication). Field data collected included canopy height and per-species horizontal proportional cover for meadow plots, species identity and height information for shrubs, as well as species identity, height, diameter at breast height, and health assessment information for trees. Photos of the focal site and surrounding landscape were taken for all sampling sites and are included in this archive. Green leaves or needles were collected for plant trait and foliar chemistry analysis. This data is archived separately (DOI and citation to be added upon publication). High-precision geospatial data for each sample (crown perimeter polygons for trees and shrubs, plot boundaries for meadow plots) is available here (Henderson et al., 2026). Field and remote sensing protocols largely followed those of a previous field and airborne imaging campaign performed in 2018 (described in Chadwick et al. 2020). Field data from the 2018 campaign can be found here (Chadwick et al., 2020 doi:10.15485/1618130). Because different field measurements were taken for meadow, shrub, and tree sites, data from these three sample types are archived as separate tables (chess_meadow_site_cleaned.csv, chess_shrub_site_cleaned.csv, chess_tree_site_cleaned.csv). Meadow proportional cover data is stored in a separate table (chess_meadow_cover_cleaned.csv). Taxonomy was treated identically between sample types, and the dataset shares a common set of voucher specimens (chess_voucher_IDs_cleaned.csv), as well as a single species list (chess_species_list_cleaned.csv). All taxonomic determinations were performed to the species level, and adhere to the Global Biodiversity Information Facility (GBIF) backbone taxonomy as of January 10th, 2026 (GBIF Secretariat 2023). 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 Acknowledgment: 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 OSTI2026

CHESS 2025: Spectrometer orthorectified at-sensor radiance from NEON AOP imaging spectroscopy surveys

This dataset provides Level 1 (L1) orthorectified at-sensor radiance derived from measurements collected by the Imaging Spectrometer-1 (NIS-1) onboard the NEON (National Ecological Observatory Network) Airborne Observation Platform (AOP) for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). NIS-1 captures light reflected from the Earth’s surface in 426 discrete wavelength bands as raw digital numbers (DNs; Level 0). These data are then calibrated to physical units (uW/cm²·sr·nm) following the processing steps described in the NEON Imaging Spectrometer Level 1B Calibrated Radiance Algorithm Theoretical Basis Document (ATBD; Gallery 2022). The data delivered here are the primary inputs for the surface reflectance product in “Custom surface reflectance, shade masks, and equivalent water thickness maps for the Colorado Headwaters Ecological Spectroscopy Study” (Carroll et al. 2026). For intertemporal comparison, the radiance data here are most directly relatable to the v2 radiance data in “NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset” (Goulden et al. 2018), to which the same processing methodology was applied. Together, the radiance and reflectance data enable users to exploit the unique reflection signatures of different surface objects for land cover classification, foliar trait mapping, plant vigor assessment, water content estimation, trace-element identification, and other scientific applications. 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. Within each domain, data are delivered by flightline as orthorectified and calibrated hyperspectral rasters in Hierarchical Data Format version 5 (HDF5) format, with radiance values provided in uW/cm²·sr·nm on a fixed, uniform Universal Transverse Mercator (UTM) grid at 1 meter spatial resolution. The radiance rasters include all 426 NIS-1 spectral bands, along with associated quality-assurance (QA) and diagnostic and ancillary layers needed for atmospheric correction workflows. Orthorectified radiance is produced from pushbroom spectrometer observations by applying NEON’s radiometric calibration (including bad pixel masking, dark subtract, dark pedestal shift correction, electronic panel ghost correction, grating ghost correction, deblur correction and flat-fielding) and spectral calibration (using spectral response function band centers and full-width at half-maximum intensity), followed by geolocation and regridding to the fixed grid. 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↗