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NASA NTRS2020

Great Lakes Water Resources II: A Google Earth Engine Tool to Automate Wetland Extent Mapping Using Optical and Radar Satellite Sensors in the Great Lakes Basin for Wetland Management and Monitoring

The Great Lakes Basin is one of the world’s largest freshwater ecosystems. The Basin harbors over 200,000 acres of wetlands that provide a variety of environmental, ecological, and recreational functions to over 30 million people in the region. Some of these functions include improving water quality, mitigating flood impacts, providing wildlife habitat, and housing recreational activities. However, due to anthropogenic activities, habitat conversion and degradation threaten to disrupt or destroy remaining wetland ecosystems. Maps of wetland distribution based on ground surveys are costly and labor-intensive, prohibiting timely evaluations of wetland loss and gain. The Great Lakes Water Resources II team at the NASA Jet Propulsion Laboratory developed the Wetlands Extent Tool 2.0 (WET 2.0) in Google Earth Engine to automate mapping of wetland distribution in the Great Lakes Basin. The team partnered with the US Fish and Wildlife Service, Environmental Protection Agency, Minnesota Department of Natural Resources, the National Oceanic and Atmospheric Administration, and Ducks Unlimited. WET 2.0 incorporates Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI) data. Utilizing a Random Forest classifier, WET 2.0 is capable of automatically mapping wetland extent in the entire Great Lakes Basin, achieving a mean overall accuracy of 80.12% when tested in Michigan.Findings and maps produced by WET 2.0 will enable our partners to identify areas of ecosystem degradation and wetland destruction in order to enact environmental practices and policy initiatives to maintain environmental and economic health in the area.

Water Resources↗

NASA NTRS2020

Mapping the Predicted Solar Wind Hydrogen Flux in Lunar South Pole Craters

The solar wind hydrogen flux is mapped onto the topography of four lunar south pole craters; Shackleton, Haworth, Shoemaker and Faustini. Using altimetry data from the Lunar Reconnaissance Orbiter, we apply an analytic plasma model to map the hydrogen flux onto the surface, time-averaged over a lunar rotation cycle. We present a series of maps including the average flux, geomagnetic modulation, and ion flow energy. These results are intended to inform further studies of dynamic lunar surface processes, such as volatile implantation, sputtering,and weathering. As an example, we also present a map of a surface ice sheet lifetime based on ion sputtering.

William M Farrell↗

NASA NTRS2021

Spectrophotometric Modeling and Mapping of (101955) Bennu

Using hyperspectral data collected by OVIRS, the visible and infrared spectrometer onboard the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer) spacecraft, we modeled the global average spectrophotometric properties of the carbonaceous asteroid (101955) Bennu and mapped their variations. We restricted our analysis to 0.4–2.5 µm to avoid the wavelengths where thermal emission from the asteroid dominates (>2.5 µm). Bennu has global photometric properties typical of dark asteroids; we found a geometric albedo of 0.046 ± 0.007 and a linear phase slope of 0.024 ± 0.007 mag deg–1 at 0.55 µm. The average spectral slope of Bennu’s normal albedo is –0.0030 µm–1, and the phase reddening parameter is 4.3´10–4 µm–1 deg–1, both over the spectral range of 0.5–2.0 µm. We produced normal albedo maps and phase slope maps at all spectral channels, from which we derived spectral slope and phase reddening maps. Correlation analysis suggests that phase slope variations on Bennu are likely due to photometric roughness variation. A correlation between photometric roughness and thermal roughness is evident, implying that the roughness of Bennu is self-similar on scales from tens of microns to meters. Our analysis reveals latitudinal trends in the spectral color slope and phase reddening on Bennu. The equatorial region appears to be redder than the global average, and the spectral slope decreases towards higher latitudes. Phase reddening on Bennu is relatively weak in the equatorial region and shows an asymmetry between the northern and southern hemispheres. We attributed the latitudinal trend to the geophysical conditions on Bennu that result in a global pattern of mass flow towards the equator.

Jian-Yang Li (李荐扬)↗

NASA NTRS2021

Experiment for Cryogenic Large-Aperture Intensity Mapping: Instrument Design

The EXperiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) is a balloon-borne tele-33scope designed to survey star formation in windows from the present to z=3.5. During this time, the rate of star34formation dropped dramatically, while dark matter continued to cluster. EXCLAIM maps the redshifted emission35of singly-ionized carbon lines and carbon monoxide using intensity mapping, which permits a blind and complete36survey of emitting gas through statistics of cumulative brightness fluctuations. EXCLAIM achieves high sensitivity37using a cryogenic telescope coupled to six integrated spectrometers employing kinetic inductance detectors covering38420540GHz with spectral resolving power R=512and angular resolution⇡40. The spectral resolving power and39cryogenic telescope allow the survey to access dark windows in the spectrum of emission from the upper atmosphere.40EXCLAIM will survey305 deg2in the Sloan Digital Sky Survey Stripe 82 field from a conventional balloon flight41in 2023. EXCLAIM will also map several galactic fields to study carbon monoxide and neutral carbon emission as42tracers of molecular gas. Here, we summarize the design phase of the mission.

Eric R Switzer↗

NASA NTRSDate not supplied

Building Maps for Terrain Relative Navigation Using Blender: An Open-Source Approach

A persistent challenge for vision-based navigation systems that compare imagery to a reference map is generating high quality maps with similar lighting conditions. Image rendering software can be used to apply variable lighting to reference maps or to generate synthetic imagery for test trajectories. While many image rendering software packages are available, with several developed specifically for spaceflight applications, there are often limitations due to cost, image fidelity, or flexibility. In this paper, we demonstrate the use of an open-source image rendering software, Blender, for use in Terrain Relative Navigation (TRN) applications. A scene in Blender was generated based on elevation data and satellite imagery of the region of West Texas used by Blue Origin for the operation of their New Shepard suborbital rocket. The Blender scene was validated by reproducing imagery collected during a flight of New Shepard in October 2020 and was further used to generate reference maps for use by a TRN algorithm on a subsequent New Shepard flight in August 2021. The work was performed under the NASA Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project, which is focused on technology advancement for precision landing and hazard avoidance. This work aims to lower the cost of entry and generally promote the adoption and advancement of vision-based navigation technologies.

Kyle W Smith↗

NASA NTRSDate not supplied

The NASA Earth Science Applied Sciences Disasters Program: Making EO Data and Expertise Available through the Disasters Mapping Portal to Inform Decision-Makers throughout the Disaster Cycle

The NASA Earth Science Applied Sciences Disasters Program promotes the use of Earth Observations (EO) to inform disaster risk reduction and resilience throughout the disaster cycle, from local to global scales, by harnessing NASA science and technology capabilities, through engagement with end users to demonstrate the value and impact of EO to support decision-making, and by supporting end users in their use of EO in decision-making while developing relationships to grow as a trusted source of relevant science and useful results. Through the NASA Earth Science Applied Sciences Disasters Program Mapping Portal, an Esri-backed hub of geospatially enabled disaster products, event-based and near-real-time products are hosted to provide end users with analysis-ready data and data services, keeping in mind their expressed EO needs. In this presentation, case studies of past events will be highlighted, showcasing how EO data and services were provided by the Program and utilized by end users during the disaster cycle. Additionally, this presentation will highlight some of the Program’s ongoing collaboration activities to assist end users in understanding and preparing for utilization of EO data from the Mapping Portal to inform their decision-making throughout the disaster cycle. Ongoing efforts to advance the science provided by the Program on the Mapping Portal through new developments and capabilities will be highlighted, and common challenges and data needs end users often encounter when using EO data and our Program’s innovative solutions to these challenges will be addressed. Furthermore, this presentation will touch on the challenges faced and the solutions created by the Mapping Portal team in managing and hosting a plethora of EO data for end users across various disciplines.

Ronan Lucey↗

NASA NTRS2021

Exploring Sentinel-1 and Sentinel-2 diversity for Flood inundation mapping using deep learning

Identification of flood water extent from satellite images has historically relied on either synthetic aperture radar (SAR) or multi-spectral (MS) imagery. MS sensors are limited to cloud free conditions, whereas SAR imagery is plagued by noise-like speckle. Prior studies that use combinations of MS and SAR data to overcome individual limitations of these sensors have not fully examined sensitivity of flood mapping performance to different combinations of SAR and MS derived spectral indices or band transformations in color space. This study explores the use of diverse bands of Sentinel 2 (S2) through well-established water indices and Sentinel 1 (S1) derived SAR imagery along with their combinations to assess their capability for generating accurate flood inundation maps. The robustness in performance of S-1 and S-2 band combinations was evaluated using 446 hand labeled flood inundation images spanning across 11 flood events from Sen1Floods11 dataset which are highly diverse in terms of land cover as well as location. A modified K-fold cross validation approach is used to evaluate the performance of 32 combinations of S1 and S2 bands using a fully connected deep convolutional neural network known as U-Net. Our results indicated that usage of elevation information has improved the capability of S1 imagery to produce more accurate flood inundation maps. Compared to a median F1 score of 0.62 when using only S1 bands, the combined use of S1 and elevation information led to an improved median F1 score of 0.73. Water extraction indices based on S2 bands have a statistically significant superior performance in comparison to S1. Among all the band combinations, HSV (Hue, Saturation, Value) transformation of S2 bands provides a median F1 score of 0.9, outperforming the commonly used water spectral indices owing to HSV’s transformation’s superior contrast distinguishing abilities. Additionally, U-Net algorithm was able to learn the relationship between raw S2 based water extraction indices and their corresponding raw S2 bands, but not of HSV owing to relatively complex computation involved in the latter. Results of the paper establishes important benchmarks for the extension of S1 and S2 data-based flood inundation mapping efforts over large spatial extents.

Goutam Konapala↗

NASA NTRS2022

An Empirical Algorithm to Map Perennial Firn Aquifers and Ice Slabs Within the Greenland Ice Sheet Using Satellite L-band Microwave Radiometry

Perennial firn aquifers are subsurface meltwater reservoirs consisting of a meters-thick water-saturated firn layer that can form on spatial scales as large as tens of kilometers. They have been observed within the percolation facies of glaciated regions experiencing intense seasonal surface melting and high snow accumulation. Widespread perennial firn aquifers have been identified within the Greenland Ice Sheet (GrIS) via field expeditions, airborne ice-penetrating radar surveys, and satellite microwave sensors. In contrast, ice slabs are nearly continuous ice layers that can also form on spatial scales as large as tens of kilometers as a result of surface and subsurface water-saturated snow and firn layers sequentially refreezing following multiple melting seasons. They have been observed within the percolation facies of glaciated regions experiencing intense seasonal surface melting but in areas where snow accumulation is at least 25 % lower as compared to perennial firn aquifer areas. Widespread ice slabs have recently been identified within the GrIS via field expeditions and airborne ice-penetrating radar surveys, specifically in areas where perennial firn aquifers typically do not form. However, ice slabs have yet to be identified from space. Together, these two ice sheet features represent distinct, but related, sub-facies within the broader percolation facies of the GrIS that can be defined primarily by differences in snow accumulation, which influences the englacial hydrology and thermal characteristics of firn layers at depth. Here, for the first time, we use enhanced-resolution vertically polarized L-band brightness temperature () imagery (2015–2019) generated using observations collected over the GrIS by NASA's Soil Moisture Active Passive (SMAP) satellite to map perennial firn aquifer and ice slab areas together as a continuous englacial hydrological system. We use an empirical algorithm previously developed to map the extent of Greenland's perennial firn aquifers via fitting exponentially decreasing temporal L-band signatures to a set of sigmoidal curves. This algorithm is recalibrated to also map the extent of ice slab areas using airborne ice-penetrating radar surveys collected by NASA's Operation IceBridge (OIB) campaigns (2010–2017). Our SMAP-derived maps show that between 2015 and 2019, perennial firn aquifer areas extended over 64 000 km2, and ice slab areas extended over 76 000 km2. Combined together, these sub-facies are the equivalent of 24 % of the percolation facies of the GrIS. As Greenland's climate continues to warm, seasonal surface melting will increase in extent, intensity, and duration. Quantifying the possible rapid expansion of these sub-facies using satellite L-band microwave radiometry has significant implications for understanding ice-sheet-wide variability in englacial hydrology that may drive meltwater-induced hydrofracturing and accelerated ice flow as well as high-elevation meltwater runoff that can impact the mass balance and stability of the GrIS.

Julie Z Miller↗

NASA NTRSDate not supplied

New York Ecological Forecasting: Utilizing NASA Earth Observations to Map Ash Distribution and Inform Emerald Ash Borer Control

Since their first sightings in the U.S. in 2002, emerald ash borer beetles (Agrilus planipennis; EAB) have killed millions of native ash (Fraxinus spp.) trees across 35 states. Infected ash stands frequently exhibit complete mortality, with the predicted result being the functional extinction of native ash in U.S. forests. In August of 2020, EAB was discovered in the 6.1-million-acre Adirondack Park. The team’s partners at the Adirondack Park Invasive Plant Program (APIPP) desired ash tree distribution and EAB susceptibility information to help improve EAB bio-control efficiency and apply the methodology to future invasive programs. To assist, the team mapped ash tree distribution using NASA Earth observations from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Shuttle Radar Topography Mission (SRTM), along with hyperspectral imagery from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Field data from the Monitoring and Managing Ash (MaMA) project, iMapInvasives and iNaturalist databases, and the New York State Department of Environmental Conservation (NYSDEC) provided ground truthing for mapping and modeling. Results indicate that for ash detection, the team’s Spectral Angle Mapping (SAM) hyperspectral classification is slightly more sensitive but less accurate than multispectral Random Forest (RF) classification, though neither method was above a ~20% detection rate. End products include maps of ash extent derived from both imagery types, a model forecasting future spread scenarios based on current EAB presence, and outreach materials. These products inform APIPP’s management decisions and facilitate public awareness of EAB’s threat to communities within the region.

Liam Megraw↗

NASA NTRSDate not supplied

Envisioning the Future of International Earth Observations Collaboration: Area and Map Accuracy Estimation by Sampling

- Maps have errors, sometimes a lot of errors ⇒ obtaining information directly from map problematic; any use of the map will benefit from information about errors/uncertainty - IPCC: unbiasedness and uncertainty - By randomly drawing a sample from the study area, observing reference conditions at drawn locations, and constructing estimators – easily estimate areas and map accuracy ± uncertainty - Sampling design and analysis, relatively easy – collecting reference observations is not. Cloud-based solutions, e.g. AREA2, Collect Earth Online, facilitate the collection of reference observations - More research and guidance needed!

Pontus Olofsson↗

NASA NTRS2020

Overview and Status of EXCLAIM, the Experiment for Cryogenic Large-Aperture Intensity Mapping

The EXperiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) is a balloon-borne far-infrared telescope that will survey star formation history over cosmological time scales to improve our un-derstanding of why the star formation rate declined at redshiftz <2, despite continued clustering of darkmatter. Specifically, EXCLAIM will map the emission of redshifted carbon monoxide and singly ionized carbon lines in windows over a redshift range0< z <3.5, following an innovative approach known asintensity mapping. Intensity mapping measures the statistics of brightness fluctuations of cumulative lineemissions, as opposed to detecting individual galaxies, thus enabling a blind, complete census of the emittinggas. To detect this emission unambiguously, EXCLAIM will cross-correlate with a rich spectroscopic galaxycatalog. The EXCLAIM mission will use a cryogenic design to cool the telescope optics to approximately1.7K. The telescope will feature a90-cm primary mirror to probe spatial scales on the sky from the linearregime up to shot-noise-dominated scales. The telescope optical elements will couple to six μ-Spec spectrom-eter modules, operating over a420–540-GHz frequency band with a spectral resolution of512and featuringMicrowave Kinetic Inductance Detectors (MKIDs). In the baseline design, the detectors will be read out witha Radio Frequency System-on-Chip (RFSoC). The cryogenic telescope and the sensitive detectors will allowEXCLAIM to reach high sensitivity in spectral windows of low emission in the upper atmosphere. Here, anoverview of the mission design and development status since the start of the EXCLAIM project in early 2019 is presented.

Giuseppe Cataldo↗

NASA NTRSDate not supplied

2024 IEEE GRSS Data Fusion Contest Flood Rapid Mapping

The Challenge Task As a result of climate change, extreme hydrometeorological events are becoming increasingly frequent. Flood rapid mapping products play an important role in informing flood emergency response and management. These maps are generated quickly from remote sensing data during or after an event to show the extent of flooding. They provide important information for emergency response, and damage assessment. The aim of this challenge is to develop data fusion algorithms that generate flood maps by processing spatial data from a variety of sources. The goal of this IEEE challenge (sponsored by NASA and CNES) is to design and develop an algorithm that will combine multi-source data to classify flood surface water extent–that is, water and non-water areas. Provided data sources include optical and SAR remote sensing images as well as a digital terrain model. The output is a gridded flood map where each grid cell is labeled water or non-water. The difficulty of detecting flooded areas can vary greatly depending on the conditions in the area of interest and the event. This data fusion challenge has two tracks representing this variance.

Jacqueline J Le Moigne-stewart↗

NASA NTRSDate not supplied

A Machine Learning Ready Dataset of Acoustic Power Maps for Detection of Active Region Emergence

The development of an accurate forecast for solar eruptive activity has become increasingly important in order to prevent any potential impact on activities in space and the Earth's environment. It is therefore crucial to detect active regions before they appear on the solar surface and create early warning capabilities for upcoming Space Weather disturbances. In this work, 9TB of solar data (SDO/HMI dopplergrams, magnetograms and continuum intensity maps) involving the emergence of 61 NOAA solar active regions since 2010 were processed using the NASA HECC capabilities. An acoustic power maps time-series dataset was created (for four different frequency ranges and processed to take into account the solar sphere geometric effect ) which can be used for understanding the dynamics of the solar surface and train a variety of ML models. The calculated acoustic power maps carry precursor information associated with the decrease in continuum intensity on the solar surface, verifying older helioseismology research. Our results show that a Long Short-Term Memory (LSTMs) model, with a modest layer depth and the right hyperparameters tuned, when trained on this solar acoustic power maps dataset can predict without false negatives a drop in intensity (associated with the emergence of the active region), up to 18 hours in advance.

SMD↗

NASA NTRSDate not supplied

Metabolic Vessel for Impedance Spectroscopy and Electrochemistry (MVISE): The Ground Mapping Unit for the Lunar Explorer Instrument for Space Biology Applications (LEIA)

The BioSensor payload on the upcoming LEIA platform aboard a CLPS lander will carry yeast to the moon to study response to radiation and lunar gravity. The LEIA BioSensor is designed to monitor metabolic activity using absorbance in conjunction with alamarBlue for measuring colorimetric changes as proxy measurement for redox potential. The science data returned from small spacecraft mission modules like LEIA is limited as it relies solely on optical measurements, necessitating a corresponding ground mapping unit that is equipped with multiple electrochemical sensors for accurate mapping of the optical data and operates fully automatically. This technology development work discusses the extensive design and optimization efforts put into the ground mapping unit, MVISE. MVISE is a custom designed, 3D-printed vessel with an agitation system, with six different electrochemical sensor probes, and ports for sample collection and a pressure release valve. The sensors provide real-time data, with dry absorbance measurements aligning with LEIA flight hardware and wet measurements demonstrating invasive sensor design enabling a comparison between the two setups. The 3D printer resin was tested for mechanical robustness, biocompatibility, and resistance to autoclave sterilization. The inner walls were coated with food-grade epoxy, ensuring a smooth finish to prevent microbial lodging and dye staining. The MVISE has successfully passed a week-long leak test and is now undergoing active biology tests. The MVISE prototype will be prepared for radiation tests, with three identical units being tested for varying radiation levels and culture compositions at the NASA Space Radiation Laboratory in November 2024. The integrated sensor approach proposed in this work will enable the accurate mapping of the BioSentinel/LEIA optical flight data to six sensor parameters on the ground unit for better science data return and will enable the first effort to evaluate classical biochemical sensor measurements by comparing and contrasting their responses.

Chinmayee Govinda Raj↗

NASA NTRSDate not supplied

Environmental Barrier Coating Surface Temperature Mapping Using a Compatible Er-Doped Sc 2 SiO 5 Temperature-Sensing Layer

Accurate surface temperature-mapping capabilities in the 1300 to 1500 °C range are needed for SiC/SiC ceramic matrix composites protected by environmental barrier coatings (EBCs) under testing in turbine engine environment facilities. The strong background thermal radiation at these higher temperatures is a challenging issue. Er-doped Y 2 SiO 5 was previously shown to be capable of achieving luminescence lifetime-based temperature mapping up to 1560 °C as a standalone material. However, compatibility issues between an Er-doped Y 2 SiO 5 surface temperature sensing layer and an underlying Sc 2 Si 2 O 7 -based EBC topcoat limited temperature mapping of the EBC surface to a maximum of 1380 °C. Therefore, an Er-doped Sc 2 SiO 5 temperature sensing layer has been subsequently developed with better compatibility with the Sc2Si2O7-based EBC topcoat. Localized spot temperature measurements as well as luminescence lifetime imaging-based temperature mapping were demonstrated up to 1535 °C from a 15 µm thick Er-doped Sc 2 SiO 5 layer at the surface of a Sc2Si2O7-based EBC topcoat, a significant improvement over the Er-doped Y2SiO5 layer 1380 °C temperature sensing limit. No degradation of the Er-doped Sc 2 SiO 5 temperature sensing surface layer was observed.

temperature measurement↗

NASA NTRS2025

Mission-Maps For Outbound Cislunar Transfer Trajectories

This study quantifies the robustness and sensitivity of an outbound cislunar trajectory for a lunar lander in the form of mission-maps, or topological maps that allows either a computer program or mission designer to intuitively optimize the placement of critical outbound correction burns from the derived sensitivity data. The non-linear multi-body dynamics are applied to generate an outbound cislunar reference profile used by a linear covariance analysis (LinCov) tool to compute the expected Δv and trajectory dispersions due to the initial state uncertainty, sensor errors, maneuver execution errors, and disturbance accelerations along the outbound cislunar profile. The rapid performance analysis capabilities of LinCov are complimented with parallel processing techniques to evaluate hundreds and thousands of different translational burn locations, placements, and targeting constraints to identify the combination that minimizes the total Δv usage (nominal plus 3σ Δv) and trajectory dispersions at lunar orbit insertion. This study utilizes a generalized reference targeting algorithm to quickly assess the integrated closed-loop GN&C system performance due to different targeting configurations and constraints. The resulting mission maps provide an intuitive insight to ascertain each trajectory correction maneuver’s (TCM) sensitivity to different burn times along an outbound cislunar trajectory and quickly identify desirable engineering tradeoffs when performing analysis on the number and placement of these burns that nominally zero. Multiple mission maps are generated for a variety of different performance parameters that allow engineers to visually identify optimal solutions for trajectory correction maneuver placements, the number of correction burns, and the targeting constraints for each burn.

GN&C↗

NASA NTRS2026

The Thermal and Kinematic Sunyaev–Zeldovich Effect in Galaxy Clusters and Filaments Using Multifrequency Temperature Maps of the Cosmic Microwave Background A399–A401 Cluster Pair Case Study

We present a multifrequency and multi-instrument methodology to study the physical properties of galaxy clusters and cosmic filaments using cosmic microwave background observations. Our approach enables simultaneous measurement of both the thermal (tSZ) and kinematic Sunyaev–Zeldovich (kSZ) effects, incorporates relativistic corrections, and models astrophysical foregrounds such as thermal dust emission. We do this by jointly fitting a single physical model across multiple maps from multiple instruments at different frequencies, rather than fitting a model to a single Compton-y map. We demonstrate the success of this method by fitting the A399–A401 galaxy cluster pair and filament system using archival data from the Planck satellite and new, targeted deep data from the Atacama Cosmology Telescope, covering 11 different frequencies over 14 maps from 30 GHz to 545 GHz. Our tSZ results are consistent with previous work using Compton-y maps. We measure the line-of-sight peculiar velocities of the cluster–filament system using the kSZ effect and find statistical uncertainties on individual cluster peculiar velocities of ≲600 km s −1 , which are competitive with current state-of-the-art measurements. Additionally, we measure the optical depth of the filament component with a signal-to-noise of 8.5σ and reveal hints of its morphology. This modular approach is well-suited for application to future instruments across a wide range of millimeter and submillimeter wavebands.

Ajay S Gill↗

NASA NTRSDate not supplied

Geologic Maps for Civil Engineering and Infrastructure Planning

The Artemis Program mandate for sustainable, long-term presence on the Moon requires learning to "Live Off the Land". Geologic maps enable a paradigm shift to model the development and scaling of infrastructure for robotic and human exploration inside a bounded system on the lunar surface. Relying on geologic maps produced from orbital data and robotic precursor missions, in-situ resource utilization (ISRU) will be required to produce infrastructure, building materials and consumables. The ISRU value chain must be mapped to identify linkages of resources, producers, processes and equipment capabilities for transforming excavated regolith into usable feedstocks. Coordination will be required to balance supply and demand across the whole system of lunar infrastructure and operations, at each stage of development.

Geologic Mapping↗