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NASA NTRS2007

Synthetic Vision Enhanced Surface Operations With Head-Worn Display for Commercial Aircraft

Experiments and flight tests have shown that airport surface operations can be enhanced by using synthetic vision and associated technologies, employed on a Head-Up Display (HUD) and head-down display electronic moving maps (EMM). Although HUD applications have shown the greatest potential operational improvements, the research noted that two major limitations during ground operations were its monochrome form and limited, fixed field-of-regard. A potential solution to these limitations may be the application of advanced Head Worn Displays (HWDs) particularly during low-visibility operations wherein surface movement is substantially limited because of the impaired vision of pilots and air traffic controllers. The paper describes the results of ground simulation experiments conducted at the NASA Langley Research Center. The results of the experiments showed that the fully integrated HWD concept provided significantly improved path performance compared to using paper charts alone. When comparing the HWD and HUD concepts, there were no statistically-significant differences in path performance or subjective ratings of situation awareness and workload. Implications and directions for future research are described.

Arthur, Jarvis J., III↗

NASA NTRS2010

NASA's Space Lidar Measurements of Earth and Planetary Surfaces

A lidar instrument on a spacecraft was first used to measure planetary surface height and topography on the Apollo 15 mission to the Moon in 1971, The lidar was based around a flashlamp-pumped ruby laser, and the Apollo 15-17 missions used them to make a few thousand measurements of lunar surface height from orbit. With the advent of diode pumped lasers in the late 1980s, the lifetime, efficiency, resolution and mass of lasers and space lidar all improved dramatically. These advances were utilized in NASA space missions to map the shape and surface topography of Mars with > 600 million measurements, demonstrate initial space measurements of the Earth's topography, and measured the detailed shape of asteroid. NASA's ICESat mission in Earth orbit just completed its polar ice measurement mission with almost 2 billion measurements of the Earth's surface and atmosphere, and demonstrated measurements to Antarctica and Greenland with a height resolution of a few em. Space missions presently in cruise phase and in operation include those to Mercury and a topographic mapping mission of the Moon. Orbital lidar also have been used in experiments to demonstrate laser ranging over planetary distances, including laser pulse transmission from Earth to Mars orbit. Based on the demonstrated value of the measurements, lidar is now the preferred measurement approach for many new scientific space missions. Some missions planned by NASA include a planetary mission to measure the shape and dynamics of Europa, and several Earth orbiting missions to continue monitoring ice sheet heights, measure vegetation heights, assess atmospheric CO2 concentrations, and to map the Earth surface topographic heights with 5 m spatial resolution. This presentation will give an overview of history, ongoing work, and plans for using space lidar for measurements of the surfaces of the Earth and planets.

Abshire, James B.↗

NASA NTRS2006

NASA Tech Briefs, November 2006

Topics include: Simulator for Testing Spacecraft Separation Devices; Apparatus for Hot Impact Testing of Material Specimens; Instrument for Aircraft-Icing and Cloud-Physics Measurements; Advances in Measurement of Skin Friction in Airflow; Improved Apparatus for Testing Monoball Bearings; High-Speed Laser Scanner Maps a Surface in Three Dimensions; Electro-Optical Imaging Fourier-Transform Spectrometer; Infrared Instrument for Detecting Hydrogen Fires; Modified Coaxial Probe Feeds for Layered Antennas; Detecting Negative Obstacles by Use of Radar; Cryogenic Pound Circuits for Cryogenic Sapphire Oscillators; PixelLearn; New Software for Predicting Charging of Spacecraft; Conversion Between Osculating and Mean Orbital Elements; Generating a 2D Representation of a Complex Data Structure; Making Activated Carbon by Wet Pressurized Pyrolysis; Composite Solid Electrolyte Containing Li+- Conducting Fibers; Electrically Conductive Anodized Aluminum Surfaces; Rapid-Chill Cryogenic Coaxial Direct-Acting Solenoid Valve; Variable-Tension-Cord Suspension/Vibration- Isolation System; Techniques for Connecting Superconducting Thin Films; Versatile Friction Stir Welding/Friction Plug Welding System; Thermal Spore Exposure Vessels; Enumerating Spore-Forming Bacteria Airborne with Particles; Miniature Oxidizer Ionizer for a Fuel Cell; Miniature Ion-Array Spectrometer; Promoted-Combustion Chamber with Induction Heating Coil; Miniature Ion-Mobility Spectrometer; Mixed-Salt/Ester Electrolytes for Low-Temperature Li+ Cells; Miniature Free-Space Electrostatic Ion Thrusters; Miniature Bipolar Electrostatic Ion Thruster; Holographic Plossl Retroreflectors; Miniature Electrostatic Ion Thruster With Magnet; Using Apex To Construct CPM-GOMS Models; Sequence Detection for PPM Optical Communication With ISI; Algorithm for Rapid Searching Among Star-Catalog Entries; Expectation-Based Control of Noise and Chaos; Radio Heating of Lunar Soil to Release Gases; Using Electrostriction to Manipulate Ullage in Microgravity; Equations for Scoring Rules When Data Are Missing; Insulating Material for Next-Generation Spacecraft; and Pseudorandom Switching for Adding Radar to the AFF Sensor.

Source record↗

NASA NTRS2012

Sensing and Virtual Worlds - A Survey of Research Opportunities

Virtual Worlds (VWs) have been used effectively in live and constructive military training. An area that remains fertile ground for exploration and a new vision involves integrating various traditional and now non-traditional sensors into virtual worlds. In this paper, we will assert that the benefits of this integration are several. First, we maintain that virtual worlds offer improved sensor deployment planning through improved visualization and stimulation of the model, using geo-specific terrain and structure. Secondly, we assert that VWs enhance the mission rehearsal process, and that using a mix of live avatars, non-player characters, and live sensor feeds (e.g. real time meteorology) can help visualization of the area of operations. Finally, tactical operations are improved via better collaboration and integration of real world sensing capabilities, and in most situations, 30 VWs improve the state of the art over current "dots on a map" 20 geospatial visualization. However, several capability gaps preclude a fuller realization of this vision. In this paper, we identify many of these gaps and suggest research directions

Moore, Dana↗

NASA NTRS2011

Snow Cover, Snowmelt Timing and Stream Power in the Wind River Range, Wyoming

Earlier onset of springtime weather, including earlier snowmelt, has been documented in the western United States over at least the last 50 years. Because the majority (is greater than 70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for the management of streamflow. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work, such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud-gap-filled (CGF) map products and 30 years of discharge and meteorological station data are studied. Streamflow data from streams in WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period as a whole. The extent of snow-cover (percent of basin covered) derived from the lowest elevation zone (2500-3000 m) of the WRR, using MODIS CGF snow-cover maps, is strongly correlated with maximum monthly discharge on 30 April, where Spearman's Rank correlation, rs,=0.89 for the decade of the 2000s. We also investigated stream power for Bull Lake Creek above Bull Lake; and found a trend (significant at the 90% confidence level) toward reduced stream power from 1970 to 2009. Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period, possibly contributing to a reduction in snow cover. In addition, the strong relationship between percent of basin that was snow covered, and maximum monthly streamflow indicates that MODIS snow-cover maps are useful for predicting streamflow, and can be used to improve management of water resources in the drought-prone western United States.

MODIS↗

NASA NTRS2017

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗

NASA NTRS2017

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Remote Sensin↗

DOE OSTI2020

Precision snow removal analysis

A method for precision snow removal analysis provides a melt rate in inches per day for roadways in a geometric region is provided. Elevation data is used to calculate upward looking hemispherical viewsheds at each roadway coordinate to determine the total solar radiation. The snowmelt capacity and slope are determined at each coordinate and the data is displayed on a geographical map of the roadway. The processing speed of the computer is improved since the snowmelt capacity is only determined for a roadway subset of the region coordinates.

42 ENGINEERING↗

NASA NTRS2011

The Goes-R Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved storm diagnostic capability with the Advanced Baseline Imager. The GLM will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. In this paper we will report on new Nowcasting and storm warning applications being developed and evaluated at various NOAA Testbeds.

Goodman, Steven J.↗

DOE OSTI2022

The SiD Digital ECal Based on Monolithic Active Pixel Sensors

The SiD detector concept capitalizes on high granularity in its tracker and calorimeter to achieve the momentum resolution and particle flow calorimetry physics goals in a compact design. The collaboration has had a long interest in the potential for improved granularity in both the tracker and ECal with an application of monolithic active pixel sensors (MAPS) and a study of MAPS in the SiD ECal was described in the ILC TDR. Work is progressing on the MAPS application in an upgraded SiD design with a prototyping design effort for a common SiD tracker/ECal design based on stitched reticules to achieve 10 × 10 cm2 sensors with 25 × 100 micron2 pixels. Application of large area MAPS in these systems would limit delicate and expensive bump-bonding, provide possibilities for better timing, and should be significantly cheaper than the TDR concept due to being a more conventional CMOS foundry process. The small pixels significantly improve shower separation. Recent simulation studies confirm previous performance projections, indicating electromagnetic energy resolution based on digital hit cluster counting provides better performance than the SiD TDR analog design based on 13 mm2 pixels. Furthermore, the two shower separation is excellent down to the millimeter scale. Geant4 simulation results demonstrate these expectations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2012

Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived from this study agree well with an existing urban extent polygon data set that was previously developed independently. The overall mapping accuracy was estimated at about 92.5% with 3% commission error and 12% omission error for the impervious type from all images regardless of image quality and initial spatial resolution.

Gao, Feng↗

NASA NTRS1992

A study of mapping exogenous knowledge representations into CONFIG

Qualitative reasoning is reasoning with a small set of qualitative values that is an abstraction of a larger and perhaps infinite set of quantitative values. The use of qualitative and quantitative reasoning together holds great promise for performance improvement in applications that suffer from large and/or imprecise knowledge domains. Included among these applications are the modeling, simulation, analysis, and fault diagnosis of physical systems. Several research groups continue to discover and experiment with new qualitative representations and reasoning techniques. However, due to the diversity of these techniques, it is difficult for the programs produced to exchange system models easily. The availability of mappings to transform knowledge from the form used by one of these programs to that used by another would open the doors for comparative analysis of these programs in areas such as completeness, correctness, and performance. A group at the Johnson Space Center (JSC) is working to develop CONFIG, a prototype qualitative modeling, simulation, and analysis tool for fault diagnosis applications in the U.S. space program. The availability of knowledge mappings from the programs produced by other research groups to CONFIG may provide savings in CONFIG's development costs and time, and may improve CONFIG's performance. The study of such mappings is the purpose of the research described in this paper. Two other research groups that have worked with the JSC group in the past are the Northwest University Group and the University of Texas at Austin Group. The former has produced a qualitative reasoning tool named SIMGEN, and the latter has produced one named QSIM. Another program produced by the Austin group is CC, a preprocessor that permits users to develop input for eventual use by QSIM, but in a more natural format. CONFIG and CC are both based on a component-connection ontology, so a mapping from CC's knowledge representation to CONFIG's knowledge representation was chosen as the focus of this study. A mapping from CC to CONFIG was developed. Due to differences between the two programs, however, the mapping transforms some of the CC knowledge to CONFIG as documentation rather than as knowledge in a form useful to computation. The study suggests that it may be worthwhile to pursue the mappings further. By implementing the mapping as a program, actual comparisons of computational efficiency and quality of results can be made between the QSIM and CONFIG programs. A secondary study may reveal that the results of the two programs augment one another, contradict one another, or differ only slightly. If the latter, the qualitative reasoning techniques may be compared in other areas, such as computational efficiency.

Mayfield, Blayne E.↗

NASA NTRS2011

Bringing Together Users and Developers of Forest Biomass Maps

Brown, Molly E.↗

NASA NTRS2012

Bringing Together Users and Developers of Forest Biomass Maps

Forests store carbon and thus represent important sinks for atmospheric carbon dioxide. Reducing uncertainty in current estimates of the amount of carbon in standing forests will improve precision of estimates of anthropogenic contributions to carbon dioxide in the atmosphere due to deforestation. Although satellite remote sensing has long been an important tool for mapping land cover, until recently aboveground forest biomass estimates have relied mostly on systematic ground sampling of forests. In alignment with fiscal year 2010 congressional direction, NASA has initiated work toward a carbon monitoring system (CMS) that includes both maps of forest biomass and total carbon flux estimates. A goal of the project is to ensure that the products are useful to a wide community of scientists, managers, and policy makers, as well as to carbon cycle scientists. Understanding the needs and requirements of these data users is helpful not just to the NASA CMS program but also to the entire community working on carbon-related activities. To that end, this meeting brought together a small group of natural resource managers and policy makers who use information on forests in their work with NASA scientists who are working to create aboveground forest biomass maps. These maps, derived from combining remote sensing and ground plots, aim to be more accurate than current inventory approaches when applied at local and regional scales. Meeting participants agreed that users of biomass information will look to the CMS effort not only to provide basic data for carbon or biomass measurements but also to provide data to help serve a broad range of goals, such as forest watershed management for water quality, habitat management for biodiversity and ecosystem services, and potential use for developing payments for ecosystem service projects. Participants also reminded the CMS group that potential users include not only public sector agencies and nongovernmental organizations but also the private sector because much forest acreage in the United States is privately held and needs data for forest management. Additional key outcomes identified by meeting participants include the following: (1) Priority should be given to building into the biomass product ease of use and low costs (including costs of hardware, software, and analysis requirements), (2) CMS products should also be relevant to other biomass measures for forest watershed management, habitat protection for biodiversity, and assessment of markets for ecosystem services, (3) CMS leadership should engage with the Subsidiary Body for Scientific and Technological Advice of the United Nations Framework Convention on Climate Change as they establish measuring, reporting, and verification standards, and (4) CMS leadership should continue to keep sister agencies and other organizations informed as CMS develops, particularly via the agencies active in the U.S. Global Change Research Program Carbon Cycle Interagency Working Group (U.S. Geological Survey, U.S. Department of Agriculture, and National Oceanic and Atmospheric Administration) and nongovernmental organizations.

Forest↗

DOE OSTI2021

Scalable In Situ Computation of Lagrangian Representations via Local Flow Maps

In situ computation of Lagrangian flow maps to enable post hoc time-varying vector field analysis has recently become an active area of research. However, the current literature is largely limited to theoretical settings and lacks a solution to address scalability of the technique in distributed memory. To improve scalability, we propose and evaluate the benefits and limitations of a simple, yet novel, performance optimization. Our proposed optimization is a communication-free model resulting in local Lagrangian flow maps, requiring no message passing or synchronization between processes, intrinsically improving scalability, and thereby reducing overall execution time and alleviating the encumbrance placed on simulation codes from communication overheads. To evaluate our approach, we computed Lagrangian flow maps for four time-varying simulation vector fields and investigated how execution time and reconstruction accuracy are impacted by the number of GPUs per compute node, the total number of compute nodes, particles per rank, and storage intervals. Our study consisted of experiments computing Lagrangian flow maps with up to 67M particle trajectories over 500 cycles and used as many as 2048 GPUs across 512 compute nodes. In all, our study contributes an evaluation of a communication-free model as well as a scalability study of computing distributed Lagrangian flow maps at scale using in situ infrastructure on a modern supercomputer.

Sane, Sudhanshu↗

NASA NTRS1983

Comparative assessment of LANDSAT-4 MSS and TM data quality for mapping applications in the southeast

The initial objectives of analyses of the MSS data are two-fold: (1) to evaluate the geodetic accuracy of CCT-P data of the test sites; and (2) to improve the geodetic accuracy by additional processing if the original data either do not meet pre-launch specifications or mapping requirements. The location of 45 ground control points (GCP) digitized from 35 U.S. Geological Survey 1:24,000 scale quadrangles (UTM coordinates) were identified in terms of pixel and scan line values. These 46 points are used to establish UTM position error vector distributions in the scene. As an initial check on the geometric reliability of the MSS data, 28 well-distributed GCPs were input to a program which compares the scaled image distances between all possible point pairs with the corresponding map distances and computes the distance differences; that is, the relative positional errors. The relative errors obtained from initial computations averaged about +/- 200 m. These errors could result from a number of sources, including misidentification of GCP locations, UTM coordinate errors introduced by the map digitizing process or errors resulting from data acquisition and geometric processing.

Welch, R.↗

NASA NTRS1975

Environmental monitoring of North Merritt Island

The environmental impact of the space shuttle operation on North Merritt Island was studied mainly by means of color infrared photos and field visits. An attempt was also made to generate character maps of the Island using LANDSAT data with a view to decreasing the cost of monitoring and making the process more flexible in terms of rapid estimation of the extent of selected ground features. It seems possible that the IMAGE-100 output can be improved by using it in conjunction with software systems which are used for generating character maps. All the methods for generating maps show six main plant associations on North Merritt Island. It was shown that the six associations are related by ecological succession, merge into their neighbors in terms of component species and can be observed for changes in terms of component species.

Poonai, P.↗

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↗