Search NASA⌕ Search

SEARCH · Search NASA

Results for “Landslide”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

NASA-ISRO Synthetic Aperture Radar (NISAR) Mission

NISAR is a multi-disciplinary Earth-observing radar mission that makes global measurements of land surface changes that will greatly improve Earth system models. NISAR data will clarify spatially and temporally complex phenomena, including ecosystem disturbances, ice sheet collapse, and natural hazards including earthquakes, tsunamis, volcanoes, and landslides. It provides societally relevant data that will enable better protection of life and property. The mission, a NASA-ISRO partnership, uses two fully polarimetric SARs, one at L-band (L-SAR) and one at S-band (S-SAR), in exact repeating orbits every 12 days that allows interferometric combination of data on repeated passes. NASA provides the L SAR; a shared deployable reflector; an engineering payload that supports mission-specific data handling, navigation and communication functions; science observation planning and L SAR data processing. ISRO provides the S-SAR, spacecraft, launch vehicle, satellite operations, and S-SAR data processing. The mission will be launched from the Satish Dhawan Space Centre, Sriharikota, India. Mission development has addressed many unique challenges and incorporates many “firsts” for a jointly-developed free-flyer radar science mission.

Sarma, C V H S↗
NASA NTRS2020

MSL Telecom Automated Anomaly Detection

Deformation in the form of natural hazards like earthquakes, volcanic eruptions and landslides, to ecosystem disturbances, to changes in the cryosphere (measurements of polar ice caps, ice sheets and sea ice).

Bell, David↗
NASA NTRSDate not supplied

Building Capacity to Use Earth Observations for Disaster Risk Reduction and Resilience Applications: A Summary of NASA’s DEVELOP Program and Projects in Central and South America

NASA’s DEVELOP program engages individuals and organizations in 10-week feasibility studies to apply NASA Earth observations (EO) to decision makers’ needs. Since 2018, DEVELOP conducted 21 projects in Central and South America, eight of those in collaboration with Sistema de la Integración Centroamericana (SICA) and its member state partner agencies. These projects addressed a diverse set of community needs across multiple themes, including two focused on disaster risk reduction and resilience using EO for mapping landslide susceptibility in the Dominican Republic and riparian flooding in Guatemala and El Salvador. This poster introduces DEVELOP, its approach to capacity building, key partnerships, and project results highlighting the capabilities of EO for enhanced decision making in the area of reduction of disaster risk and support disaster resilience.

Capacity Building↗
NASA NTRSDate not supplied

Co-developing a SAR for Disasters Reference Guide for the International Applications Community

Synthetic Aperture Radar (SAR) data are widely applicable for disaster monitoring, especially in Central and South America where atmospheric effects are a frequent obstacle for disaster monitoring. There is a growing interest in the application of SAR data to diverse disasters, ranging from landslides to volcanic eruptions and floods. With this interest comes a growing need for user-friendly guides that facilitate the integration of SAR into existing workflows. A joint effort between AmeriGEO, university networks in the Americas, NASA SERVIR’s Science Coordination Office (SCO), and the NASA Earth Science Disasters Program, culminated in the “SAR for Disasters” Guide. The guide is modeled after the one-page informational sheets created for SERVIR’s SAR Handbook, with the aim to succinctly communicate the key considerations needed to apply relevant analyses using SAR. Developed with contributors from diverse backgrounds, this guide is designed to be a useful reference for experienced technical users and beginners alike.

SAR↗
NASA NTRSDate not supplied

Evaluating and Exploring Extreme Precipitation in CHIRPS3, CHIMES, and the Climate Hazards Station Database

Between 2015 and 2019, the impacts and losses associated with droughts, floods, and hurricanes surged through the interaction of increasing exposure and more extreme weather and climate (Funk 2021). In 2020, the Aon-Benfield Reinsurance Company reported that cyclones, floods, and droughts resulted in $165 billion (USD) in losses. For 2020, EM-DAT lists 363 flood, landslide, storm, and drought events impacting some 98 million people. As hazards mount, models indicate more variable precipitation, and observations indicate increasing extremes in humid regions, yet the small number of available gauge observations is declining. In this talk we briefly introduce two new resources: version 3 of the 1981-near present Climate Hazards center Infrared Precipitation with Stations (CHIRPS3) archive, and the 2000-near present Climate Hazards IMErg with Stations archive (CHIMES). The satellite-only CHIRP3 and CHIME components are based, respectively, on geostationary thermal infrared Cold Cloud Duration (CCD) values and the NASA GPM IMERGlate product. These archives benefit from thousands of station observations. In addition to standard global sources, the Climate Hazards station database includes about 5,000 additional stations in humid tropical and sub-tropical areas associated with likely increases in extreme rainfall. While effectively monitoring extreme precipitation is important to humanitarian agencies like FEWS NET, and to hydrologic modeling applications (a, b), evaluations of the widely used CHIRPS2 product indicate a propensity to underestimate extremes. Here, we explain the source of this problem. Then, focusing on pentad totals in 12 well-gauged regions, we use the high-quality gauge-based REGEN dataset to show that CHIRP3 and CHIME perform substantially better than CHIRP2. We examine trends in extremes in these validation regions, comparing REGEN results with values from the satellite-only CHIRP2, CHIRP3, CHIME and the gauge-enhanced CHIRP2, CHIRP3, CHIME. Trends in dry and humid regions are contrasted and compared. We conclude with global evaluations of the pentad CHIRP3, CHIRPS3, CHIME, CHIMES, and Climate Hazards station database products. How does the performance of the shorter period of record CHIME compare with CHIRP3? We anticipate that the sophisticated microwave-based IMERGlate inputs into CHIME will perform better. Where do we see the largest increases in extremes in these products? How well might CHIRPS3 and CHIMES perform in the context of humanitarian assistance efforts?

C Funk↗
NASA NTRSDate not supplied

Planning Satellite Swarm Measurements for Climate Models: Comparing Dynamic Constraint Processing and MILP Methods

We present D-SHIELD, a challenging climate science application to plan coordinated measurements (observations) for a constellation of satellites, each containing two different sensors, each with 61 pointing angle options. The L-band and P-band radar sensors collect data fed into a soil moisture model which tracks and predicts soil moisture across 1.67 million Ground Positions (GP). Soil moisture is an important predictor of wildfires, and then a predictor of floods, landslides and debris flow after a fire. Each measurement covers multiple GP due to the sensor footprint. Each GP has a "model error" which represents the uncertainty of the the soil moisture state prediction. Model error changes at different rates for each GP as the time since last observation increases and after significant events like rain. The planner's goal is to select measurements which maximize soil moisture model improvement (reduce model uncertainty). This problem is combinatorically explosive, involving many degrees of freedom for planner choices. Good domain heuristics can find solutions within a reasonable time for our application needs but cannot be proven optimal. In this paper we compare two different planning approaches to this problem: Dynamic Constraint Processing (DCP) and Mixed Integer Linear Programming (MILP). We match inputs and metrics for both DCP and MILP algorithms to enable a direct apples-to-apples comparison. We demonstrate and discuss the trades between DCP flexibility and performance vs. MILP's promise of provable optimality.

Rich Levinson↗
NASA NTRS2021

Central America Disasters: Using Earth Observations to Map Flooding for Disaster Monitoring, Inform Potential Risk, and Prepare for Possible Response

In November 2020, Hurricanes Eta and Iota hit Central America within weeks of each other, causing severe flooding, landslides, and widespread damage. NASA DEVELOP partnered with Comité Regional de Recursos Hidráulicos (CRRH), Centro de Coordinación para la Prevención de los Desastres en América Central y República Dominicana (CEPREDENAC), and Sistema de la Integración Centroamericana (SICA) to better understand how flooding throughout Central America has impacted and will continue to affect communities, focusing on sites in Guatemala, Honduras, El Salvador, Belize, Nicaragua, western Panama, and eastern Costa Rica from January 2015 to October 2021. The team utilized surface reflectance data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). This project also utilized backscatter data from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and elevation data from the Shuttle Radar Topography Mission (SRTM). Incorporating these Earth observations in NASA SERVIR’s Hydrologic Remote Sensing Analysis for Floods (HYDRAFloods) tool run on Google Earth Engine (GEE), the team produced historical surface water maps, a case study analysis of the two hurricanes, and a code tutorial. These results indicated that surface water increased in priority sites from 2015 to 2021, optical and SAR imagery detected similar flood patterns and extent after the hurricanes, and rainfall was concentrated on the east coast of the region. These products allow partners to make informed decisions around flooding preparation and disaster mitigation.

Caroline Williams↗
NASA NTRS2020

Operations Concept for Responding to Urgent Requests for NASA-ISRO Synthetic Aperture Radar (NISAR)

The NASA-ISRO Synthetic Aperture Radar, or NISAR, mission is an Earth-mapping radar observatory to be launched from Sriharikota (India) in 2022. This mission is a collaboration between the National Aeronautics and Space Administration (NASA) and the Indian Space Research Organization (ISRO). This spacecraft will carry two instruments that will operate at radar wavelengths (L and Sband) and will provide data for understanding changes in the Earth’s land surface. The scientific data from this mission will revolutionize our understanding of the causes and consequences of land surface changes on Earth, ranging from Solid Earth Deformation in the form of natural hazards like earthquakes, volcanic eruptions and landslides, to ecosystem disturbances, to changes in the cryosphere (measurements of polar ice caps, ice sheets and sea ice). A nominal Reference Observation Plan, that repeats roughly every 12-24 days, developed prior to launch by the NISAR Mission Planning team, in consultation with the Science Team, will form the basis of science data collection by the payload instruments onboard the NISAR observatory after launch. Scheduling of science observations for the mission requires accounting for limited spacecraft resources like onboard data storage, downlink capacity, energy/power, thermal limits and instrument duty cycles. In addition to nominal science data collection, the project has a Level 1 requirement to respond to requests for urgent data acquisition over disaster sites (natural or anthropogenic) by scheduling new acquisitions within 24 hrs of notification and delivering science data within 5 hours of data acquisition. This capability is to be exercised on a ‘best-efforts basis’. While the definition of what constitutes an ‘urgent request’, and how such requests would be submitted to the project, is within the domain of the Science Team, the Mission System team is responsible for developing the baseline operations concept and implementation approach for responding to such requests. Given the ‘best-efforts’ nature of this requirement, a few highlevel guidelines have been developed to help guide the formulation of the operations concept, and are presented in this paper. Requests for urgent response data will be accommodated following the guiding principle of minimal to no impact on nominal science and planned engineering activities. No change in satellite orbit or attitude will be made for urgent response. Restricting response approaches to only changing the downlink and/or ground processing priority for existing observations, and adding new observations only in areas where NISAR will not be nominally imaging, allows for minimal impact on the Reference science Observation Plan. No instrument mode changes will be allowed for urgent response (except for high-priority requests), and no new observations that impact either planned science or engineering activities will be scheduled. Additionally, data requests must fit within the available project resource margins (both spacecraft and ground resources are to be evaluated). Both JPL and ISRO will be involved at various steps of the implementation, irrespective of whether the urgent request is for L-SAR (NASA instrument) or S-SAR (ISRO instrument) or a joint dataset.

Sharma, Priyanka↗
NASA NTRSDate not supplied

SURFACE EXOSURE TIMESCALES OF APOLLO CORE SAMPLE 73002 SPACE WEATHERED GRAINS

Introduction: Space weathering causes the surface regolith on airless bodies like the Moon to be morphologically, microstructurally, and chemically altered due to micrometeoroid bombardment and solar wind irradiation[1]. These processes produce a multitude of microstructural and chemical changes in individual soil grains that accumulate as grains are exposed on the surface over time. One microstructural feature produced by exposure to the solar wind is the development of ion-damaged rims on regolith grains via H+ and He+ ion irradiation. Also present are solar energetic particle (SEP) tracks, which are nanoscale lineations of ionization damage within grain interiors formed by high energy solar flare ions(primarily Fe group nuclei) which penetrate millimeters below the surface [2]. Recent work has confirmed that the thickness of solar wind-damaged amorphous rims on anorthite grains, nanocrystalline rims on olivine grains, and their respective SEP track densities are correlated with their surface exposure ages [3].Core sample 73002, recently released under the Apollo Next Generation Sample Analysis (ANGSA) Program, has provided an opportunity to study material collected from the light mantle formation during Apollo 17. The light mantle is thought to have been deposited via a landslide originating from the neighboring South Massif [4]. Spectral profiles and ferromagnetic resonance measurements of bulk soils sampled at cm-intervals from 73002 indicate the existence of mature regolith extending ~8 cm below the surface, suggesting the presence of an in-situ reworking zone in the core[5,6].Here we present the distribution of SEP track densities, solar wind damaged rim widths, and the corresponding surface exposure ages of grains residing in the proposed in-situ reworking zone of core 73002. Methods: Bulk samples of regolith from the first eight intervals and every following fourth interval down the core (dissection Pass 2) were delivered to Purdue University as <45 μm size fractions. The first eight0.5 cm intervals, representing the top 4cmof regolith, were individually dry sieved to a<20 μm size fraction, and grains were prepared by ultramicrotomy for analysis in the scanning transmission electron microscope (STEM). Bright field (BF) and dark field (DF) STEM images of solar flare tracks and solar wind damaged rims were acquired on a JEOL 2500SE TEM, equipped with a 60 mm2ultra-thin window silicon drift energy dispersive X-ray (EDX) spectrometer at NASA John-son Space Center. Grain compositions were determined by EDX compositional spectrum imaging. SEP track densities and amorphous rim thicknesses were measured on BF and DF images. Results: The fraction of grains with discernable space weathering features decreased with depth, with 100% in the first interval exhibiting space weathering features as opposed to ~60% in Interval 8.BF and DF STEM images show splash-melt and vapor deposited rims on outermost grain margins with embedded Fe-bearing nanoparticles ranging in size up to ~10 nm in diameter. Images also show solar-wind damaged rims below the vapor deposits, and SEP tracks present in grain interiors. The rim thicknesses and SEP track densities were determined using the methods of [3] for 54grains spanning the top 4 cm. ~80% of the grains analyzed were anorthite and ~20% were olivine. The track production rate from[3] was used to estimate the surface exposure times of the grains in this study. The majority of exposure times are in the 1 -5 MY range for all intervals. The lowest value was 3.8x 10¬5years in Interval 8and the highest value was1.1x 107years in Interval 6. Grains with the highest solar wind damage rim thicknesses and SEP track densities are found in Interval 6.The highest rim thickness and track density observed for anorthiteis126.5 nm and4.7 x 1011tracks/cm2, while for olivine they are 98.6 nm and 1.83 x 1011tracks/cm2, respectively. Discussion: Intervals from the top 4 cm of 73002 show similar SEP track density and solar wind damaged rim thickness distributions. Spectral and ferromagnetic resonance measurements of 73002 indicate an in-situ reworking zone up to~8 cm below the surface[5,6].The depth analyzed in this work is within the core’s uppermost in-situ reworking zone and may serve as an explanation to the homogenous distribution of exposure ages. The decreasing abundance of space weathered features with depth is consistent with regolith mixing models showing an exponential decay in regolith maturity with depth over time[7].A maximum surface exposure age determined via SEP track density is approximately 10million years. This timescale is consistent with the lower estimate of surface exposure ages of the light mantle determined in previous studies, which can range from 10s to over 100 Ma [4].It also falls within the core regolith reworking development timescale of ~17 Ma [5,6]. Additional analysis will be performed for a further seven intervals in 73002.

J A McFadden↗
NASA NTRSDate not supplied

X-Ray Computed Tomography of Apollo Drive Tube 73001 as Part of the Apollo Next Generation Sample Analysis Program

Introduction: Starting in 2019, the Apollo Next Generation Sample Analysis (ANGSA) Program has enabled consortium studies of specially curated Apollo samples that were previously unstudied (or under studied). This program was intended as a participating scientist program for these Apollo samples, as well as a preparation for upcoming lunar sample return missions (e.g., Artemis). The work began with studies of unsealed core tube 73002 [1,2] that is the upper ~35 cm of an Apollo 17 double drive tube (~70 cm total depth) collected on the landslide deposit near Lara Crater at Station 3 in the Taurus Littrow Valley. More recently the program extended to the study of a variety of frozen Apollo 17 samples [3], as well as the gas extraction [4] and dissection [5] of 73001, the lower half of the station 3 double drive tube. Sample 73001 was sealed under vacuum on the Moon in a Core Sample Vacuum Container (CSVC). In this abstract we will examine the role of X-ray Computed Tomography (XCT) during the preliminary examination process for sealed core 73001, including: (1) engineering scans to aid in understanding the gas extraction process, (2) whole-core scanning prior to opening to inform extrusion and dissection work, and (3) individual particle scanning to characterize rock fragment lithologies for follow on studies. Methodology: Sample 73001 is a 33 cm long, 4 cm diameter regolith sample collected inside a lunar drive tube (~1 mm aluminum walls). That drive tube was sealed inside a 0.5 mm thick stainless steel (SS) CSVC. XCT scans for engineering purposes were done on the Nikon XTH 320 system at Johnson Space Center using the 225 kV multi-metal reflection source at 215 kV, 179 A, and a 38.49 m voxel size. Individual >4 mm particles separated from the core during processing (then triply sealed in Teflon bags) were also scanned at JSC using the 180 kV source at 90 kV, 33 A, and a 2.98 – 10.65 m voxel size. Whole-core scans were done at the University of Texas High-Resolution X-ray Computed Tomography Facility (UTCT) on the 225 kV reflection source on the North Star Imaging cabinet XCT system. These scans included: (1) a series of 9 overlapping super-resolution scans each covering a ~4 cm length of the tube at 190 kV, 180 µA, and a 12.9 µm voxel size and (2) a lower resolution continuous helical scan of the entire core at 190 kV, 180 µA, and a 51.8 µm voxel size. Progress and Results: Before piercing and extracting the gas from sample 73001, an XCT scan of the bottom portion of the CSVC was used to confirm the location of the Teflon cap on the inner drive tube and whether there was an “air” gap between the Teflon cap and the CSVC. This was to ensure the Teflon cap (which immobilized the soil inside the drive tube) was not accidentally pierced during gas extraction. Similarly, after piercing, the bottom and top portions of the CSVC were scanned in order to capture engineering knowledge about the results of the piercing process, as well as the metal knife edge vacuum seal (SS into an In-Ag alloy). Both scans will provide constraints on future work of this type, both for the design of tools used on the lunar surface during Artemis, as well as how we open future samples of this type. An unexpected finding from these engineering scans was that the device in the drive tube that immobilizes the regolith (the keeper) was not seated in the tube properly. This meant that (1) the drive tube could not be removed from the CSVC for the trip to UTCT, and (2) the procedure for opening and extruding the drive tube had to be modified. Had either of these things not been known prior to opening the CSVC, it could have led to an inability to XCT scan the whole core at high resolution and/or potential disruption of the core stratigraphy during extrusion. At UTCT, the entire length of the core was scanned at high resolution (12.9 microns per voxel). This scan serves multiple purposes: (1) A lower resolution (and uncorrected) version of these scans stitched together was used to help inform the processors of potential pitfalls during extrusion and dissection (voids, angular fragments at the edges of the sample, etc.); and (2) the full resolution corrected data will serve as the permanent in situ record of the stratigraphy of the sample and will enable future researchers to perform a variety of analyses. All 121 >4 mm particles separated during dissection pass 1 of sample 73001 have been individually scanned. These scans clearly show the lithology of each particle while keeping the particles in pristine condition (they are individually triply bagged in Teflon within our N2 purged processing cabinets). Because of the dust adhering to particle exteriors, it would otherwise be impossible to determine lithologies in a non-contaminating way. Thus far the types of lithologies seen in sample 73001 (e.g., regolith breccias, impact-melt breccias, agglutinates, and bas-alts) are similar to those previously identified in sample 73002 [2]. By the time of the meeting, all particles from all 3 dissection passes will have been scanned and statistics on the different lithologies in 73001 compiled. References: [1] Shearer et al. (2020) 51st LPSC, abstract 1181. [2] Zeigler et al. (2020) 51st LPSC, abstract 3023. [3] Kent et al. (2022) This Volume. [4] McDonald et al. (2022) European Lunar Symposium. [5] Gross et al (2022) This volume.

Moon↗
NASA NTRSDate not supplied

From Apollo to Artemis: How Processing ANGSA Core Samples 73001/2 Can Help to Prepare for Future Sample Return Missions to the Moon and Beyond.

Introduction: Apollo Sample 73001/2 is a ~71cm long double drive tube consisting of an upper part (73002) and a lower part (73001) that contains regolith collected near Lara Crater at the Apollo 17 site, Station 3. The double drive tube is believed to have penetrated a lunar landslide deposit that was transported from the slope of the South Massif into the Taurus-Littrow Valley [1]. As part of the ANGSA (Apollo Next Generation Sample Analyses) initiative, preparing a preliminary examination (PE) catalog of 73001/2 is a crucial first step for the early identification of material types such as rock fragments and potential stratigraphy within the core. Many new curation and scientific tools such as X-ray computed tomography (XCT) [3], multi-spectral imaging [4], and gas extraction manifold with piercing tool [5-7], have been applied to the ANGSA core to benefit curation strategy, PE efforts, sample allocation to the planetary science community, and ultimately help to prepare for future sample return missions like Artemis. 73001/2 Preliminary Examination and Processing: Sample 73002 was successfully opened and extruded in Nov. 2019 and fully dissected at the end of 2021. Sample 73001 (Fig. 1) was successfully extruded in March 2022 after careful planning before opening the Core Sample Vacuum Container (CSVC) that was holding the drive tube of 73001. XCT, as part of PE, was used to scan the bottom and top part of the 73001 core tube within the CSVC prior to opening it to 1) facilitate non-destructive, rapid detection of any contamination potentials due to piercing of the CSVC during gas extraction [7]; and 2) to aid in the Artemis sample tool development and provide data on the knife edge seal of the CSVC. This knowledge will help us connect the mechanics of the implemented design (i.e., XCT data) to the performance of the seal (i.e., data on the gas samples will tell us how well the seal preserved the volatile record of lunar samples). Both type of information will feed forward into Artemis tool and storage strategies for future samples. Results and Lessons learned: The XCT data of the CSVC and core tube within showed that the bottom Teflon cap was not pierced during gas extraction (Fig. 1c) and thus, the sample integrity remained guaranteed during piercing and subsequent gas extraction. However, the XCT scan of the top of the core (Fig. 1b) revealed that the drive tube was overfilled with lunar soil and the tool that keeps the soil constrained within the drive tube was not fully deployed. These preliminary data allowed us to implement the necessary steps to prevent loss of sample integrity, including any potential stratigraphy shifts during extrusion. Processing Apollo core 73001/2, creating an informative PE catalog, and applying new and refined tools and technologies for sample analyses are invaluable activities that will assist in circumventing any potential pitfalls, aid in the characterization of samples, and help in the assessment of how well any lunar material has been collected and preserved in the past. This will aid in designing future sample collections and curation procedures and help to prepare for future human exploration and sampling missions such as Artemis. References: [1] Schmitt H. (2017) Icarus 298, 2-33. [3] Zeigler et al. (2021) LPSC 52nd, #2632; [4] Sun et al. (2021), LPSC 52nd, #1789; [5] Parai et al. (2021), LPSC 52nd #2665; [6] Schild et al. (2021) LPSC 52nd #1888; [7] McDonald (2022) ESL 2022.

ANGSA↗
NASA NTRSDate not supplied

Investigation of Geomorphological Signatures of Permafrost in the Polar Lunar Areas With VIPER

A study of images of the polar regions shows that small craters near the poles of the Moon are distinguished by the following features: 1. they have a smoother shape - see Fig (a); 2. patterned ground (“wrinkled skin”) is often observed in and around the crater - see Figs (a,b,c); 3. outside the craters landslides and cracks are noticeable - see Fig (d); 4. layers or scarps are often visible on the inner slope - see Fig (e). These features (scarps and patterned ground) are typical for Martian craters in the permafrost zone (see Fig f), as well as for similar zones on Earth. It is hypothesized that these features of lunar craters are associated with the presence of permafrost in the polar regions of the Moon. In 2023, the VIPER rover will investigate the distribution of ice (volatile) deposits in the region of the Moon's South Pole. VIPER navigation cameras represent a unique opportunity for the geomorphological analysis of the lunar surface and the study of physical properties of regolith due to multiple key factors: - A large number of high-quality digital images with a good resolution of the South Pole of the Moon, which is a key region for the landing of manned expeditions. - A low position of the Sun, which generates long shadows, creates favorable conditions for object recognition algorithms. - A presence of a rover track in the images enables VIPER wheels to be used as tools for the study of the regolith and the development of a geotechnical model of regolith in the South Pole region. Rover navigation cameras will allow investigation of the distribution and shape of small craters and other structures along the path of the rover and test the hypothesis about geomorphological signatures of permafrost in the lunar polar areas. If a relationship between characteristics of lunar craters and the distribution of permafrost is confirmed, this will open a possibility to remotely determine the deposits of lunar ice from satellite imagery.

VIPER↗
NASA NTRSDate not supplied

Microstructural Characterization of Felsite Fragments From the Apollo Next Generation Sample Analysis (ANGSA) Double Drive Tube 73001/73002

While the Moon’s surface is dominated by mafic igneous products formed through the crystallization of the lunar magma ocean, and the subsequent eruption of mare basalts – felsic magmatic fragments (variably referred to as felsites, granites, rhyolites or granophyres) have been identified from a number of Apollo samples (e.g. 12013[1], 14321[2], 15405[3] and 73215[4]). Magmatic edifices like the Gruithuisen Domes – silicic constructs sometimes found proximal to the basaltic mare provinces filling nearside basins, may represent a petrogenetic origin. However, this is, is complicated by the fact that they apparently predate mare volcanism (e.g. [5]). Additionally, crater-counting indicates that these silicic surface features also postdate radiogenic ages of Apollo felsites [6]. Various modes of felsic magmatism have been invoked to explain the presence of felsic lithologies on the Moon, including: 1) fractional crystallization and silicate liquid immiscibility; 2) partial melting of lunar crust through basaltic underplating; and 3) fractional crystallization of the mare parent magmas. Although these models are plausible, based on known Apollo samples and lunar meteorites, they are complicated by the lack of sample lithologies with intermediate composition between basaltic magmas and the felsic components, and the fact that partial melting of many crustal rock types on the Moon (e.g., anorthosite, troctolites) are unlikely to form granites. Along with other unique magmatic lithologies, new felsites have been identified within the < 1 mm size fractions of the ANGSA double drive core tube (73001/73002) from Apollo 17 station 3, sampling the light mantle landslide deposit from the South Massif [7]. These additional examples of lunar felsite will help us to better constrain the processes that lead to the formation of these evolved lithologies. To do this, we have employed a gambit of high-resolution scanning electron microscopy (SEM) and scanning transmission electron microscopy (TEM) analytical techniques, including electron backscatter diffraction (EBSD), cathodoluminescence and high-angle annular dark field (HAADF) imaging. These data provide unique insights into the felsite mineralogy and microstructures including the coexistence of quartz and tridymite in many of the fragments. In addition, these analyses provide petrological context and assist targeted in situ secondary ion mass spectrometry (SIMS) measurements of the U-Pb systematics of accessory minerals, and the volatile abundances and D/H ratios of apatite grains identified within the clasts.

lunar↗
NASA NTRS2023

Diverging Trends in Rain-on-Snow Over High Mountain Asia

Rain-on-snow (ROS) over snow-dominated regions such as High Mountain Asia (HMA) modulates snowmelt and runoff and is key contributor in influencing water availability and hazards (e.g., floods and landslides). We studied the trends in ROS in HMA over the past two decades from 2001 to 2018 using the land surface model Noah-MP driven by an ensemble precipitation data set. Our results show that changes in precipitation phase and rainfall are altering ROS. Because of the strong physical heterogeneity and atmospheric dynamics of HMA, ROS characteristics and trends are region-dependent and ROS occurs predominantly over the Indus, Ganges-Brahmaputra, and northwestern basins. In the Indus, ROS representing ∼5% of the annual precipitation and ∼20% of the annual snowmelt, has an increasing trend. This is contrary to the Ganges-Brahmaputra characterized by decreasing ROS trends, where it represents ∼11% of the annual precipitation and ∼60% of the annual snowmelt. In the northwestern basins, ROS has bidirectional trends due to elevation patterns and trends in rainfall, and it constitutes ∼5 to ∼10% of the annual precipitation. Increasing trends in ROS over Indus contribute to reducing the snowpack in late summer, with concerns of reduced water availability and increased groundwater exploitation. Similarly, because of its high amount and contribution to snowmelt, the decreasing ROS trends in the Ganges-Brahmaputra will have consequences of decreased recharge from the headwaters and exacerbated use of groundwater unless increasing trends in rainfall compensate for the decreasing snowmelt. These results provide new insights on ROS-driven changes in the hydrological cycle over HMA.

rain-on-snow↗
NASA NTRSDate not supplied

Coronado Ecological Conservation: Assessing Vegetation Change Due to Border Wall Construction and Shifting Social Trails

Species monitoring is essential in mitigating the impacts of plant invasion, such as radical changes in an area’s ecosystem, degraded soil health, increased wildfire severity, landslides, and increased flooding. NASA DEVELOP partnered with the National Park Service (NPS) to investigate invasive species in disturbed lands: specifically, areas affected by off-trail walking and US-Mexico border construction activities. The team assessed how construction has impacted the distribution of Lehmann’s lovegrass and Russian thistle invasives throughout Coronado National Memorial, AZ from 1986 to 2022. Using data from Landsat 5 and 8, Sentinel-2, the National Agriculture Imagery Program, and PlanetScope, the team computed vegetation indices including the Normalized Difference Vegetation Index, Normalized Difference Moisture Index, Modified Soil Adjusted Vegetation Index 2, Enhanced Vegetation Index, and Tasseled Cap Wetness, Brightness, and Greenness transformations as vegetation health indicators to input into various machine learning algorithms. To minimize noise, the team conducted Principal Component Analysis on the vegetation indices and spectral bands before running k-means++ clustering and random forest classification algorithms. Between all datasets, we found the median area fully overtaken by invasive plants was 5.37% of the park’s total area in 2022. The NPS will use the end products to help increase restoration efforts in disturbed areas with high concentrations of invasive plants. The NPS’s collection of ground data for 2022–2023, in conjunction with future data collection, will notably improve the accuracy of classification models, leading to more precise monitoring of invasive spread over time.

Carson Schuetze↗
NASA NTRS2023

Coronado Ecological Conservation: Assessing Vegetation Change Due to Border Wall Construction and Shifting Social Trails

Species monitoring is essential for mitigating the impacts of plant invasion, such as radical changes in an area’s ecosystem, degraded soil health, increased wildfire severity, landslides, and increased flooding. For this project, NASA DEVELOP partnered with the National Park Service (NPS) to investigate invasive species in disturbed lands: specifically, areas affected by off-trail travel and U.S.-Mexico border construction activities. The team assessed how construction has impacted the distribution of Lehmann’s lovegrass and Russian thistle invasives throughout Coronado National Memorial, AZ from 1986-2022. Using data from Landsat 5 and 8, Sentinel-2, NAIP, and PlanetScope, the team computed NDVI, NDMI, MSAVI2, EVI, and Tasseled Cap Wetness, Brightness, and Greenness transformations as vegetation health indicators to input into various machine learning algorithms. To minimize noise, the team conducted Principal Component Analysis on vegetation indices and spectral bands before running k-means clustering and random forest classification algorithms. Between all datasets, the team found that the median area fully overtaken by invasive plants was 5.37% of the park’s total area in 2022. The NPS will use end products to help increase restoration efforts in disturbed areas with high concentrations of invasive plants, and this project can serve as a jumping off point for future invasive species monitoring. The NPS’s collection of ground data for 2022-2023, in conjunction with future data collection, will notably improve the accuracy of classification models, leading to more precise monitoring of invasive species spread over time.

Coronado National Memorial↗
NASA NTRSDate not supplied

Assessing the Needs of NASA's Near Real-Time Earth Observation Products

"The 2017-2027 Decadal Survey for Earth Science and Applications from Space stated that NASA's Earth Science with planned implementation of applications provides sustained earth observations for societal benefits [1]. The Decadal Survey indicated that data latency is invaluable for time-sensitive applications including disaster risk reduction, wildland fire carbon emissions quantification, real-time measurements of the state of the hydrologic systems and many more. Data latency refers to the time between earth observation and data products available to users. During the past 13 years, NASA's Land, Atmosphere Near Real-Time Capability for Earth Observing Systems (LANCE) continues to provide free access to earth observation products that are made available much quicker than routine processing allows. The latency of most LANCE data products is Near Real-time (NRT) which is defined as less than three hours from satellite observations [2]. LANCE is managed by the Earth Science Data and Information System (ESDIS) Project at NASA Goddard Space Flight Center [3], and a User Working Group (UWG) is responsible for providing guidance to LANCE. LANCE data are used by direct users and brokers who add value to the data [4]. NASA Earth Applied Sciences Program (ASP) is one of the primary users of LANCE, which collaborates with partner organizations and provides support to scientists to solve problems in applications of earth observations. ASP promotes the use of LANCE NRT data products to demonstrate applications in decision making, facilitates end-user feedback to the science team to improve data products, and provides information on future demands for research. LANCE supports applications that need a rapid response including detecting wildland fires and volcanic eruptions, tracking smoke, ash and dust plumes, monitoring air quality and tracking extreme weather events such as hurricanes, landslides, and floods. To gather feedback regarding the availability, accessibility and actionability of NASA's NRT data products for societal benefit, three surveys and a few discussions with experts involved in the topic within ASP were conducted from the perspective of users. Feedback has been collected from users who are interested in using low latency NASA data within application communities of agriculture, disasters, water resources, health and air quality, ecological conservation, wildland fires and capacity building. Analysis-ready NRT data products in a variety of formats have been mentioned many times in the collected feedback, especially for applied users with little to no experience using research-grade earth observation products. Users prefer to have products that can be easily integrated into their existing workflows and take their analysis to the data. HDF5 is a commonly used data format for research, but typically requires some conversion to a more friendly format for applications and regular use in decision-making. Users prefer the GeoTIFF data format that can be directly ingested into a GIS mapping software and platform for data analysis and visualization. For example, LANCE’s fire, flood, SO2 and Black Marble Nighttime Blue/Yellow Composite data products have been integrated into NASA Disasters Mapping Portal, which is an GIS-based open data portal, for users in the disaster management community. There are 291 LANCE NRT layers available through GIBS and Worldview, where users can download a snapshot in GeoTIFF format. Operational users expect data to be processed as close to the user as possible. The collected feedback indicates that LANCE fire products within 3 hours latency would meet the needs of the wildland fire community. The ideal latency for volcanic application is 10-15 minutes. Users in Volcanic Ash Advisory Centers (VAAC) reported that the first forecast volcanic product should be issued within 75 minutes from the volcano eruption [5]. Overall, for disaster applications, data latency within 3 hours is useful while latency greater than 12 hours is not timely enough for operational use. Capacity building and training are critical for users to be able to access, interpret and use data products and tools for their decision making, especially for applied users with limited experience using earth observation products. LANCE data products have been used in a number of capacity building projects domestically and internationally [6]. As LANCE continues to bring new products into the system, users request training to utilize LANCE new and upcoming data products and capabilities in their applications. Due to the limitation of bandwidth and downstream flow paths, users in some developing countries need tools to select and download data for a specific area of interest instead of bulk downloads. The collected feedback also shows the lack of available SAR satellite low latency data products. The advantages of SAR to monitor conditions and changes on the ground through darkness, clouds, volcanic ash, and other atmospheric conditions, are appealing to low latency users. For example, terabytes of low latency but cloudy optical images are not helpful in rapidly identifying the extent of flood or fire impacts. LANCE could be complemented with low latency measurements via the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission [7]. Requests for higher spatial resolution products are expressed. A user from the wildland fire management community reported that products with 30-m spatial resolution could be used to detect small fires. The 30-m Landsat OLI fire data is now part of NASA’s Fire Information for Resource Management System (FIRMS) US/Canada [8]. Within the open and free NASA resources, LANCE disseminates NRT data products in a manner that allows them to be accessible and understandable to both scientific and applied users. In many application areas, latency plays an important or even decisive role where low latency earth observations help people to observe areas of interest, detect and track changes in the environment and make timely decisions. NASA’s Earth Applied Sciences Program promotes the use of LANCE NRT products and builds a bridge between application users and research teams. The collected feedback indicates data latency within 3 hours is useful for most of the applications, and shows the needs of user-friendly, analysis-ready products, and requests training on LANCE’s new and upcoming data products. User feedback has been provided to LANCE UWG for guidance and recommendations, and for translating findings into something actionable.

Tian Yao↗
NASA NTRS2023

Designing an Observing System to Study the Surface Biology and Geology (SBG) of the Earth in the 2020s

Observations of planet Earth from space are a critical resource for science and society. Satellite measurements represent very large investments and United States (US) agencies organize their effort to maximize the return on that investment. The US National Research Council conducts a survey of Earth science and applications to prioritize observations for the coming decade. The most recent survey prioritized a visible to shortwave infrared imaging spectrometer and a multispectral thermal infrared imager to meet a range of needs for studying Surface Biology and Geology (SBG). SBG will be the premier integrated observatory for observing the emerging impacts of climate change by characterizing the diversity of plant life and resolving chemical and physiological signatures. It will address wildfire risk, behavior, and recovery as well as responses to hazards such as oil spills, toxic minerals in minelands, harmful algal blooms, landslides, and other geological hazards. The SBG team analyzed needed instrument characteristics (spatial, temporal, and spectral resolutions, measurement uncertainty) and assessed the cost, mass, power, volume, and risk of different architectures. We present an overview of the Research and Applications trade-study analysis of algorithms, calibration and validation needs, and societal applications with specifics of substudies detailed in other articles in this special collection. We provide a value framework to converge from hundreds down to three candidate architectures recommended for development. The analysis identified valuable opportunities for international collaboration to increase the revisit frequency, adding value for all partners, leading to a clear measurement strategy for an observing system architecture.

Observing System↗