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361 records · Page 6Linked to original sources
USGS2026

Late Miocene Colorado River arrival in the Bidahochi basin supports spillover origin of Grand Canyon

The timing and mechanism of the integration of the Colorado River and incision of the Grand Canyon remain among geology’s enduring controversies. A key question is the configuration of the upper Colorado River watershed between 11 and 6 million years ago. In this study, we present new evidence from zircon uranium-lead geochronology for the arrival of distinctive Colorado–Green River sediment in the Bidahochi basin by 6.6 million years ago derived from the Browns Park Formation. This is coeval with an order-of-magnitude increase in depositional rate, an increase in carbonate strontium isotope ( 87 Sr/ 86 Sr) ratios, the appearance of large fish species characteristic of fast-flowing waters, and other sedimentological changes. This evidence is consistent with the Colorado River supplying water and sediment to the Bidahochi basin before spillover integration of the river through the Grand Canyon.

Arizona, Nevada, Utah↗
USGS2024

A conceptual framework to assess post-wildfire water quality: State of the science and knowledge gaps

Wildfire substantially alters aquatic ecosystems by inducing moderate to catastrophic physical and chemical changes. However, the relations of environmental and watershed variables that drive those effects are complex. We present a Driver-Factor-Stressor-Effect (DFSE) conceptual framework to assess the current state of the science related to post-wildfire water-quality. We reviewed 64 peer-reviewed papers using the DFSE framework to identify drivers, factors, stressors, and effects associated with each study. A total of five drivers were identified and ranked according to their frequency of occurrence in the literature: atmospheric processes > fire characteristics > ecologic processes and characteristics > land surface characteristics > soil characteristics. Commonly reported stressors include increased nutrients, runoff, and sediment transport. Furthermore, although several different factors have been used at least once to explain water-quality effects, relatively few factors outside of precipitation and fire characteristics are frequently studied. We identified several gaps indicating the need for long-term monitoring, multi-factor studies, consideration of organic contaminants, consideration of groundwater, and inclusion of soil characteristics. This assessment expands on other reviews and meta-analyses by exploring causal linkages between influential variables and overall effects in post-wildfire watersheds. Information gathered from our assessment and the framework itself can be used to inform future monitoring plans and as a guide for modeling efforts focused on better understanding specific processes or to mitigate potential risks of post-wildfire water quality.

Water Resources Research↗
USGS2026

A 481 m-high landslide-tsunami in a cruise ship-frequented Alaska fjord

Early in the morning of 10 August 2025, a >64 × 10 6 –cubic meter landslide struck Tracy Arm fjord in Alaska. The landslide was preconditioned by glacial retreat caused by climate change. The resulting 481-meter runup megatsunami followed an initial 100-meter-high breaking wave traveling at >70 meters per second. The landslide was preceded by several days of microseismicity, which increased in rate and magnitude until ~1 hour before failure. The landslide produced globally observed long-period seismic waves equivalent in size to a moment magnitude 5.4 earthquake. A long-period (~66 second) global seismic signal, produced by a landslide-induced seiche trapped within the fjord, persisted for up to 36 hours, the second time a days-long seiche had thus been observed. With fjord regions increasingly visited by cruise ships, and climate change making similar events more likely, this unanticipated, near-miss event highlights the growing risk from landslides and tsunamis in coastal environments.

Alaska↗
USGS2025

Scoping decision-maker needs and science availability to support regional natural capital accounting in the U.S. Colorado River Basin

Natural capital accounting has the potential to yield important policy insights at multiple scales, but there remains a disconnect between regional-scale natural capital accounts and their use for informing policy. In this paper, we propose a roadmap that could lead to the creation of policy-relevant regional accounts, with steps split across an initial scoping phase and a subsequent development phase. We demonstrate the scoping steps in action with an application to the Colorado River Basin (“Basin”), a large watershed in the southwestern United States (U.S.) that has faced aridification and substantial high-profile tradeoffs around the use of its water and other natural resources. Drawing on prior U.S. Geological Survey science co-production efforts, we conducted a series of eight discussion sessions with 41 scientists and science representatives whose work is relevant to Basin water, riparian and riverine ecosystems, upland ecosystems and energy and minerals. We summarise participants' thoughts on key topics and economic linkages, their insights and questions of interest and their recommendations on existing scientific data sources and gaps. We evaluate the suitability of the available data for construction of System of Environmental-Economic Accounting (SEEA) Central Framework and SEEA Ecosystem Accounting accounts, including those for land, water, forests, energy and minerals and ecosystems (covering extent, condition and ecosystem services). We present a series of lessons learned during the scoping phase, as well as lessons that could be relevant for future practitioners engaging in the development phase. The information can help guide the development of timely and relevant regional-scale environmental-economic accounts in the U.S. and beyond.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2025

Geologic framework and Holocene sand thickness offshore of Seven Mile Island, New Jersey

The U.S. Geological Survey assessed the Quaternary evolution of Seven Mile Island, New Jersey, to quantify coastal sediment availability, which is crucial for establishing sediment budgets, understanding sediment dispersal, and managing coastlines. This report presents preliminary interpretations of seismic profiles, maps of Holocene sand thickness from the shoreline to 2 kilometers offshore, and tables quantifying the volume of available sediment along the coastal margin based on data collected during 2021 and 2022. The results reveal spatial variability in the thickness and cross-shore extent of Holocene sand. The study area was separated into northern, central, and southern zones by using underlying stratigraphy and geomorphic features. The characteristics and spatial extent of the Holocene sand deposit indicate that hydrodynamic processes contribute to its spatial variability. Northern Seven Mile Island contains the thickest deposits of Holocene sand that were formed by sediment bypass around the Townsends Inlet ebb-tidal delta. Specifically, swash bars have welded to the updrift end of Seven Mile Island and have formed thick deposits of Holocene sand that thicken landward and taper seaward. Despite their thickness, these deposits have the smallest cross-shore extent; therefore, northern Seven Mile Island has the smallest volume of Holocene sand of the three geomorphic zones. Central Seven Mile Island has the thinnest Holocene sand deposits because this section of the barrier island is outside the influence of ebb-tidal deltas. Southern Seven Mile Island has the greatest volumes of Holocene sand because of increased accommodation and deposition adjacent to the Hereford Inlet ebb-tidal delta. Even though tidal inlets exert variable influence on the three geomorphic zones, sediment is distributed fairly uniformly within each geomorphic zone; each of the three zones contains 31.05–36.48 percent of the volume of available Holocene sand.

New Jersey↗
USGS2025

Using visualization science to inform the design of environmental decision-support tools—A case study of the U.S. Geological Survey Waterwatch

Environmental decision-support tools are increasingly being used to serve both expert and non-expert audiences. Many existing tools are primarily expert-focused, and redesigning them can be challenging because experts and non-experts interact with tools differently, existing users may be resistant to changes, and there is little guidance on how to prioritize redesign efforts and demonstrate their efficacy. In this report, we present a case study of a user-centered redesign of an established environmental decision-support tool—the U.S. Geological Survey WaterWatch. WaterWatch supports flood, drought, and other water resource management decisions through the display of water levels at gages across the United States. Using a participatory process, we identified a functional change (replacing the existing rainbow colormap), created an alternative design, and tested the alternative’s usability through two general public surveys. The results showed that replacing the rainbow colormap with a more intuitive diverging colormap improves usability, regardless of the audience’s subjective preference for the rainbow color scheme. In addition, we demonstrated the importance of using legends to improve the audience’s understanding of the map symbols. This study demonstrates how user-centered design approaches can be used to inform the design of high-profile products and tools.

Scientific Investigations Report↗
USGS2024

Prioritizing US Geological Survey science on salinization and salinity in candidate and selected priority river basins

The US Geological Survey (USGS) is selecting and prioritizing basins, known as Integrated Water Science basins, for monitoring and intensive study. Previous efforts to aid in this selection process include a scientifically defensible and quantitative assessment of basins facing human-caused water resource challenges (Van Metre et al. in Environmental Monitoring and Assessment , 192(7), 458 2020). In the present work, we explore this ranking process based on water quality considerations, specifically salinity and salinization. We selected top candidate basins to study salinity and salinization issues in 18 hydrologic regions that include 163 candidate basins. Our prioritization is based on quantitative assessment of sources of salinity, drivers of change, and receptors that must respond to those sources and drivers. Source terms represented in the prioritization include geology, depth to brackish groundwater, stream conductivity, chloride in precipitation, urban and agricultural land use, application of road salt as a deicer, and irrigation. Drivers represented in prioritization include changes in chemical weathering as a result of changes in rainwater chemistry. Receptors include measures of water stress, measurements of stream ecological health, and socioeconomic factors. In addition, we present research activities for the USGS on salinity and salinization that can be pursued in these basins including assessment of sources, pathways, and loadings; predicting and understanding changes in sources, peaks, and trends; understanding the components of salinity and mobilization of contaminants; understanding the relationship between salinization and changing ecosystems; and developing knowledge on the causes and distribution of groundwater salinity, brackish water resources, and challenges related to desalination.

Enviornmental Monitoring and Assessment↗
USGS2025

A newly identified creeping strand of the Concord fault, San Francisco Bay Area

The Concord fault constitutes a major branch of the Pacific–North America transform plate boundary in Northern California, bridging the strike‐slip Bartlett Springs ‐ Green Valley Fault system to the north with the Greenville and Calaveras Faults to the south. Like many faults in the San Francisco Bay Area its long‐term slip is partially accommodated by aseismic slip (creep). Although creep has been recognized and monitored on the northern half of the fault for decades, the precise location of the southern half of the fault and its slip rate—whether accommodated seismically or aseismically—has remained enigmatic. How slip transfers between the Concord and Greenville or Calaveras faults to the south remains an outstanding question. New field observations presented here indicate that the active trace of the fault south of downtown Concord is not where previously interpreted and is indeed actively creeping. We report observations of shallow creep continuing >7 km farther south along the Concord fault than previously reported, along a fault strand not previously recognized for most of its length. This is evident as right‐laterally deflected concrete curbs and sidewalk slabs on both sides of every street that crosses the fault at a high angle in southeast Concord and northeast Walnut Creek. We document the magnitude and location of these deflections to estimate accumulated right‐lateral aseismic slip expressed in engineered structures. Offsets of these piercing lines range from 8 to 18 cm, over widths varying from narrow breaks along centimeter‐scale concrete joints to 10‐m‐wide zones of deflection. Significantly, this active trace is ∼400 m west of where the Quaternary active trace has previously been inferred, placing it within—rather than bounding—the built area of suburban Concord. Slip along the fault has already caused infrastructure damage. These results revise our understanding of the southern Concord fault and help constrain its seismic potential.

California↗
USGS2026

SlideDetect: Spatio-temporal landslide detection using a three-dimensional convolutional neural network

Landslides pose a serious and ongoing threat to both human lives and infrastructure worldwide; therefore, it is of interest to predict where and when landslides are likely to occur. Advances in machine learning techniques have spurred numerous studies aimed at estimating relative landslide propensity, but are limited to spatial (as opposed to temporal) prediction due to the sparsity of landslide timing data. We address this data gap by training SlideDetect, a 3-dimensional convolutional neural network (3D CNN), to identify landslides based on their spatial and temporal occurrence within multitemporal image stacks. We use an inventory of landsides triggered by the 2018 Hokkaido earthquake and two years of monthly composite optical imagery spanning this event. The model can identify not only landslide location but also landslide date with an area under the precision-recall curve (PR-AUC) of 0.84. We further present a new standard for presenting PR curve results that explicitly compares model performance at different confidence thresholds, allowing for clearer model evaluation and comparison. Our new approach to constraining landslide timing paired with this more consistent and objective method for evaluating model performance shows considerable promise, and with further application and testing, SlideDetect could enhance the data availability and tools needed to advance landslide hazard and risk assessments.

JGR Machine Learning and Computation↗
USGS2026

Towards a refined definition of “tidal influence” for the coastal wetland sciences

The astronomical tide relates to lunar (and to a lesser extent solar) influences on rising and falling water bodies, and is a key control of many coastal processes. However, tides manifest along coastal margins in different ways to muddle application beyond Sir Isaac Newton’s first descriptions. Here, we argue that tide, or specifically “tidal,” has not been adequately defined for the coastal wetland sciences to facilitate contemporary interdisciplinary distinction for rapidly changing coastlines and future climate adaptation planning. We provide a brief history of the tidal concept, and we describe tides in a diversity of uncommonly recognized marginal coastal environments. Common astronomical tide manifestations are described through hydrographic examples, then expanded to include those tidal environments exposed additionally to fluvial, meteorological (wind), or groundwater influences. Our expanded definition of “tidal” is intended to be a forward-looking construct as environments will inevitably change with sea-level rise, water extraction, and anthropogenic flow alteration. Our definition of wetland tidal influence, which we broaden, includes those “wetlands affected by astronomic water level fluctuations within coastally restricted environments causing frequent or infrequent surface inundation or groundwater tidal variation that affects the biogeochemistry of the soil (e.g., ion exchange capacity, oxygen state, mineralization processes)”. Astronomic water level fluctuations are often amplified or dampened by non-astronomical events, such as wind. Expanding the definition of what is considered tidal by the scientific community is critical for improved understanding of coastal wetland function and the suite of ecosystem services they provide people and society, including climate mitigation opportunity, management, and adaptation.

Wetlands↗
USGS2025

Cascading land surface hazards as a nexus in the Earth system

Earth’s surface is sculpted by numerous processes that move sediment, ranging from gradual and benign to abrupt and catastrophic. Although infrequent, high-magnitude sediment mobilization events can be hazardous to people and infrastructure, leaving topographic imprints on the landscape and remarkable narratives in the historical record. Hazardous events such as fires, storms, and earthquakes accelerate erosion and sediment transport, increasing landscape sensitivity to subsequent perturbations, thus forming a cascading hazard. Although the redistribution of sediment across Earth’s landscape can result in higher risks to vulnerable populations, cascading processes are commonly unaccounted for in hazard assessments. Cascading hazards can occur almost immediately after triggering events, such as coseismic landslides, or over months, years, or even decades after an initial perturbation, such as debris flows after wildfires or flooding in channels alluviated by volcanic debris. Sediment cascades span Earth’s surface, from mountaintops to river valleys, where erosion, deposition, and aggradation can lead to a myriad of hazardous processes, including decreased river conveyance capacity, which increases the likelihood of downstream flooding. An improved understanding of the magnitude, frequency, and persistence of cascading hazards is critical given the rapid changes in the frequency and severity of storms, fires, sea-level change, and cryospheric melting, as well as the expansion of high-population-density urban footprints in regions susceptible to solid Earth hazards. Understanding the full consequences and underlying physics of Earth’s cascading land surface hazards can help minimize future human and economic losses.

California↗
USGS2025

Scientific opportunities in the National Landscape Conservation System

The National Landscape Conservation System consists of unique and beautiful places across America’s landscapes where identified resources and values are protected and science is highlighted. The mission of the National Landscape Conservation System (NLCS), which is managed by the Bureau of Land Management and is often referred to as the agency’s National Conservation Lands, is to conserve, protect, and restore nationally significant landscapes for their cultural, ecological, and scientific values. This clear inclusion of science in the NLCS mission sets the stage for individual units to serve as places of learning, teaching, discovery, and innovation. Science is an integral part of managing the National Conservation Lands, and science conducted within and across the more than 900 units that make up the NLCS can inform and influence conservation and public land management well beyond its boundaries. Here, we highlight seven core aspects of National Conservation Lands that present valuable science opportunities: (1) the scientific values for which individual units are designated; (2) the many other resources, objects, and values within units; (3) the value of units as “control” sites for understanding the effects of activities such as mineral extraction that commonly occur elsewhere on multiple-use public lands but are often prohibited within National Conservation Lands; (4) the value of units for studying the effects of activities such as recreation that regularly occur and may be intensified on National Conservation Lands; (5) the high visibility of units, which draws strong interest and engagement from scientists, partners, and the public; (6) the functioning of the units as a network managed for a common purpose, which provides an opportunity to explore cross-cutting science questions across widely varying contexts and geographies; and (7) the opportunities units provide to promote and apply Indigenous Knowledge to scientific research to manage natural and cultural resources. Because of all of these characteristics, National Conservation Lands can serve as hubs for basic and applied science that can inform management of all public lands and resources into the future. We highlight these science opportunities through examples from existing units and suggest two actions that could help further science activities and impact on National Conservation Lands.

Parks Stewardship Forum↗
USGS2026

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi↗
USGS2026

Hyperspectral narrowband imaging spectroscopy: A new paradigm for Earth observation

This editorial introduces the Special Issue entitled “Hyperspectral Narrowband Imaging Spectroscopy: A New Paradigm for Earth Observation” in the August 2026 issue of Photogrammetric Engineering & Remote Sensing (PE&RS), the flagship journal of the American Society for Photogrammetry and Remote Sensing (ASPRS). This volume represents the fourth dedicated hyperspectral special issue published in PE&RS, following earlier contributions by Thenkabail et al. (2025, 2024a, 2024b), and continues ASPRS’s commitment to advancing cutting‑edge imaging spectroscopy research and its applications across Earth system science. Remote sensing is undergoing one of the most profound transformations in its history. The emergence of hyperspectral narrowband (HNB) imaging spectroscopy data, capable of acquiring hundreds of contiguous, narrow spectral bands, has shifted the discipline from observing Earth in a handful of broad spectral windows to capturing continuous spectral signatures of the Planet. This transition marks a decisive break from the multispectral paradigm that has dominated satellite remote sensing for nearly five decades, driven by the advent of new orbital imaging spectrometers such as EnMAP, PRISMA, and NASA’s EMIT, and by the forthcoming Surface Biology and Geology (SBG) mission ((Pires Silva et al., 2026; Bourriz et al., 2025; Thenkabail et al., 2025; Chabrillat et al., 2024; Aneece et al., 2024; Dave et al., 2024; Thenkabail et al., 2024a; Thenkabail et al., 2024b; Thenkabail, 2024a; Thenkabail, 2024b; Thompson et al., 2022; Kokaly et al., 2022; Aneece & Thenkabail, 2022; Cawse Nicholson et al., 2021; Guanter et al., 2021; Vangi et al., 2021; Thenkabail et al., 2021). These missions (e.g., Table 1) deliver unprecedented spectral fidelity, improved signal to noise ratios, and global coverage capabilities, enabling a new era of quantitative, spectroscopy based Earth observation. Where multispectral broadbands (MBBs) provide only a few discrete measurements along the electromagnetic spectrum, HNB systems deliver rich, diagnostic information that enables scientists to characterize Earth’s surface with unprecedented biochemical, biophysical, and structural detail (Figure 1a, 1b). The implications for environmental monitoring, agriculture, water resources, and mineral exploration are profound. Several overarching themes emerge: • Spectral fidelity matters. The ability to preserve subtle absorption features is essential for mineral mapping, vegetation trait retrieval, and biochemical modeling. • AI and deep learning are indispensable. From destriping to classification, modern analytics must be scalable, label‑efficient, and capable of exploiting the full spectral–spatial richness of HNB data. • Physics‑based and data‑driven approaches must converge. Radiative transfer models such as PROSAIL, enhanced with localized soil parameterizations, remain foundational for biophysical retrievals and model‑based inference. • Dimensionality reduction and feature extraction are critical. Techniques such as L1‑ISOMAP demonstrate that intelligent manifold learning can unlock the structure of fused, high‑dimensional datasets. • Next‑generation architectures must be interactive and multimodal. ICTNet exemplifies the future of hyperspectral classification: hybrid, synergistic, and capable of modeling both local textures and global spectral dependencies.

Photogrammetric Engineering and Remote Sensing (PE↗
USGS2026

The eruptive behavior of distributed volcanism forming low shield edifices—A case study of Sentinel-Arlington volcanic field, U.S.A.

Distributed volcanic fields are present in various tectonic settings worldwide, and their characteristics reflect differing influences from magmatic and tectonic processes. In the southwestern United States alone, there are 37 Quaternary distributed volcanic fields. After the primary period of extensional tectonics in the southern Basin and Range 15–5 million years ago, the Sentinel-Arlington volcanic field developed in southwestern Arizona between 4 and 1 million years ago. The Sentinel-Arlington volcanic field consists primarily of low relief shield volcanoes, a type of distributed volcanism with poorly understood temporal evolution. The Sentinel-Arlington volcanic field is less than 200 kilometers (km) from the Colorado Plateau, Gulf of California, and southern San Andreas Fault system. This work identifies and examines controls on the emplacement of the Sentinel-Arlington volcanic field by documenting shallow and surficial structures as well as eruption characteristics and style through time. The Sentinel-Arlington volcanic field consists of 21 volcanoes with a total of 33 vents over an area of about 770 square kilometers (km 2 ). The prominence of low relief shield volcanoes may be explained by ascent of basaltic magmas through thin Basin and Range crust, without much crustal contamination, and low viscosities common to mafic compositions. Typical eruption characteristics involve the construction of low relief shield volcanoes followed by Strombolian fissure eruptions at the summits or near-summit medial areas that produce scoria lapilli, which may weld to form agglomerate. The total lifetime erupted volume of about 4.3 cubic kilometers (km 3 ) represents an average eruptive flux of approximately 2x10 -3 km 3 per thousand years (k.y.). This erupted volume is low relative to Neogene basaltic intraplate distributed volcanic fields worldwide, which typically range from 10 -3 to 1 km 3 k.y. -1 . Sentinel-Arlington volcanic field eruptions were likely triggered by intermittent rejuvenation of transient magmatic zones that exist in thinned crust. Instantaneous flux from point sources feeding the lava flows is estimated to be on the order of 10 -1 to 10 cubic meters per second.

Arizona↗
USGS1998

Satellite imagery of the north-central Gulf of Mexico, June 1993-May 1997

This CD contains imagery collected by the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA polar-orbiting weather satellites. The AVHRR provides almost daily coverage of a site at a resolution of approximately 1 km. The data types included are sea surface temperature (SST), water reflectance (REF), and a false-color infrared overview (FCI).

Alabama, Florida, Louisiana, Mississippi↗
USGS2025

VIPER site analysis

We needed to evaluate available orbital data of NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) mission area in order to derive a variety of maps to help the science team identify scientifically interesting places for the rover to visit and to provide scientific context for our mission. Some of these maps also fulfilled engineering and mission design needs to enable safe and efficient landing and roving. We incorporated data from the Lunar Reconnaissance Orbiter Camera, the Lunar Orbital Laser Altimeter, the Mini-RF instrument, the Chandrayaan-2 Orbital High Resolution Camera, the Korean Pathfinder Lunar Orbiter’s Shadowcam, the Kaguya Spectral Profiler and Multiband Imager, and the Chandrayaan-1 Moon Mineralogy Mapper. We used a variety of techniques to build these maps, including stereogrammetry, shape-from-shading, ice stability depth and surface temperature calculations, and the horizon method for solar illumination and direct-to-Earth communications maps. Altogether, these maps allowed us to survey for boulders, evaluate features in permanently shadowed regions that VIPER might explore, provide mineralogic context for what VIPER’s instruments may learn, estimate the ages and radar properties of craters in the VIPER mission area, and evaluate the potential for gravity traverses with the rover. These data and techniques provided a rich set of information from which both the VIPER science team and engineering teams were able to draw in order to plan a safe landing and to plan a VIPER surface mission that will be both scientifically valuable and robust from an operational perspective.

The Planetary Science Journal↗