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The Sedimentary Geochemistry and Paleoenvironments Project Phase 2 data release: An open data resource for the study of Earth's environmental history

Geochemical data from sedimentary rocks are the primary source of information regarding Earth's surface evolution through time, including its air and water envelopes and interactions with life and deep Earth processes. The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is a scientific consortium centered around open data and community-driven development of cyberinfrastructure tools and resources for sedimentary geochemistry and Earth history. Here we describe the SGP Phase 2 data release, which focused on incorporating Paleoproterozoic and Mesoproterozoic (2500–1000 million years ago) data and better accommodating carbonate data. This data release was built through the involvement of >200 researchers worldwide in academia, government, and industry, and provides the largest available public data resource for our user community in the academic fields of geochemistry, sedimentology, tectonics, paleontology, Earth history, and paleoclimate, as well as the petroleum and minerals industries. The dataset now encompasses 126,006 samples and 4,132,371 geochemical analyses. In addition to direct entry by SGP Team Members, we have ingested and incorporated datasets from the Geoscience Australia OZCHEM database, the Alberta Geological Survey, and the Deep-Time Marine Sedimentary Element Database (DM-SED) compilation. This paper details sampling in the Phase 2 dataset with respect to age, geography, lithology, and other geological characteristics, documents access via our search website and API, discusses possible issues and/or biases in the dataset that could impact analyses, describes plans for governance and stewardship of data from Indigenous lands, and serves as the citable reference paper for the data release.

Chemical Geology

Advancing current understanding of Martian impact-generated hydrothermal systems through novel coupled modeling: Insights from Gale, Jezero, and other craters

Impact-generated hydrothermal systems are considered potentially habitable environments on Mars, Earth, and other planetary bodies for microbial life. However, there is an ongoing debate regarding what geological features on Mars provide definitive evidence for such systems. Although earlier studies have modeled hydrothermal processes in Martian craters, they often lacked integration with shock physics hydrocodes to constrain initial impact conditions. The importance of this two-code coupling was demonstrated by successfully replicating alteration signatures in the Earth's Haughton impact structure. In this study, we use a similar two-code approach, combining the iSALE hydrocode with the HYDROTHERM hydrothermal model to simulate the full evolution of impact-generated hydrothermal systems. We apply this method to craters the size of Jezero (∼50 km) and Gale (∼154 km) in diameter. Although Jezero's interior is largely buried, our results align with hypothesized hydrothermal vents and alteration minerals near central uplifts in similarly sized exposed craters, such as Toro and Auki. Furthermore, our models correspond to alteration patterns observed by the Curiosity in the lower layers of Mount Sharp, which may represent remnants of impact-driven hydrothermal activity. A key finding is that these systems may persist much longer than previously estimated. Our simulations suggest that a Jezero-sized system could remain habitable for thermophiles for approximately 720,000 years, whereas a Gale-sized system could persist for nearly 2 million years. Additionally, simulations under unsaturated crustal conditions reveal that air-dominated near-surface layers can suppress vertical fluid flow, enabling deep subsurface alteration without producing detectable mineral signatures at the surface.

Journal of Geophysical Research - Planets

Timescales of surface faulting preservation in low-strain intraplate regions from landscape evolution modeling and the geomorphic and historical record

Large surface-rupturing intraplate earthquakes in stable continental regions (SCRs) are uncommon globally and have recurrence intervals of thousands to hundreds of thousands of years based on the paleoseismic and geomorphic record, challenging accurate active fault identification in these regions. To constrain the timescales of preservation for scarps created by surface ruptures from dip-slip earthquakes, we use a two-dimensional scarp diffusion model for typical intraplate settings and explore which parameters influence fault scarp preservation. These parameters include the coseismic vertical surface offset, the recurrence interval of similar magnitude earthquakes, diffusivity (as a proxy for mean annual precipitation rate), and the erodibility of the surficial material. We constrain parameter ranges from a compilation of historical surface ruptures in intraplate settings in a variety of climates, including the Central and Eastern United States, Australia, Europe, Central Asia (Mongolia, China), India, and West Africa. The timescales of scarp preservation from landscape evolution modeling agree well with observations of scarp preservation in low-strain SCR and intraplate tectonic settings, with some notable exceptions for Australian scarps. We find that the erodibility of the surficial material and earthquake recurrence interval have a stronger effect on the timescales of scarp preservation than diffusivity or coseismic vertical surface offset. Our model results may aid in identifying and characterizing subtle, slow-moving active faults in low-strain SCR and intraplate tectonic settings for different tectonic, geomorphic, and climatic characteristics. Accurate fault locations and characterization from the landscape record has implications for both probabilistic seismic and fault displacement hazard analyses.

Journal of Geophysical Research Solid Earth

Structural evolution of iron coordination in proteins across Earth’s oxygenation history

Protein metal-binding sites support essential biological functions shaped by protein fold, subunit interactions, and cofactor chemistry. Because these sites encode both biochemical function and environmental constraint, they offer a route to connect protein evolution with changes in Earth’s surface environment through time. Of particular interest is iron (Fe), the most widely used metal in biology and a cofactor central to both anaerobic and aerobic metabolism. Here, we systematically compare the immediate chemical environments of functionally essential Fe-binding sites in three-dimensional protein structures to test whether Fe coordination spheres differ across oxygen contexts. Using a curated dataset of experimentally determined structures, we identify a clear shift in the local chemistry of Fe-binding environments from anaerobic to aerobic proteins. Aerobic Fe sites are significantly more hydrophilic than anaerobic ones, and amino-acid composition analyses show reduced cysteine use in aerobic Fe-binding neighborhoods. These patterns suggest that as Earth’s surface environments became more oxygenated, proteins retained Fe as a core redox metal while reconfiguring local coordination chemistry in ways less vulnerable to oxidative damage. More broadly, this study introduces and applies the Coordination Sphere Analysis and Comparison (CSAC) workflow, an open and archived Python workflow for extracting local metal-binding environments from structure datasets, providing a framework for linking metalloprotein structure to evolutionary and geobiological transitions across Earth history.

Discover Life

Three-dimensional seismic velocity models for the San Francisco Bay region, California from joint body-wave and surface-wave tomography validated by waveform simulation

A high-resolution seismic velocity model for both P and S waves is essential for the San Francisco Bay (SFB) region to accurately simulate earthquake ground motions and assess seismic hazards in this high-risk region. We present new three-dimensional P-wave and S-wave velocity (Vp and Vs) models of the SFB region developed using joint tomographic inversion with a rich set of earthquake and active-source body-wave data and ambient-noise surface-wave data. We designed a dynamic balance strategy to effectively balance the contributions of body-wave and surface-wave data during each iteration of the inversion. Owing to the complementary resolution of body-wave and surface-wave data, our new models are significantly improved compared to previous tomographic models. Major geologic features in the SFB region, including low-velocity basins, high-velocity Franciscan Complex, granite, and gabbro rocks, and across-fault velocity contrasts, are imaged in our Vp and Vs models. Compared to the geology-based U.S. Geological Survey velocity model, our new model has better defined structures for some important areas that are of great concern for seismic hazard assessment, such as the Sacramento-San Joaquin Delta, and the 2014 magnitude 6.0 South Napa earthquake area. We validated our model by simulating waveforms for a set of moderate-magnitude earthquakes. The good performance of our model in waveform simulation indicates its potential for improving ground motion simulation and seismic hazard assessment in the SFB region.

California

Patterns and drivers of cliff erosion in Big Sur, California, USA using repeat photogrammetry, 2017–2023

Seacliff erosion in steep terrain poses major risks to transportation and critical infrastructure. In Big Sur, California, USA, seacliff erosion threatens the sustainability of the central coast stretch of California State Route 1, a transportation corridor that is critical to the region's economy. Published cliff retreat rates for the region range from 1 to 40 cm yr −1 , highlighting that high-resolution, process-based studies could enhance understanding of the causes of spatial and temporal variability. We quantified cliff erosion and investigated its drivers along ∼13 km of the Big Sur coastline at week–month timescales during the late fall to early spring wet seasons between January 2017 and June 2023 by analyzing 3D point clouds developed from aerial imagery using four-dimensional structure-from-motion (4D SfM) photogrammetry techniques. We calculated cliff face retreat rates of 2.23 ± 3.06 cm yr −1 (mean ±1 σ ), an order of magnitude lower than long-term estimated rates for the region (which included large deep-seated landslides), but in line with short-term rates reported across California. Change detection imagery comparison, cliff profiles through time, and statistical analysis reveal a cyclical cliff evolution process in which erosion by wave action at the cliff base destabilizes the cliff and primes it for subsequent failure during precipitation events. Although more erosion by volume could be attributed to precipitation-induced increases in soil moisture (784 m 3 km −1 yr −1 ) compared with erosion attributed to wave power (282 m 3 km −1 yr −1 ), our observations underscore the coupled nature of these processes in driving cliff evolution, consistent with established theory and observations.

California

Fully contained laboratory earthquakes: The effect of asperity aspect ratio and free surfaces

Corner frequency ( f c ) and seismic moment ( M 0 ) are key parameters derived from seismic signals that are used to characterize earthquake stress drop, rupture area, and slip. These parameters are also affected by fault geometry and boundary conditions. However, the systematic study of these effects in laboratory settings has been challenging. This study presents laboratory earthquake experiments that examine how rupture dynamics are influenced by (a) the aspect ratio of rectangular PMMA velocity-weakening (VW) asperities surrounded by the Teflon velocity-strengthening (VS) patches, and (b) whether the sides of a VW asperity are confined with VS patches or are free surfaces. We found that increasing confinement by reducing free surfaces or increasing the VW asperity aspect ratio stabilizes fault slip, so that higher normal stress is required to transition from aseismic to seismic slip. Increased confinement and high aspect ratios also reduced M 0 and increased f c , both of which were determined from the radiated seismic waves. M 0 and f c were primarily controlled by the shorter dimension of the VW asperity. Analysis of high-frequency acoustic emission signals revealed that ruptures on high-aspect-ratio VW asperities propagated more unidirectionally, whereas ruptures on square VW asperities were more complex. Further, the high-aspect-ratio asperities were more likely to be eroded by surrounding VS regions while low-aspect-ratio asperities were more likely to rupture into the VS surroundings. These results demonstrate that both the confinement from surrounding stable areas and the geometry of the seismogenic patch can affect rupture nucleation, propagation, and seismic source characteristics.

JGR Solid Earth

Distributed volcanic fields—Patterns, products, processes, and plumbing

Distributed volcanic fields—also referred to as “monogenetic fields” or simply “volcanic fields”—are found on every continent, on the seafloors, and in every tectonic setting on Earth. Yet, our understanding of what constitutes a distributed volcanic field, and our knowledge of the common products, spatiotemporal patterns in activity, and plumbing systems of these fields, are commonly poor and (or) debated. Here we provide an overview of the current understanding of distributed volcanic fields (DVFs) through review and compilation of published data, with an emphasis on understanding the characteristics of fields that are essential to prepare for future hazardous volcanic activity. Distributed fields can erupt restricted to variable magma compositions. Activity in these fields produces nearly all types of volcanoes, including scoria and spatter cones, maars, low shields, lava fields, stratovolcanoes, and calderas, but monogenetic volcanoes are the defining characteristic of DVFs. The number of vents and lifespans of DVFs vary greatly; vent numbers range from 2 to greater than 1,000, and fields can remain active for 150,000 to 10 million years. Some characteristics of DVFs appear field dependent. Although the volumes of single monogenetic eruptions within DVFs globally are variable (from less than 0.1 to a few cubic kilometers), each field may have a characteristic range in eruption volumes. Eruptions within distributed volcanic fields can have a random distribution and timing, but spatial and (or) temporal vent clustering and alignment are common, and eruptions may be time or volume predictable. Average eruption recurrence intervals in DVFs span over an order of magnitude, from less than 3 to greater than 100 thousand years. Exposures of the shallow portions of older systems reveal that many magma batches end their ascent before reaching the surface, with some dikes stopping within only meters of the surface. Petrologic insights into the deeper plumbing systems of DVF volcanoes indicate variable depths of magma crystallization and (or) stalling, and that magma transport and storage systems may be unique to a particular DVF and its underlying crustal structure. Both seismic and petrologic data for mafic DVF eruptions corroborate intrusions of magma into storage systems in the months to years before eruption, as well as variable ascent rates through the crust (days to weeks). Few distributed fields are closely monitored, as they erupt infrequently, but these observations imply that the amount of time available to install monitoring instrumentation after the first felt seismicity may be short, as precursory activity is frequently on the order of days to months for modern DVF eruptions. Satellite-based geodesy may provide useful warning in such cases. This chapter concludes with outstanding questions and areas for future research that will aid in our understanding and preparedness for future DVF eruptions.

Professional Paper

The feasibility of using lidar-derived digital elevation models for gravity data reduction

Gravity data require submeter elevation accuracy for data processing, and differential global navigation satellite system (dGNSS) equipment is commonly used to acquire three-dimensional positional data to achieve such accuracy. However, lidar (light detection and ranging) data are commonly used to develop digital elevation models (DEMs) of Earth’s surface. Therefore, using elevations from lidar-derived DEMs for gravity-data acquisition and reduction may improve field efficiency and reduce cost. This study examines the feasibility of using DEMs for gravity-data reduction by comparing dGNSS elevation data from 435 gravity stations in Michigan, Wyoming, and Colorado with their respective DEM elevations. The results show that the average difference between DEM and dGNSS elevations is 13 centimeters (cm) and that 93 percent of those differences are less than 50 cm, even in areas with steep terrain. Because an elevation discrepancy of 50 cm corresponds to an error of roughly 0.1 milligals (mGal) in the simple Bouguer gravity anomaly, the results suggest that lidar-derived DEMs are a viable source for acquiring the elevation data needed to process gravity data, thus improving both the cost and efficiency of data collection for regional surveys where an accuracy of less than 1.0 mGal is desired.

Open-File Report

Complex carbonate ore mineralogy in the Mountain Pass carbonatite rare earth element deposit, USA

Economic concentrations of rare earth element (REE) minerals are uncommon in the Earth’s crust, with most occurring in carbonatites. Unlike most igneous rocks composed of silicate minerals, carbonatites are dominated by carbonate minerals, some of which can incorporate significant light REEs (LREEs; La, Ce, Pr, Nd). Technological applications of REEs are numerous and they have been identified as some of the most critical mineral commodities to the global economy. The Mountain Pass carbonatite stock in the Mojave Desert of California is the most economically significant REE deposit in the USA and contains a few to tens of percent (by volume) of the carbonate REE ore mineral bastnäsite. Despite the economic significance of the Mountain Pass deposit, studies of its ore mineralogy are limited. Here we present new carbonate ore mineralogy data for a compositionally diverse suite of carbonatitic rocks from the Mountain Pass stock and related dikes. Whole-rock geochemical data are integrated with mineral-scale textural and chemical data obtained by scanning electron microscopy (SEM), electron probe microanalysis (EPMA), and microRaman spectroscopy. Our results document a complex spectrum of REE-bearing carbonate minerals and intermediate mixed-layer structures. Mineral species include bastnäsite [REE(CO 3 )F], hydroxylbastnäsite [REE(CO 3 )OH], parisite [Ca(REE) 2 (CO 3 ) 3 F 2 ], synchysite [Ca(REE)(CO 3 ) 2 F], röntgenite [Ca 2 (Ce,La) 3 (CO 3 ) 5 F 3 ], and sahamalite [(Mg,Fe 2+ )(REE) 2 (CO 3 ) 4 ]. Carbonate ore mineralogy is heterogeneous within and between samples, including at the intracrystal scale. Complexly zoned crystals exhibit as many as five to six different compositional domains and syntaxial intergrowths, commonly with the more Ca-rich varieties (parisite, synchysite) forming crystal rims that surround relict bastnäsite cores. We attribute the phenocryst variability to changes in the chemistry and temperature of primary carbonatite magmas and evolved/exsolved fluids. Cross-cutting vein textures of calcite, celestine and various REE carbonate minerals, interstitial bastnäsite crystallization, breccia blocks lined by fine-grained bastnäsite, and the presence of hydroxylbastnäsite and partially hydroxylated bastnäsite point to the role of secondary hydrothermal processes in REE mineralization. Fluorcarbonate mineral compositions demonstrate that La and Ce are more structurally abundant in bastnäsite, whereas the more Ca-rich species (parisite, synchysite) contain a greater proportion of REE heavier than Pr (Nd, Sm, Eu, Gd) and Y. Atomic ratios of Pr/(Nd + Pr) are likewise variable, with the highest average value for bastnäsite (0.25) compared to parisite (0.22) and sychysite (0.21). This finding has geometallurgical implications, given that current mining operations are focused on recovery of Nd and Pr for high field strength permanent magnets and the Nd/Pr ratios are a critical factor in ore processing and magnet manufacture.

California

A review of abrupt permafrost thaw: Definitions, usage, and a proposed conceptual framework

Purpose of Review We review how ‘abrupt thaw’ has been used in published studies, compare these definitions to abrupt processes in other Earth science disciplines, and provide a definitive framework for how abrupt thaw should be used in the context of permafrost science. Recent Findings We address several aspects of permafrost systems necessary for abrupt thaw to occur and propose a framework for classifying permafrost processes as abrupt thaw in the future. Based on a literature review and our collective expertise, we propose that abrupt thaw refers to thaw processes that lead to a substantial persistent environmental change within a few decades. Abrupt thaw typically occurs in ice-rich permafrost but may be initiated in ice-poor permafrost by external factors such as hydrologic change (i.e., increased streamflow, soil moisture fluctuations, altered groundwater recharge) or wildfire. Summary Permafrost thaw alters greenhouse gas emissions, soil and vegetation properties, and hydrologic flow, threatening infrastructure and the cultures and livelihoods of northern communities. The term ‘abrupt thaw’ has emerged in scientific discourse over the past two decades to differentiate processes that rapidly impact large depths of permafrost, such as thermokarst, from more gradual, top-down thaw processes that impact centimeters of near-surface permafrost over years to decades. However, there has been no formal definition for abrupt thaw and its use in the scientific literature has varied considerably. Our standardized definition of abrupt thaw offers a path forward to better understand drivers and patterns of abrupt thaw and its consequences for global greenhouse gas budgets, impacts to infrastructure and land-use, and Arctic policy- and decision-making.

Current Climate Change Reports

Multi-scale geophysical imaging of a hydrothermal system in Yellowstone National Park, USA

Little is known about the local plumbing systems that fuel Yellowstone’s famous hot springs, geysers and mud pots. A multi-method, multi-scale geophysical investigation was carried out in the Obsidian Pool Thermal Area (OPTA) to: (i) delineate the lateral extent of the hydrothermal area and associated surface features; (ii) estimate the dimensions of the upflow zone and identify its main controlling structures; (iii) assess fluids circulation pathways from depth to surface. Ground and airborne geophysical data were acquired to connect local and regional scales, from shallow to large depths. Maps of surface electrical resistivity show a strong correlation with hydrothermal features. At in-termediate depths, electrical resistivity permits delineating the upper limit of the upflow zone, while Poisson’s ratio highlights differences in subsurface fluid content. Combining these results with surface observations and topographic information, we speculate that differential mixing of hydrothermal and fresh water could explain the wide diversity of features observed at OPTA. Low electrical resistivity observed at large depths also suggest that a vast upflow zone, controlled by rhyolite flows and conjugate faults, underlies the OPTA. We speculate that hydrothermal fluids rise along fractures and reach the surface in topographic lows to form hydrothermal features. Our results show that synoptic, multi-scale geophysical measurements provide a roadmap for understanding where and how geologic heterogeneity, topography, fluid-gas separation, and the mixing of thermal and meteoric waters conspire to produce the wide variety of Yellowstone’s renowned hydrothermal features.

Wyoming

RegionGrow3D: A deterministic analysis for characterizing discrete three-dimensional landslide source areas on a regional scale

Regional-scale characterization of shallow landslide hazards is important for reducing their destructive impact on society. These hazards are commonly characterized by (a) their location and likelihood using susceptibility maps, (b) landslide size and frequency using geomorphic scaling laws, and (c) the magnitude of disturbance required to cause landslides using initiation thresholds. Typically, this is accomplished through the use of inventories documenting the locations and triggering conditions of previous landslides. In the absence of comprehensive landslide inventories, physics-based slope stability models can be used to estimate landslide initiation potential and provide plausible distributions of landslide characteristics for a range of environmental and forcing conditions. However, these models are sometimes limited in their ability to capture key mechanisms tied to discrete three-dimensional (3D) landslide mechanics while possessing the computational efficiency required for broad-scale application. In this study, the RegionGrow3D (RG3D) model is developed to broadly simulate the area, volume, and location of landslides on a regional scale (≥1,000 km 2 ) using 3D, limit-equilibrium (LE)-based slope stability modeling. Furthermore, RG3D is incorporated into a susceptibility framework that quantifies landsliding uncertainty using a distribution of soil shear strengths and their associated probabilities, back-calculated from inventoried landslides using 3D LE-based landslide forensics. This framework is used to evaluate the influence of uncertainty tied to shear strength, rainfall scenarios, and antecedent soil moisture on potential landsliding and rainfall thresholds over a large region of the Oregon Coast Range, USA.

Journal of Geophysical Research: Earth Surface

Uncertainty reduction for subaerial landslide-tsunami hazards

Subaerial rock slopes may generate a tsunami by rapidly moving into the water. Large uncertainty in landslide characteristics propagates into large uncertainty in tsunami hazard, making hazard assessment more difficult for land and emergency managers. Once a potentially tsunamigenic landslide is identified, it may not be clear which landslide characteristics contribute most significantly to uncertainty in the tsunami hazard. Our aim is to document the relative worth of different landslide characteristics (e.g., size, material properties) for reducing uncertainty in landslide-tsunami hazard assessments. Isolating the relative importance of specific landslide characteristics may inform prioritization of data collection and improve efficiency in understanding hazard. To accomplish this, we generated a set of 288 landslide-tsunami simulations in which we systematically varied the size and material properties of possible failure extents at the Barry Arm landslide complex in northwestern Prince William Sound, Alaska, USA. We find that for landslides smaller than the receiving waterbody, the landslide volume has the strongest effect on resulting wave characteristics and thus the highest leverage on reducing uncertainty in tsunami hazard. In contrast, for landslides substantially larger than the waterbody, the duration of rapid movement of the landslide has the highest leverage. Based on our results, we propose a classification scheme for subaerial landslides based on the relative size of the landslide and waterbody. Additionally, our results support the generation of a tsunami height transfer function between existing tide gages and a nearby coastal city. These results have direct implications for the practice of operational early warning.

Alaska

Constraining mean landslide occurrence rates for non-temporal landslide inventories using high-resolution elevation data

Constraining landslide occurrence rates can help to generate landslide hazard models that predict the spatial and temporal occurrence of landslides. However, most landslide inventories do not include any temporal data due to the difficulties of dating landslide deposits. Here we introduce a method for estimating the mean landslide occurrence rate of deep-seated rotational and translational slides derived solely from high-resolution (≤3 m) elevation data and globally available estimates of the diffusion coefficient for sediment flux. The method applies a linear diffusion model to the roughest landslide deposits until they reach a representative non-landslide roughness distribution. This estimates the time for a landslide deposit to be unrecognizable in high-resolution digital elevation data, which we term the mean lifetime of the landslide. Using the mean lifetime and number of landslides within an area of interest, we can estimate the mean occurrence rate of landslides over that domain. We validate this approach using a comprehensive temporal inventory of landslides in western Oregon created using age-roughness curves that are calibrated with high-resolution elevation data and radiocarbon data. We find good agreement between our diffusion method and the existing age-roughness-derived estimates, producing mean lifetimes of 4500 and 5200 years (4% difference), respectively. Hazard maps produced using the two methodologies generally agree, with the maximum differences in landslide probability reaching 0.1. Due to the relative abundance of high-resolution elevation data compared with age-dated landslides, our method could help constrain landslide occurrence rates in areas previously considered unfeasible.

Oregon

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

Dynamic feedbacks between river meandering and landsliding in northwestern Washington glacial terraces

Landsliding in river valleys poses unique risks for cascading hazards and can damage infrastructure and cause fatalities. In postglacial valleys, many landslides are posited to occur in relation to lateral river erosion, but the dynamics of fluvial-hillslope interactions are not well understood. Here, we investigate a section of the Nooksack River in western Washington State where the channel is flanked by landslide-prone glacial terraces similar to those that failed in the 2014 State Route 530 “Oso” landslide. We map 216 landslides through time across 17 aerial imagery data sets (1933–2022) and analyze them in relation to river meandering and curvature. We observe dynamic feedbacks between lateral river meandering and valley-adjacent landsliding. Terrace lateral retreat rates of up to 25 m/year owing to combined fluvial erosion and slope failure occur on pinned, outer meander bends immediately downstream from peaks in river curvature (>0.0075 1/m); these locations are predisposed to both shallow and deep-seated landslides. Deep-seated landslides extending 17%–32% of the active valley width into the floodplain can displace the river away from the floodplain margin and change the channel planform. River-displacing landslides relocate meanders up- or downstream, thereby conditioning the location of subsequent landslides. This conceptual model of coupled landslide-driven meander displacement and valley-adjacent landsliding is exemplified across western Washington river systems. The distance between up- and downstream valley-adjacent landsliding scales with valley width, meander wavelength, and terrace height. Our results can advance our understanding of the river-hillslope interface in landscape evolution and can be used to inform hazard management in river corridors.

Washington

SURF: An automated method for building nonplanar 3D fault models from earthquake hypocenters

Accurately characterizing 3D fault geometry is vital for improving our understanding of earthquake behavior and informing the development of seismic hazard models. Despite their importance, subsurface fault structures tend to be poorly constrained because of limitations in observational data. Improvements to the seismic networks and earthquake detection algorithms have increased the precision and volume of earthquake catalogs, which help illuminate detailed subsurface fault structure and provide the most direct information available about fault geometries at depth. We present a Python package to automate generating 3D fault geometries directly from hypocentral seismicity patterns. This method begins with clustering events based on their spatial density, identifying coherent patterns. Nearby clusters are then merged based on the similarity of their orientations. We fit nonplanar surfaces using support vector regression to balance surface accuracy with minimal deviations from planarity. The fault models are output as quadrilateral meshes at user‐defined resolution. In the process of generating the 3D fault surfaces, we compute the spatial density of seismicity around the surface and the planarity as quantitative metrics of the model outputs. As a proof of concept, we apply this approach to the San Andreas–Calaveras fault junction region and the 2019 Ridgecrest earthquake sequence, both in California, which contain complex subparallel faults well defined at the Earth’s surface and abundant microseismicity. These case studies demonstrate the method’s ability to model complex fault structures, including long continuous fault surfaces, crossing faults, variably dipping segments, and subparallel faults. We test the method on both standard network catalogs and double‐difference relocated catalogs. We find that our seismicity‐based fault model results align with published 3D models that incorporate additional constraints and interpretations ( Plesch et al. , 2020 ; Aagaard and Hirakawa, 2021 ). This workflow provides a low‐user‐input solution for estimating fault geometries at depth from earthquake catalogs.

California