Before Navan Fort became the mythological capital of the Irish province of Ulster, construction of the monumental Haughey’s Fort around 1200 BC marked the foundation of an important prehistoric centre. Here, the authors report on research integrating remote sensing, excavation and archival reassessment in the exploration of this Bronze Age landscape. Indicators of long-distance exchange and craft production of high-status artefacts, together with the presence of 204 possible structures and a ceremonial avenue leading towards a unique ritual pool, help elucidate the site’s social, economic and ritual importance, while identification of a 109ha enclosure underlines the exceptional scale of activities.

In July 1954, while making glacier mass-balance measurements in Northwest Greenland just below the boundary of the dry-snow facies, a team led by C.S. Benson documented a rain-on-snow event triggered by an atmospheric river. This produced extensive surface melt and notable ice layers, lenses and percolation columns in the snowpack that were tracked in subsequent years in snow pits dug nearby. Since 2000, numerous surface-melt events in the dry-snow facies have been documented by satellite observations. We compare and contrast the 1954 event with recent melt events to highlight challenges in monitoring melting in Greenland. Satellite sensors can accurately map melt extent across the ice sheet but cannot reliably quantify the melt intensity. Snow pit and ice core measurements can assess melt intensity but are too localized to capture melt extent. Reanalysis of the 1954 event adds an additional caveat: the extensive surface-melt event produced features only on two of the four sides of a large snow pit, evidence that the notable 1954 event could easily be missed in an ice core extracted years later. This suggests that analysis of historical melt events, using ice cores, probably underestimates both the spatial extent and temporal frequency of past melt events.

Census counts of Pygoscelis penguins on the Antarctic Peninsula and Scotia Arc are conducted both regularly around field stations and opportunistically from ships with the goal of assessing the breeding abundances and trends of these indicator species. Regional trends and abundances are often more policy-relevant than population-specific metrics, but survey patterns in the area have not been planned to optimize regional inference. We evaluated the ability of several monitoring schemes to describe regional trends and abundances of Pygoscelis penguins. Using a ‘pseudo-true’ time series as a starting point, we simulated time series of ‘observed’ census data for the period of 2000–2024. We then fit a hierarchical Bayesian population model to each dataset to assess how well each monitoring scheme recovered the known regional trends and abundances. Simulations were repeated across combinations of survey efforts, variances in inter-population abundances and census uncertainties. We found that implementing structured monitoring schemes would improve our ability to recover regional trends and abundances compared to the actual distribution of surveys conducted during the 2000–2024 period. For scenarios characterized by low variance in abundance such as the gentoo penguins on the central-west Antarctic Peninsula, we could recover trend and abundance estimates with considerably less survey effort if we deployed a monitoring scheme that cycled through all populations at an equal interval. For scenarios characterized by high variance in abundance such as the Adélie penguins on the north-east Antarctic Peninsula, surveys were optimized by splitting effort between satellite monitoring of the largest populations and cycling through the other populations. These findings are strongly influenced by the rapid increase in uncertainty regarding population abundance in the seasons after a census count, highlighting the importance of prioritizing sites where abundances are highly uncertain due to long intervals since the last survey.

Tropical glaciers in the Cordillera Real (Bolivia) are rapidly retreating. In the early 2000s, it was predicted that many of its small glaciers (<0.5 km2) would vanish within a few decades. More than two decades after this dire prediction, we evaluate their fate using a recently published, multitemporal inventory of glaciers in the Cordillera Real. We identify 174 glaciers that disappeared between 1998 and 2024, more than five times the number previously reported. All of the glaciers that vanished were small, as predicted, and most (79.9%) were low-lying (maximum elevation <5400 m). These losses represent 30.5% of the total number of glaciers in the Cordillera Real in 1998, but their demise accounts for only 8.5% of the total area loss between 1998 and 2024. Although a majority (62.7%) of small glaciers persist to 2024, current and projected warming will likely threaten most of those that remain.

Drylands cover 41% of Earth’s land surface, support 36% of the global population and contribute 60% of global food production. Despite these ecosystems’ importance and high vulnerability to droughts and heatwaves, drylands remain some of the most understudied systems on Earth. Monitoring drylands is challenging due to their complex ecosystem structure of visible soil mixed with diverse plant species that respond rapidly to weather and climate. In 2023 and 2024, a NASA scoping study was conducted for a proposed dryland terrestrial ecology field campaign called Adaptation and Response in Drylands (ARID). Thereafter, the NASA ARID scoping team submitted their campaign proposal to NASA Headquarters, providing a study design for how field, aircraft and satellite measurements, as well as modeling, could address the most critical fundamental and applied science questions in drylands. The extensive strategic vision was created by and for the drylands research community, including remote sensors, modelers, experimentalists and ecologists from across the world, and the overall approach can be further utilized and altered for different uses and data information needs. Here, we summarize the final ARID research agenda, including its main objectives, field campaign strategy, data end-user support strategy, and U.S. and global community engagement.

Ice sheets leave contact with the bed at grounding lines, beyond which floating ice shelves experience no friction at their base. In places where basal friction begins to decrease upstream of the grounding line, ice sheets respond more strongly to climate forcing. However, the spatial extent of zones of low grounding line friction is poorly constrained by observations. Here, we use a steady-state model of marine-terminating ice stream flow to show that the location where basal friction begins to weaken upstream of the grounding line is accompanied by a prominent surface slope break. We then use observations of grounding zone features around the Antarctic ice sheet derived from ICESat-2 laser altimetry to find the displacement between grounding line locations determined from SAR flexure measurements and such surface slope break points. We find widespread evidence of decreasing friction hundreds to thousands of meters upstream of grounding lines around the Antarctic ice sheet, indicating that grounding lines may be more sensitive to forcing than typically assumed in ice-sheet models, where friction does not decrease upstream of the grounding line. We suggest that such an observational approach should be used to parameterize grounding line friction interpolation schemes in ice-sheet models.

Small glaciers (${ \lt }0.5\,\mathrm{km}^2$), glacierets (${ \lt }0.25\,\mathrm{km}^2$) and, in particular, very small glacierets (${ \lt }0.01\,\mathrm{km}^2$), despite being numerous in mountain environments, are underrepresented in scientific inquiry when assessing their response to climate change. We present new insights into the vanishing (no visible surface ice whilst underlain by bedrock or water) of 77 very small glacierets distributed in the Northern and Central Andes of Chile. We also analyse the presumable vanishing (no visible surface ice whilst underlain by regolith) of 244 additional very small glacierets, comprising a total dataset of 321 very small glacierets within the study area, equivalent to the loss of $5.69\times 10^6\,\mathrm{m}^3$ of water equivalent ice volume according to the 2022 Chilean Public Glacier Inventory. Our results show that 45.5% of the sample shrank from individually small glaciers at the beginning of the 21st century, whereas 53.0% of the sample vanished after being fragmented from larger glaciers in the same time span. The observed generalised reduction behaviour and vanishing results after extremely dry conditions at the end of the 2009–2022 Central Andes megadrought. We discuss our results in terms of the minimum area threshold for classifying very small glacierets, and whether their vanishing poses a hydrological impact.

Despite the survival of some historical records, little is known about water management in Urartu. This project focuses on the fortress of Argishtikhinili in the Araks Valley, Armenia, employing satellite imaging and remote sensing data to identify 1019km of water-management features, including a potential 134.6km of ancient canals.

In spite of contributing to social, economic and cultural well-being, wetlands in the Indian Himalayan Region have seen rapid degradation due to unplanned anthropogenic activities. We analysed spatiotemporal wetland dynamics in Srinagar (1991–2031) using remote sensing and Geographic Information Systems. The future land cover for 2031 was projected using an artificial neural network–multi-layer perceptron and cellular automata model. Change detection in the open water area of Dal Lake and its 2-km peri-lacustrine zone was conducted to identify land-cover transition patterns. Furthermore, wetland landscape pattern changes were quantified using landscape metrics to assess fragmentation and spatial configuration over time. The results reveal that, from 1991 to 2021, wetlands decreased from 16.12 to 7.2 km2, with the open surface water area of Dal Lake and its 2-km peri-lacustrine zone declining from 9.77 to 6.39 km2. The land cover projected for 2031 indicates that the total wetland area may decrease to 5.62 km2. Landscape metrics indicated increasing fragmentation and decreasing contiguity among wetland patches, as revealed by fluctuating shape complexity and aggregation, primarily due to conversions to agricultural land, fallow land and built-up areas.

Glacier surges are dynamic instabilities that dramatically alter glacier flow and geometry. Their triggers remain poorly understood, and improved methods of monitoring to further constrain the phenomenon are therefore important. We present a novel method for detecting glacier surges automatically using surface elevation data from NASA’s ICESat-2 laser altimetry satellite. Elevation changes from 2018 to 2023 were computed relative to a high-resolution reference digital elevation model and analyzed using a hypsometric binning approach. We trained a Random Forest classifier on known surge events in Svalbard to identify spatial elevation change patterns indicative of surging. Our model detected 110 surges, of which 48 were false positives, 20 uncertain cases that may or may not be surges and 42 certain surges confirmed by external validation. Two of these are currently not part of any surge inventory. The classifier achieved an accuracy of 88.4% and highlighted features in the lower glacier region as most predictive. This study demonstrates that sparse altimetry data such as from ICESat-2 can effectively detect glacier surges and offers a promising, scalable approach to monitoring dynamic glacier instabilities.

The manual identification of ancient agricultural terraces is time-consuming and subjective, limiting large-scale archaeological landscape documentation. This study applies deep learning to detect ancient terraces in the Bozburun Peninsula, southwestern Turkey, a historically significant Hellenistic landscape. Four U-Net–based architectures were implemented—early, intermediate, and late fusion, along with an RGB-only baseline—integrating high-resolution aerial imagery (30 cm) and digital elevation models (DEMs) across 193 km2. Sixteen manually digitized areas (37.8 ha) produced 256 training patches (512 × 512 px). The early fusion model that combined spectral and topographic data achieved the best performance (IoU = 0.754; accuracy = 85.9%). Monte Carlo evaluation confirmed its robustness. Spatial analysis showed that 89.8% of detected terraces lie below 300 m elevation, mainly on 10°–20° slopes with north-northwest orientation, in agreement with previous archaeological observations. Compared with expert digitization, the model yielded higher precision (87.4% vs. 79.3%), while experts achieved higher recall (94.3% vs. 76.6%). Applied to the full peninsula, the model mapped 2,517 ha of terraces. Validation using an existing archaeological dataset (Demirciler 2014) enabled direct comparison between automated and expert-based interpretations. The results indicate the potential of deep learning for terrace detection in Mediterranean landscapes and outline a methodological framework for documenting threatened cultural heritage.

Snow grain size is a primary control on albedo and snowmelt. Compact imaging spectrometers and lidars mounted on uncrewed aerial systems (UAS) now offer flexible, high-resolution observations, but their relative performance for optical snow property retrievals has not been assessed. We compared grain size retrievals from two UAS-mounted imaging spectrometers (925–1700 nm and 900–2500 nm) and two lidars (905 nm and 1550 nm) against field spectroscopy over snow covered terrain (Mores Creek Summit, ID in March 2024). The compact imagers and 905 nm lidar retrieved grain sizes within ∼10% of field reference values, with little sensitivity to flight altitude (40–120 m). The 1550 nm lidar showed large negative bias (>90% error) due to strong shortwave-infrared absorption by ice. Results demonstrate that affordable, lightweight UAS sensors can accurately map grain size, with 905 nm lidar offering flexibility, notably in conditions unsuitable for passive optical measurements.

Seasonal glacier dynamics are key to predicting hazards and glacier stability due to short-term events as well as improving glacier models. However, the short-term ice velocity variations remain poorly constrained for slow-moving glaciers in the Himalaya due to the scarcity of in situ observations and limitations of satellite data and methods. We present seasonal velocity variations of Drang Drung Glacier (western Himalaya) in 2021 using Sentinel-1 phase-based Interferometric Synthetic Aperture Radar and offset tracking. Smoothed velocity estimates reveal $\sim$400 % seasonal variability (3–13 m a$^{-1}$), with speedups in spring and autumn and slowdowns in summer and winter. We relate these patterns to changes in radar backscatter and seasonal widening of the proglacial stream observed in Planet imagery. To interpret the mechanisms, we simulate the evolution with the Subglacial Hydrology and Kinetic Transient Interactions model coupled to the Ice-sheet and Sea-level System Model. Results indicate that speedup–slowdown cycles and their upglacier migration are driven by meltwater-induced shifts in subglacial drainage efficiency. This study emphasizes the role of hydrology and basal sliding in Himalayan glacier dynamics, often oversimplified in existing models.

This study analyses the dynamics of Southeast-1 and Southeast-2 glaciers on Devon Ice Cap (1959–2024) using multiple remote sensing datasets. Sharing a common tidewater terminus, the glaciers experienced two dynamic instabilities: an 8–9-year surge in the 1970s–80s advancing the terminus by up to ∼5 km and reaching velocities of >3000 m a−1, and a multiannual acceleration of Southeast-2 beginning in the mid-2000s, suggesting the start of a new surge within that basin. This instability progressed through stepwise increments each summer and propagated up-glacier, reaching velocities over an order of magnitude above quiescent levels. In 2020–23, Southeast-2 showed dynamic thickening of ∼1–5 m a−1 within the lower ∼7.5 km and thinning in the upper trunk (∼7.5–17 km from the terminus) of <−1 m a−1, indicating down-glacier mass transfer. Long-term terminus thinning and retreat increased surface slopes and driving stress, preconditioning the glacier for instability. Seasonal velocity patterns, crevasse expansion, strain rate evolution, and modelled runoff support a hydro-thermodynamic feedback, where meltwater increasingly accesses the bed and enhances basal motion. Southeast-1 remains quiescent but may destabilise similarly to the previous surge. The short surge cycle of Southeast-2 allows the first determination of a complete quiescent phase duration (∼36–37 years) in this region.

Disappearing glaciers are observed worldwide, but a reliable counting is only available for some regions. This is due to several issues, ranging from inconsistent glacier identification to different criteria applied to decide whether or not a glacier has disappeared. The public perception of a glacier being lost usually has a focus on specific, often well-known glaciers, with a related media attention. In contrast, hundreds of glaciers might disappear in other regions over the same period without any notice. When they are not widely known, this silent disappearance can also happen to scientifically valuable glaciers. For example, the loss of benchmark glaciers with decades of mass balance measurements is also a loss of important information about climate variability in remote high-mountain regions. This study gives an overview of the challenges and different criteria used to determine if a glacier has disappeared and presents recommendations for a proper counting and change assessment.

This paper analyzes seasonal grounding line migration from a 4.5-year perspective and with a high (6 days) data-sampling rate. We used a series of high-resolution (60 m) Sentinel-1 double-difference interferograms obtained in the years 2017–21 to monitor variability in the grounding line position on the Orville Coast, on the western part of the Ronne Ice Shelf. We confirmed that the integration of the double-difference interferogram method with a neural network specifically trained on this type of data allows a successful detection of the grounding line position. Despite challenges related to maintaining the coherence and reducing data noise, we were able to generate and analyze time series of grounding line positions, test the assumption of maximum migration ranges and attempt pattern recognition in temporal grounding line migration. Our results represent a pioneering approach to seasonality and trend assessment in grounding line behavior. We believe that our findings can help detect the patterns of and the reasons for glacier behavior in the grounding zone. This information may be crucial in monitoring the mass loss of glaciers, especially in light of ongoing significant climate change.

Nordmannsjøkelen, mainland Europe’s northernmost glacier, has fragmented into small remnants, with only one unit showing signs of active ice flow. The glacier has lost 92% of its area since 1970 (September 2024 area relative to 1970 area). It is reduced from 23.5 km2, as an upper bound of its size in ∼1900, to 0.4 ± 0.08 km2 in September 2024. Between 1970 and 2020, the geodetic mass balance was −17.6 ± 1.79 m w.e., corresponding to an average annual mass balance of –0.35 ± 0.04 m w.e. a−1. The warm summer of 2024 took its toll on Nordmannsjøkelen and the glacier area was reduced by 1.08 ± 0.16 km2 from 2023 to 0.4 ± 0.08 km2 in 2024 (a 68% reduction relative to 2023 area). Similar glacier retreat and thinning are observed elsewhere in the region, and the neighboring Langfjordjøkelen has mass balance measurements for the period 1989–2024, and the highest mass loss is recorded in 2024.