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Arctic landfast sea ice (LFSI) represents an important quasi-stationary coastal zone. Its evolution is determined by the regional climate and bathymetry. This study investigated the seasonal cycle and interannual variations of LFSI along the northwest coast of Kotelny Island. Initial freezing, rapid ice formation, stable and decay stages were identified in the seasonal cycle based on application of the visual inspection approach (VIA) to MODIS/Envisat imagery and results from a thermodynamic snow/ice model. The modeled annual maximum ice thickness in 1995–2014 was 2.02 ± 0.12 m showing a trend of −0.13 m decade−1. Shortened ice season length (−22 d decade−1) from model results associated with substantial spring (2.3°C decade−1) and fall (1.9°C decade−1) warming. LFSI break-up resulted from combined fracturing and melting, and the local spatiotemporal patterns of break-up were associated with the irregular bathymetry. Melting dominated the LFSI break-up in the nearshore sheltered area, and the ice thickness decreased to an average of 0.50 m before the LFSI disappeared. For the LFSI adjacent to drift ice, fracturing was the dominant process and the average ice thickness was 1.56 m at the occurrence of the fracturing. The LFSI stages detected by VIA were supported by the model results.
Antarctic krill are the dominant metazoan in the Southern Ocean in terms of biomass; however, their wide and patchy distribution means that estimates of their biomass are still uncertain. Most currently employed methods do not sample the upper surface layers, yet historical records indicate that large surface swarms can change the water colour. Ocean colour satellites are able to measure the surface ocean synoptically and should theoretically provide a means for detecting and measuring surface krill swarms. Before we can assess the feasibility of remote detection, more must be known about the reflectance spectra of krill. Here, we measure the reflectance spectral signature of Antarctic krill collected in situ from the Scotia Sea and compare it to that of in situ water. Using a spectroradiometer, we measure a strong absorption feature between 500 and 550 nm, which corresponds to the pigment astaxanthin, and high reflectance in the 600–700 nm range due to the krill's red colouration. We find that the spectra of seawater containing krill is significantly different from seawater only. We conclude that it is tractable to detect high-density swarms of krill remotely using platforms such as optical satellites and unmanned aerial vehicles, and further steps to carry out ground-truthing campaigns are now warranted.
This article explores the use of specially trained canines to detect the location of human burials in nonmodern archaeological contexts. It discusses the history of the discipline, training and field methods, the importance of developing a working relationship with descendant communities, project examples, an assessment of canine detection effectiveness, and ways to select a canine detection team. The article highlights how the application of canine detection training and protocols to the archaeological record makes it possible to locate potential precontact Native American burial areas without ground disturbance. In some cases, probable burial areas located by canines can be confidentially mapped to ensure avoidance during upcoming construction projects. For a variety of reasons, many Native American communities have been wary of embracing this new method to locate ancestral burials. Today, however, canine detection is widely accepted by many tribal groups in California to locate ancestral burials that might be impacted by construction. Although additional controlled studies and rigorous field laboratory experiments are needed to understand the range of variation in efficacy fully, available results in both North America and Europe demonstrate that specially trained canines can often accurately locate human burials that are more than a thousand years old to within a few meters.
Supraglacial ponds and ice cliffs can dramatically enhance ablation rates on debris-covered glaciers. Supraglacial ponds can also coalesce, forming moraine-dammed lakes at risk of glacial lake outburst flood (GLOF). Given Bhutanese glaciers have some of the highest ice loss rates in the Himalaya and GLOF vulnerability is high, we seek to advance our understanding of the spatial distribution and evolution of supraglacial ponds and ice cliffs. Here, we use high-resolution (3 m) Planet Labs satellite imagery to provide the first short-term, high-resolution dataset of supraglacial pond and ice cliff evolution for three glaciers along the Bhutan–Tibet border from 2016 to 2018. A total of 5754 ponds and 2088 ice cliffs were identified. Large intra-annual changes were observed, with ponded area changes and drainage events coinciding with the seasonality of the Indian Summer Monsoon. On average, ~19% of the total number of ponds had a coincident ice cliff. Pond spatial distribution was driven by ice-surface velocities, with higher numbers of ponds found in areas of low velocity (<8 m a−1). Our study provides the first detailed, quantitative investigation of supraglacial ponds and ice cliffs in Bhutan, providing a framework for further monitoring in this understudied, yet important, region of the Himalaya.
Archaeologists have long been called on to use geophysical techniques to locate unmarked graves in both archaeological and forensic contexts. Although these techniques—primarily ground-penetrating radar (GPR)—have demonstrated efficacy in this application, there are fewer examples of studies driven by Indigenous community needs. In North America, the location of ancestors and burial grounds is a priority for most Indigenous communities. We argue that when these Indigenous voices are equitably included in research design, the practice of remote sensing changes and more meaningful collaborations ensue. Drawing on Indigenous archaeology and heart-centered practices, we argue that remote-sensing survey methodologies, and the subsequent narratives produced, need to change. These approaches change both researchers’ and Indigenous communities’ relationships to the work and allow for the inclusion of Indigenous Knowledge (IK) in interpretation. In this article, we discuss this underexplored research trajectory, explain how it relates to modern GPR surveys for unmarked graves, and present the results from a survey conducted at the request of the Chipewyan Prairie First Nation. Although local in nature, we discuss potential benefits and challenges of Indigenous remote sensing collaborations, and we engage larger conversations happening in Indigenous communities around the ways these methods can contribute to reconciliation and decolonization.
Surface melting on Amery Ice Shelf (AIS), East Antarctica, produces an extensive supraglacial drainage system consisting of hundreds of lakes connected by surface channels. This drainage system forms most summers on the southern portion of AIS, transporting meltwater large distances northward, toward the ice front and terminating in lakes. Here we use satellite imagery, Landsat (1, 4 and 8), MODIS multispectral and Sentinel-1 synthetic aperture radar to examine the seasonal and interannual evolution of the drainage system over nearly five decades (1972–2019). We estimate seasonal meltwater input to one lake by integrating output from the regional climate model [Regional Atmospheric Climate Model (RACMO 2.3p2)] over its catchment defined using the Reference Elevation Model of Antarctica. We find only weak positive relationships between modeled seasonal meltwater input and lake area and between meltwater input and lake volume. Consecutive years of extensive melting lead to year-on-year expansion of the drainage system, potentially through a link between melt production, refreezing in firn and the maximum extent of the lakes at the downstream termini of drainage. These mechanisms are important when evaluating the potential of drainage systems to grow in response to increased melting, delivering meltwater to areas of ice shelves vulnerable to hydrofracture.
The Huron-Wendat have had their ancestors’ villages and burial sites investigated archaeologically for over 170 years. Past and ongoing land disturbance and invasive archaeological excavation have erased dozens of Huron-Wendat village sites in Ontario, hindering Huron-Wendat duty to care for their ancestors. Consequently, over the last 20 years, in addition to large-scale repatriation of ancestral remains, the Huron-Wendat have requested that archaeologists make every effort to avoid any further excavation of ancestral sites. This poses a new challenge for archaeologists about how to learn about the Huron-Wendat past with minimal disturbance to ancestral sites. Honoring the cultural responsibilities of the Huron-Wendat, the authors have employed minimally invasive remote sensing methods of investigation on Ahatsistari, a forested early seventeenth-century Huron-Wendat village site in Simcoe County, Ontario. Remote sensing methods (e.g., magnetic susceptibility survey, high-resolution soil chemistry sampling, and metal detector survey) have revealed village limits and the possible location and orientation of longhouses, providing essential information in support of the Huron-Wendat imperative to find, assess, and preserve as many of their archaeological sites as possible. This is to protect the ancestors, learn from the ancestors, and preserve ancestral sites and related landscapes for future generations.
In recent years, researchers have focused on the applications of uncrewed aerial vehicles (UAVs) in environmental remote sensing tasks. However, studies on glacier monitoring using UAV technology are relatively scarce, especially for high mountain glacier monitoring. To explore the feasibility of UAV technology for high mountain glaciers, four UAV surveys were deployed on two glaciers of the central Tibetan Plateau. Based on the images retrieved by UAV in 2017 and 2019, orthomosaics and digital elevation models were produced to quantify the length, area and elevation changes in the ablation zone of these two glaciers at different times. Additionally, we utilized several Landsat scenes to derive glacier changes over the last 30 years and combined these with the UAV data to assess the advantages and disadvantages of UAV technology in mountain glacier monitoring.
Glacier surges are periodic episodes of mass redistribution characterized by dramatic increases in ice flow velocity and, sometimes, terminus advance. We use optical satellite imagery to document five previously unexamined surge events of Sít’ Kusá (Turner Glacier) in the St. Elias Mountains of Alaska from 1983 to 2013. Surge events had an average recurrence interval of ~5 years, making it the shortest known regular recurrence interval in the world. Surge events appear to initiate in the winter, with speeds reaching up to ~25 m d−1. The surges propagate down-glacier over ~2 years, resulting in maximum thinning of ~100 m in the reservoir zone and comparable thickening at the terminus. Collectively, the rapid recurrence interval, winter initiation and down-glacier propagation suggest Sít’ Kusá's surges are driven by periodic changes in subglacial hydrology and glacier sliding. Elevation change observations from the northern tributary show a kinematic disconnect above and below an icefall located 23 km from the terminus. We suggest the kinematic disconnect inhibits drawdown from the accumulation zone above the icefall, which leads to a steady flux of ice into the reservoir zone, and contributes to the glacier's exceptionally short recurrence interval.
Knowledge of glacier volume is crucial for ice flow modelling and predicting the impacts of climate change on glaciers. Rugged terrain, harsh weather conditions and logistic costs limit field-based ice thickness observations in the Himalaya. Remote-sensing applications, together with mathematical models, provide alternative techniques for glacier ice thickness and volume estimation. The objective of the present research is to assess the application of artificial neural network (ANN) modelling coupled with remote-sensing techniques to estimate ice thickness on individual glaciers with direct field measurements. We have developed two ANN models and estimated the ice thickness of Chhota Shigri Glacier (western Himalaya) on ten transverse cross sections and two longitudinal sections. The ANN model estimates agree well with ice thickness measurements from a ground-penetrating radar, available for five transverse cross sections on Chhota Shigri Glacier. The overall root mean square errors of the two ANN models are 24 and 13 m and the mean bias errors are ±13 and ±6 m, respectively, which are significantly lower than for other available models. The estimated mean ice thickness and volume for Chhota Shigri Glacier are 109 ± 17 m and 1.69 ± 0.26 km3, respectively.
This last chapter recreates the changes in the landscape inside the two parks and their surrounding area. To do so, it uses a trove of more than 800 aerial images from 1953 to 1980 (as well as government reports, newspaper articles, and legal cases) to reconstruct the landscape before, during, and after the settlement of tens of thousands of settlers at the borderland. The chapter documents the role of logging, as carried out by Brazilian colonization companies with indigenous labor, in permanently transforming the native subtropical Atlantic forest into cropland. It also cast light on road building as one of the factors allowing migration to the region. Inside the park, the chapter argues that what is now seen as pristine nature – the forested landscape of the parks – is the fruit of decades of often contradictory policies and practices.
Supraglacial lakes and rivers dominate the storage and transport of meltwater on the southwest Greenland Ice Sheet (GrIS) surface. Despite functioning as interconnected hydrologic networks, supraglacial lakes and rivers are commonly studied as independent features, resulting in an incomplete understanding of their collective impact on meltwater storage and routing. We use Landsat 8 satellite imagery to assess the seasonal evolution of supraglacial lakes and rivers on the southwest GrIS during the 2015 melt season. Remotely sensed meltwater areas and volumes are compared with surface runoff simulations from three climate models (MERRA-2, MAR 3.6 and RACMO 2.3), and with in situ observations of proglacial discharge in the Watson River. We find: (1) at elevations >1600 m, 21% of supraglacial lakes and 28% of supraglacial rivers drain into moulins, signifying the presence of high-elevation surface-to-bed meltwater connections even during a colder-than-average melt season; (2) while supraglacial lakes dominate instantaneous surface meltwater storage, supraglacial rivers dominate total surface meltwater area and discharge; (3) the combined surface area of supraglacial lakes and rivers is strongly correlated with modeled surface runoff; and (4) of the three models examined here, MERRA-2 runoff yields the highest overall correlation with observed proglacial discharge in the Watson River.
In this study, we use aerial photographs, satellite imagery and field observations to quantify changes in the area, terminus length, snowline elevation and surface elevation of eight glaciers in the Alexandra Fiord region, eastern Ellesmere Island, between 1959 and 2019. Comparisons to written and pictorial descriptions from the British Arctic Expedition extend the record of change in terminus position and surface elevation to 1875 for Twin Glacier. Glacier area at Alexandra Fiord decreased by a total of 15.77 ± 0.65 km2 (11.77 ± 0.49%) between 1959 and 2019, the mean end of summer snowline increased in elevation by 360 ± 84 m (8 ± 2 m a−1) between 1974 and 2019, and the glaciers thinned at an average rate of 0.60 ± 0.06 m a−1 between 2001 and 2018. Annual rates of terminus retreat were ~3–5 times higher over the period 1974–2019 compared to 1875–1974, and rates of thinning were ~2–3 times higher over 2001–18 compared to 1875–2001. Our results are consistent with rates of change determined for other glaciers of similar size on Ellesmere Island, and with accelerated rates of ice loss coincident with regional increases in air temperature of ~1.5°C since the early 1980s.
During the late nineteenth and early twentieth centuries, over 450 precolumbian and historic Indigenous agricultural fields were documented across the state of Wisconsin. Today, the vast majority of these features are generally assumed to have been destroyed. Focusing on the Wisconsin River basin, which has the highest concentration of known archaeological field systems in the Midwest, this study explores the potential of using historical aerial photographs to identify and interpret archaeological agricultural features. Relying on state site records, an archive of high-resolution 1930s aerial images, and modern lidar data, we carefully examine the region surrounding 59 sites where fields had previously been documented. At a quarter of the sites we investigated, we successfully identified both known and unrecorded archaeological features—including agricultural fields, effigy mounds, earthworks, and house basins—most of which have been destroyed by recent land use practices. Our analysis sheds light on the complexity and richness of the archaeological landscape, with vast agricultural spaces situated beyond traditional site boundaries, and suggests that precolumbian and historic Indigenous agricultural fields may have been much larger and more widespread than conventionally understood.
Multi-decadal mass loss estimates are available for few glaciers of Central Asia. On Abramov Glacier (Pamir-Alay, Kyrgyzstan), comprehensive long-term glaciological measurements have been carried out from 1968 to 1999 and re-initiated in 2011. A climatological interpretation of this benchmark glacier in Central Asia requires bridging the gap between historical and renewed measurements. This is achieved here by computing the geodetic mass balance from 1975 to 2015 using previously unreleased Soviet aerial imagery and Pléaides stereo-imagery. During 1975–2015, Abramov Glacier lost 2.2 km2 (8.2%) of its area. The mean annual thickness change was − 0.43 ± 0.14 m a−1 for the period 1975–2015, corresponding to a volume change of − 0.45 ± 0.15 km3. The average specific geodetic mass balance amounts to − 0.38 ± 0.12 m w.e. a−1. The 1975–2015 glacier mass loss lies within the range of glaciological and geodetic mass-balance estimates that were previously published for disparate and shorter time intervals since 1968. This study covers a much longer time period than earlier geodetic estimates and demonstrates the capacity to geodetically constrain glacier change at high spatial resolution in Central Asia using historic aerial imagery and Structure from Motion techniques. Therefore, it could serve as a benchmark for future studies of regional mass change.
A programmable borehole measurement system was deployed in hot water drilled ice holes during the ‘Bed Access and Monitoring of Ice Sheet History’ (BEAMISH) project to drill to the bed of the Rutford Ice Stream in West Antarctica. This system operates autonomously (no live data) after deployment, and records borehole diameter (non-contact measurement), water column pressure, heading and inclination. Three cameras, two sideways looking and one vertical, are also included for visual inspection of hole integrity and sediments. The system is small, lightweight (~35.5 kg) and low power using only 6 ‘D’ cell sized lithium batteries, making it ideal for transport and use in remote field sites. The system is 2.81 m long and 165 mm in diameter, and can be deployed attached to the drill hose for measurements during drilling or on its own deployment line afterwards. The full system is discussed in detail, highlighting design strengths and weaknesses. Data from the BEAMISH project are also presented in the form of camera images showing hole integrity, and sensor data used to calculate borehole diameter through the full length of the hole. These data are used to show confidence in hole verticality and subsurface cavity development and connection.
Surface albedo typically dominates the mass balance of mountain glaciers, though long-term trends and patterns of glacier albedo are seldom explored. We calculated broadband shortwave albedo for glaciers in the central Chilean Andes (33–34°S) using end-of-summer Landsat scenes between 1986 and 2020. We found a high inter-annual variability of glacier-wide albedo that is largely a function of the glacier fractional snow-covered area and the total precipitation of the preceding hydrological year (up to 69% of the inter-annual variance explained). Under the 2010–2020 ‘Mega Drought’ period, the mean albedo, regionally averaged ranging from ~0.25–0.5, decreased by −0.05 on average relative to 1986–2009, with the greatest reduction occurring 3500–5000 m a.s.l. In 2020, differences relative to 1986–2009 were −0.14 on average as a result of near-complete absence of late summer snow cover and the driest hydrological year since the Landsat observation period began (~90% reduction of annual precipitation relative to the 1986–2009 period). We found statistically significant, negative trends in glacier ice albedo of up to −0.03 per decade, a trend that would have serious implications for the future water security of the region, because glacier ice melt acts to buffer streamflow shortages under severe drought conditions.
The Drygalski Ice Tongue in East Antarctica stretches 90 km into the Ross Sea and influences the local ocean circulation, and persistence of the Terra Nova Bay Polynya. We examine the controls on the size of this floating ice body by comparing the propagation of six large fractures on the ice tongue's northern side using 21 years of Landsat imagery with hydrostatic ice thickness maps and strain rate calculations. We also apply a subglacial hydrology model to estimate the location and discharge from subglacial channels over the grounding line and compare these with basal channels identified along the ice tongue using remote sensing and airborne radar data. Our results suggest that large fractures are inhibited from full-width propagation by thicker ice between basal channels. We hypothesize that only once the ice tongue thins towards the terminus, can fractures propagate and cause large calving events. This suggests an important relationship between the melting of floating ice from subglacial and ocean sources and the expansion of fractures that lead to ice tongue calving.
In this study, our goal is to track internal ice layers on the Snow Radar data collected by NASA Operation IceBridge. We examine the application of deep learning methods on radar data gathered from polar regions. Artificial intelligence techniques have displayed impressive success in many practical fields. Deep neural networks owe their success to the availability of massive labeled data. However, in many real-world problems, even when a large dataset is available, deep learning methods have shown less success, due to causes such as lack of a large labeled dataset, presence of noise in the data or missing data. In our radar data, the presence of noise is one of the main obstacles in utilizing popular deep learning methods such as transfer learning. Our experiments show that if the neural network is trained to detect contours of objects in electro-optical imagery, it can only track a low percentage of contours in radar data. Fine-tuning and further training do not provide any better results. However, we show that selecting the right model and training it on the radar imagery from the start yields far better results.
The only complete inventory of New Zealand glaciers was based on aerial photography starting in 1978. While there have been partial updates using 2002 and 2009 satellite data, most glaciers are still represented by the 1978 outlines in contemporary global glacier databases. The objective of this project is to establish an updated glacier inventory for New Zealand. We have used Landsat 8 OLI satellite imagery from February and March 2016 for delineating clean glaciers using a semi-automatic band ratio method and debris-covered glaciers using a maximum likelihood classification. The outlines have been checked against Sentinel-2 MSI data, which have a higher resolution. Manual post processing was necessary due to misclassifications (e.g. lakes, clouds), mapping in shadowed areas, and combining the clean and debris-covered parts into single glaciers. New Zealand glaciers cover an area of 794 ± 34 km2 in 2016 with a debris-covered area of 10%. Of the 2918 glaciers, seven glaciers are >10 km2 while 71% is <0.1 km2. The debris cover on those largest glaciers is >40%. Only 15 glaciers are located on the North Island. For a selection of glaciers, we were able to calculate the area reduction between the 1978 and 2016 inventories.