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Satellite observations have been widely used to measure methane (CH4) emissions from the oil and gas (O&G) industry, particularly by revealing previously undocumented, very large emission events and basin-level emission estimates. However, the performance of retrieving CH4 mixing ratios from the short-wave infrared band of passive remote sensing instruments is spatially and temporally varied due to sunlight, earth surface properties, and atmospheric conditions. Thus, the reliability of satellites is also varied. To assess the reliability of passive remote sensing satellite instruments for routine monitoring of CH4 emissions, we investigated the global observational coverage of the TROPOMI (onboard the Sentinel-5P), which has been providing a daily global CH4 mixing ratio since 2017. A 0.1° x 0.1° gridded global map that indicates the average number of days with valid observations from TROPOMI from 2019 to 2021 was generated by following the measurement retrieval quality-assurance threshold (≥0.5). We found TROPOMI had promising observational coverage over dryland regions (maximum: 58.6%) but limited coverage over tropical regions and high latitudes (minimum: 0%). Cloud cover and solar zenith angle were the primary factors at high latitudes, while aerosol optical thickness was the primary factor over dryland regions. To further assess the country-level reliability of satellites for detecting and quantifying CH4 emissions from the O&G sector, we extracted the average annual TROPOMI observational coverage (TOC) over O&G infrastructure for 160 countries. Seven of the top-10 O&G-producing countries had an average annual TOC < 10% (< 36 days per year), which indicates the limited ability to routinely identify large emissions events, track their duration, and quantify emissions rates using inverse modelling. We further assessed the potential performance of the latter by combining TOC and the uncertainties from the global O&G inventory. Results inverse modeling with CH4 measurements from TROPOMI may only be accurate for quantifying emissions from O&G sectors in countries located in dryland and mid-latitude regions. Conclusively, the current passive-sensing satellites have low potential for frequent monitoring of large methane emissions from O&G sectors in countries located in tropical and high latitudes (e.g., Canada, Russia, Brazil, Norway, and Venezuela). Therefore, alternative methods should be considered for routine emissions monitoring in the corresponding regions.

The occurrence and emissions of methane (CH4) from above-ground urban natural gas infrastructure is poorly understood. Compared to below-ground infrastructure, these facilities are relatively easy to monitor and maintain and present an opportunity for cost-effective CH4 reductions. We present a case study and methodology for detecting, attributing, and quantifying CH4 emissions from fence line measurements at above-ground natural gas facilities in the City of Calgary, Alberta, Canada. We produced bounding-box concentration maps by walking around the outer fence of 33 facilities with a backpack-configured trace gas analyzer and a tablet with integrated GPS. Wind measurements were acquired simultaneously from a fixed location on site with a 3D sonic anemometer. We fused geolocation, CH4 concentration, and wind data to determine the likelihood each facility was emitting. We found one definitive leak by carrying out measurements directly alongside an exposed section of pipe. Based on the presence of methyl mercaptan (CH3SH) odor, peak ΔCH4, and the difference between downwind and upwind ΔCH4, we interpret a high plausibility that 22 facilities were emitting CH4, followed by 2 with a medium plausibility, and 8 with a low plausibility. Once verified to plausibly emit, these data were used to estimate emissions flux at six facilities where near-field obstructions were limited. The estimated emissions flux for six facilities was 66.31 mg CH4 s-1, or 2.1 tonnes CH4 yr-1 if this flux remained constant. Overall, this study indicates most above-ground natural gas facilities surveyed in Calgary were emitting CH4. These facilities represent easy mitigation targets for reducing CH4 emissions and improving environmental performance. To our knowledge, this is the first study to integrate qualitative and quantitative information to predict detection plausibility in a complex measurement setting.Implications: The fence line methodology outlined in this study represents an extension of source assessment modes in the US EPA's Other Test Method 33A for human portable systems. This has implications for standardization of emissions measurement in situations where other platforms (e.g., vehicles) are less effective due to access limitations. We believe the methodology presented could become a recognized standard based on performance from controlled testing and added to the regulatory toolkit for emissions verification and compliance.

Recent advances in sea floor measurements and modelling have revealed new insight into submarine channel processes; however, understanding how these short‐term perspectives influence long‐term evolution of submarine channels has been limited by the difficulty in linking processes to products in the stratigraphic record. Outcrops present opportunities to characterise the detailed internal architecture of deep‐water channel fills over a wide range of timescales, but obtaining observations is compounded by challenges in outcrop accessibility and perspective along broad exposures. To demonstrate the potential value of modern remote sensing techniques in supplementing fieldwork, an extensive dip‐oriented outcrop exposure of Cretaceous deep‐water channel deposits was re‐evaluated using a 3D digital outcrop model generated from uninhabited/unmanned aerial vehicle photogrammetry. Results confirmed previous field‐based documentation of depositional element‐scale stratigraphic architecture, but also revealed nuanced internal detail that was not captured from field‐based perspectives alone. Subtle internal channel‐fill architecture, including discontinuous sandstone wedges and the interpreted stratigraphic products of upslope‐migrating bedforms, are also recognised. This study demonstrates the sedimentary detail that can be uncovered by integrating conventional field‐based approaches limited by viewable scale, perspective, and/or accessibility, with emerging remote sensing techniques. The unmanned aerial vehicle photogrammetry approach used here provides valuable supplemental data in the investigation of deep‐water channel system deposits and has the potential to overcome inherent challenges in outcrop mapping for numerous applications.

Multi-sensor vehicle systems have been implemented in large-scale field programs to detect, attribute, and estimate emissions rates of methane (CHsub4/sub) and other compounds from oil and gas wells and facilities. Most vehicle systems use passive sensing; they must be positioned downwind of sources to detect emissions. A major deployment challenge is predicting the best measurement locations and driving routes to sample infrastructure. Here, we present and validate a methodology that incorporates high-resolution weather forecast and geospatial data to predict measurement locations and optimize driving routes. The methodology estimates the downwind road intersection point (DRIP) of theoretical CHsub4/subplumes emitted from each well or facility. DRIPs serve as waypoints for Dijkstra's shortest path algorithm to determine the optimal driving route. We present a case study to demonstrate the methodology for planning and executing a vehicle-based concentration mapping survey of 50 oil and gas wells near Pecos, Texas. Validation was performed by comparing DRIPs with 174 CHsub4/subplumes measured by vehicle surveys of oil and gas wells and facilities in Alberta, Canada. Results indicate median Manhattan distances of 145.8 m between DRIPs and plume midpoints and 160.3 m between DRIPs and peak plume enhancements. A total of 46 (26%) of the plume segments overlapped DRIPs. Locational errors of DRIPs are related to misattributions of emissions sources and discrepancies between modeled and instantaneous wind direction measured when the vehicle intersects plumes. Although the development of the methodology was motivated by CHsub4/subemissions from oil and gas facilities, it should be applicable to other types of point source air emissions from known facilities.iImplications:/iThis paper presents and validates a method that addresses the challenge of measuring industrial emissions from public roads. The method can increase the effectiveness and efficiency of targeted vehicle-based emissions surveys where the locations of potential sources are known. We believe the method has broad application in addition to the upstream oil and gas context it was designed for.

We present observations, measurements, and modeling of an enigmatic eolian bedform pattern of cross-wind alternating, wind-parallel corridors of megaripples and smaller bedforms (“megaripple stripes”). Megaripple corridors have taller bedforms, longer wavelengths, and coarser surface sediment than intervening smaller bedform corridors. We document examples from Earth (Argentina, Namibia, United States, Iran, Peru, and China) and Mars. Using a reduced complexity model, we show that megaripples and megaripple stripes initiate under the influence of two eolian transport length scales: long-hop saltons and short-hop reptons. The self-organizing stripe pattern manifests in a narrow range of repton concentrations and develops into more typical megaripples as the surface repton concentration increases. We show that the three-dimensional topography of simulated megaripple stripes closely resembles natural megaripple stripes at Oceano Dunes, California, USA. By tracking repton surface concentration and spatial autocorrelation during simulations, we show that the striped pattern initiates from local repton concentrations of sufficient size to serve as megaripple nuclei that seed the striped pattern. Results suggest that megaripple stripes may have a simple and robust formation mechanism.

Small aerial drones are used in a growing number of commercial applications. However, drones cannot fly in all weather, which impacts their reliability for time-sensitive operations. The magnitude and global variability of weather impact is poorly understood. We explore weather-limited drone flyability (the proportion of time drones can fly safely) by comparing historical wind speed, temperature, and precipitation data to manufacturer-reported thresholds of common commercial and weather-resistant drones with a computer simulation. We show that global flyability is highest in warm and dry continental regions and lowest over oceans and at high latitudes. Median global flyability for common drones is low: 5.7 h/day or 2.0 h/day if restricted to daylight hours. Weather-resistant drones have higher flyability (20.4 and 12.3 h/day, respectively). While these estimates do not consider all weather conditions, results suggest that improvements to weather resistance can increase flyability. An inverse analysis for major population centres shows the largest flyability gains for common drones can be achieved by increasing maximum wind speed and precipitation thresholds from 10 to 15 m/s and 0-1 mm/h, respectively.

We report a case study using drone-based imagery to develop a pre-disaster 3-D map of downtown Victoria, British Columbia, Canada. This represents the first drone mapping mission over an urban area approved by Canada's aviation authority. The goal was to assess the quality of the pre-disaster 3-D data in the context of geospatial accuracy and building representation. The images were acquired with a senseFly eBee Plus fixed-wing drone with real-time kinematic/post-processed kinematic functionality. Results indicate that the spatial accuracies achieved with this drone would allow for sub-meter building collapse detection, but the non-gimbaled camera was insufficient for capturing building facades.

Small aerial drones are used in a growing number of commercial applications. However, drones cannot fly in all weather, which impacts their reliability for time-sensitive operations. The magnitude and global variability of weather impact is poorly understood. We explore weather-limited drone flyability (the proportion of time drones can fly safely) by comparing historical wind speed, temperature, and precipitation data to manufacturer-reported thresholds of common commercial and weather-resistant drones with a computer simulation. We show that global flyability is highest in warm and dry continental regions and lowest over oceans and at high latitudes. Median global flyability for common drones is low: 5.7 h/day or 2.0 h/day if restricted to daylight hours. Weather-resistant drones have higher flyability (20.4 and 12.3 h/day, respectively). While these estimates do not consider all weather conditions, results suggest that improvements to weather resistance can increase flyability. An inverse analysis for major population centres shows the largest flyability gains for common drones can be achieved by increasing maximum wind speed and precipitation thresholds from 10 to 15 m/s and 0–1 mm/h, respectively.

Yardangs are streamlined ridges that form in arid environments on Earth and Mars through wind-driven abrasion of consolidated substrates. Currently, there is limited consensus on the mechanisms that initiate and establish patterns of yardangs on the landscape. In this work, we examine the spatial organization of yardangs in the Campo de Piedra Pomez ignimbrite deposit of northwestern Argentina and identify evidence of antecedent controls on yardang patterns and formation. We mapped 14,826 yardangs in the region using a high-resolution digital elevation model (DEM) and satellite imagery. We classified yardangs as points using a two-stage decision rule based on morphology and spectral characteristics. Point pattern analysis shows that yardangs in the study area are not randomly distributed and commonly exhibit directional anisotropy in point pattern. The anisotropic pattern manifests as bands of closely-spaced yardangs oriented transverse to the dominant northwesterly wind direction. We hypothesize that banding is controlled by pre-existing antecedent topography in the bedrock, such as fumaroles or ridges associated with pyroclastic flow deposits. We present evidence from other locations on Earth and Mars to illustrate that the transverse banding is a common pattern in yardang landscapes.

The potential of high resolution 3D datasets is being increasingly realized in an expanding number of geoscience applications. However, sharing of these datasets and interpretations requires end-us...

We examined the horizontal and vertical accuracy of LiDAR data acquired from an unmanned aerial vehicle (UAV) at a field site with six vegetation types: coniferous trees, deciduous trees, short grass (0–0.3 m height), tall grass (>0.3 m height), short shrubs (0–1 m height), and tall shrubs (>1 m height). The objective was to assess positional accuracy of the ground surface in the context of digital mapping standards, and to determine how different vegetation types affect vertical accuracy. The data were acquired from a single-rotor vertical takeoff and landing UAV equipped with a Riegl VUX-1UAV laser scanner, KVH Industries 1750 IMU, and dual NovAtel GNSS receivers. Reference measurements of ground surface elevation were acquired with conventional field surveying techniques. Accuracy was evaluated using methods in the 2015 American Society for Photogrammetry and Remote Sensing (ASPRS) Positional Accuracy Standards for Digital Geospatial Data. Results show that horizontal accuracy and vegetated vertical accuracy at the 95% confidence level were 0.05 and 0.24 m, respectively. Median vertical errors significantly differed among 10 of 15 vegetation type pairs, highlighting the need to account for variations of vegetation structure. According to the 2015 ASPRS standards, the reported errors fulfill the requirements for mapping at the 2 and 8 cm horizontal and vertical class levels, respectively.

Aeolian rat-tails (ARTs) are a previously undocumented, regionally-ubiquitous aeolian abrasion feature observed on matrix-supported ignimbrite surfaces in the Puna Plateau of Northwest Argentina. ARTs consist of an abrasion-resistant lithic clast projecting above the surface with a lee tail or ‘keel’ in the more erodible matrix. Size is controlled by the dimensions of the windward lithic clast, ranging from centimetre to meter scale; spatial density varies with clast content, which may reflect variations in ignimbrite facies. Field observations suggest ARTs follow a definable evolutionary sequence. First, an abrasion-resistant lithic clast contained within the ignimbrite is exposed to abrasion at the surface. Impacts from abrading particles erode the softer ignimbrite matrix adjacent to the clast. The clast shelters the leeward surface under a unimodal abrasion direction, creating a tail that tapers downwind and elongates as the clast emerges. Clasts become dislodged from the matrix as the surrounding surface erodes, ultimately destroying the feature if the clast is small enough to be mobilized directly by wind or impacting particles. This evolutionary sequence explains the morphology of ARTs and the presence of loose clasts on the ignimbrite surface, which contributes to the development of other landforms in the region, such as periodic bedrock ridges, yardangs, and megaripples. Satellite and rover images suggest similar features also exist on Mars. Because the formation and preservation of ARTs is contingent on unimodal abrasion direction, their orientation can be used as an indicator of long-term aeolian sediment transport direction.

Native grassland restorations are often unsuccessful as a consequence of unreliable seed sources and competition from weeds and agronomic species. To improve on conventional approaches, we tested whether native hay can be used as a seed source for restoring native mixedgrass prairie on oil and gas well sites and associated disturbed areas. We also assessed the recovery of grassland that had been cut to harvest native hay. We assessed three wellsites seeded with native hay seven years earlier to evaluate longer term recovery, and they showed significant similarity to controls in adjacent grassland. Additionally, in 2012, five wellsites and an access road were seeded with native hay cut from grassland close to the sites. Grassland cut for native hay recovered within one year, showing similar species composition. In the second year, native hay restored wellsites had significant weedy annual cover; nevertheless, native grasses and forbs germinated, particularly needle grasses, wheatgrasses, and bluegrasses. Three of the native hay restored wellsites were sprayed with a non-selective herbicide in the third year; however, the remaining sites showed good recovery in the third year, with native grasses replacing most of the original weedy species. Collectively, results from this research suggest seeding from native hay is a successful and sustainable technique for restoring native vegetation cover and diversity on industrial disturbances in native grasslands.

Transverse aeolian ridges (TARs) are a distinct aeolian bedform found on Mars. The formative processes, evolution, and geological significance of TARs is poorly understood. Fundamentally, it is unknown whether TARs are dunes, mega-ripples, or another bedform type. We examined aeolian bedforms in the Lut Desert of Iran as a terrestrial analog for Martian TARs. From an objective sampling strategy with high-resolution satellite imagery, we developed a large morphometric dataset for comparison with existing Martian TARs. We also examined the dynamics of the Lut bedforms between 2004 and 2012 to determine if they were static or migrating. Results indicate that the range in the dimensions (length, width, height, and wavelength) of the Lut bedforms and Martian TARs overlap, suggesting Lut bedforms are a viable terrestrial TAR analog. Our sample yielded median values of 55.18 m, 9.80, 1.02 m, and 20 m for length (longest planview axis), width (shortest planview axis), height, and wavelength, respectively. Cumulative log-frequency plots of morphometric parameters suggest the sample is from a single population and process mechanism. Although the vast majority of Lut bedforms examined were static between 2004 and 2012, some migrated up to 0.09 myr −1 on average. This is much slower than nearby dunes (4–12 myr −1 ), but is explained by the existence of a surface lag of coarse particles on the TAR-like bedforms. The combination of morphometry, surface sedimentology, and slow migration rate indicate the Lut bedforms are mega-ripples, which provides evidence supporting interpretation of Martian TARs as mega-ripples. Testing the mega-ripple hypothesis for Martian TARs requires measurements of their sedimentology, which may be possible with the Mars Science Laboratory rover Curiosity, as well as expanded measurements of TAR morphometry to constrain their size, shape, and scaling.

UAV incidents were analyzed using data from Transport Canada’s Civil Aviation Daily Occurrence Reporting System (CADORS). Between 5 November 2005 and 31 December 2016 a total of 355 incidents were reported in Canadian airspace. The largest number involved UAV sightings (66.5%) and close encounters with piloted aircraft (22.3%). These incidents increased markedly after 2013, with the highest number in British Columbia, followed by Ontario, Quebec, Alberta, and Manitoba. The vast majority of UAV incident reports were filed by pilots of piloted aircraft. Typically, airspace at altitudes greater than 400 feet above ground level (AGL) is off limits to UAVs; however, of the 270 incidents in the CADORS database with UAV altitude reported, 80.4% were above 400 feet AGL and 62.6% were above 1000 feet AGL. Of the 268 incidents with reported horizontal distance to the nearest aerodrome, 74.6% occurred or likely occurred within five nautical miles (M), and of those 92.4% and 76.6% were reported above 100 and 300 feet AGL, respectively. Collectively, the CADORS data indicate that the overwhelming majority of UAV incidents reported in Canada were airspace violations. These results can guide future risk mitigation measures, hardware and software solutions, and educational campaigns to increase airspace safety.

Using HiRISE digital terrain models (DTMs), we developed a large morphological dataset to examine the three-dimensional shape, size, and scaling of Martian transverse aeolian ridges (TARs). Considerable debate exists on the characteristic morphology of TARs and the origins of these enigmatic bedforms. Some researchers suggest polygenesis or multiple classes of similar bedforms. Reliably characterizing the morphology of TARs is an essential prerequisite to developing and evaluating process-based models of TAR genesis and unraveling aeolian processes on the surface of Mars. We present measurements of TAR morphology from a large, DTM-derived dataset (n = 2295). We focused on TARs with ‘simple’ morphologies in order enable more defensible discretization. Histograms and cumulative log-frequency plots of morphometric parameters (length, width, height, elongation ratio, and wavelength) indicate the sample represents a continuum of bedforms from a single population. A typical TAR from our dataset is 88.5 m long (longest planview axis), 17.3 m wide (shortest planview axis), 1.3 m tall, and has a wavelength of 25.8 m. Combined with these data, the bulk of evidence presented to date suggests that interpreting TARs as megaripples is the most viable working hypothesis.

Complex landscapes with high topographic relief and intricate geometry present challenges for complete and accurate mapping of both lateral (x, y) and vertical (z) detail without deformation. Although small uninhabited/unmanned aerial vehicles (UAVs) paired with structure-from-motion (SfM) image processing has recently emerged as a popular solution for a range of mapping applications, common image acquisition and processing strategies can result in surface deformation along steep slopes within complex terrain. Incorporation of oblique (off-nadir) images into the UAV⁻SfM workflow has been shown to reduce systematic errors within resulting models, but there has been no consensus or documentation substantiating use of particular imaging angles. To address these limitations, we examined UAV⁻SfM models produced from image sets collected with various imaging angles (0⁻35°) within a high-relief ‘badland’ landscape and compared resulting surfaces with a reference dataset from a terrestrial laser scanner (TLS). More than 150 UAV⁻SfM scenarios were quantitatively evaluated to assess the effects of camera tilt angle, overlap, and imaging configuration on the precision and accuracy of the reconstructed terrain. Results indicate that imaging angle has a profound impact on accuracy and precision for data acquisition with a single camera angle in topographically complex scenes. Results also confirm previous findings that supplementing nadir image blocks with oblique images in the UAV⁻SfM workflow consistently improves spatial accuracy and precision and reduces data gaps and systematic errors in the final point cloud. Subtle differences among various oblique camera angles and imaging patterns suggest that higher overlap and higher oblique camera angles (20⁻35°) increased precision and accuracy by nearly 50% relative to nadir-only image blocks. We conclude by presenting four recommendations for incorporating oblique images and adapting flight parameters to enhance 3D mapping applications with UAV⁻SfM in high-relief terrain.

New mobile platforms such as vehicles, drones, aircraft, and satellites have emerged to help identify and reduce fugitive methane emissions from the oil and gas sector. When deployed as part of leak detection and repair (LDAR) programs, most of these technologies use multi-visit LDAR (MVL), which consists of four steps: (a) rapidly screen all facilities, (b) triage by emission rate, (c) follow-up with close-range methods at the highest-emitting sites, and (d) conduct repairs. The proposed value of MVL is to identify large leaks soon after they arise. Whether MVL offers an improvement over traditional single-visit LDAR (SVL), which relies on undirected close-range surveys, remains poorly understood. We use the Leak Detection and Repair Simulator (LDAR-Sim) to examine the performance and cost-effectiveness of MVL relative to SVL. Results suggest that facility-scale MVL programs can achieve fugitive emission reductions equivalent to SVL, but that improved cost-effectiveness is not guaranteed. Under a best-case scenario, we find that screening must cost < USD 100 per site for MVL to achieve 30% cost reductions relative to SVL. In scenarios with non-target vented emissions and screening quantification uncertainty, triaging errors force excessive close-range follow-up to achieve emissions reduction equivalence. The viability of MVL as a cost-effective alternative to SVL for reducing fugitive methane emissions hinges on accurate triaging after the screening phase.

Alternative leak detection and repair (alt-LDAR) programs are being introduced by regulators to provide flexibility in how oil and gas producers manage fugitive methane emissions. However, emissions reduction equivalence must be established between a proposed program and a regulatory standard. We present LDAR-Sim, an open-source, agent-based numerical model for evaluating LDAR program performance. Novel functionality includes the ability to: (1) set facility-specific LDAR requirements, (2) simultaneously deploy multiple technologies, (3) integrate screening and close-range methods, (4) include environmental constraints, and (5) explore the impact of design emissions on screening technologies. We demonstrate LDAR-Sim in two case studies with diverse LDAR programs deployed on real assets. We find that equivalence determinations depend on explicit definition of reference standards, including weather and labour availability. Screening program performance is sensitive to the confounding presence of design emissions and to decision-making strategies that guide follow-up inspections. When comparing programs, differences in simulated performance are sensitive to leak production and null repair rates, two elusive parameters used in previous studies. Future work should better constrain empirical inputs and validate specific LDAR programs as alt-LDAR deployment increases. Regulators and producers can use LDAR-Sim to facilitate the adoption of emerging technologies but should be aware of its limitations.

There is growing application of small unmanned aerial vehicles (UAVs) for detecting, enumerating, and monitoring wildlife. However, little is known about how the sound from UAVs may be affecting wildlife being studied. We quantified sound levels of 2 UAVs to determine minimum altitudes they can fly before being aurally detected by wildlife. We tested a small quadcopter (SkyRanger; Aeryon Labs, Inc., Waterloo, ON, Canada) and a fixed-wing platform (eBee; Sensefly Ltd., Cheseaux-sur-Lausanne, Vaud, Switzerland) at the University of Calgary in Calgary, Alberta, Canada, between 1000 and 1200 hours on 27 September 2014. We modeled sound propagation and attenuation in relation to the lower hearing thresholds for 3 game species and 2 species of predators. Results indicate that the UAV sound levels differed in the lower frequency ranges, but were otherwise similar above 1.25 kHz. The domestic cat (Felis silvestris catus) has the lowest hearing threshold, with the capacity to hear both UAVs from the furthest distance; whereas, the mallard (Anas platyrhynchos) has the greatest hearing threshold, which means UAVs can be closer before being aurally detected. Because flying height is related to image resolution, our results indicate that the ability to detect some wildlife species may be affected by the need to fly higher to minimize sound disturbance, potentially requiring higher resolution cameras than those currently used. Also, additional flight permitting may be required if modeling indicates a UAV must fly at a greater height to avoid a behavioral response by the target species. © 2016 The Wildlife Society.

The Bigstick and Seward Sand Hills are possibly two of the oldest dune fields within the late Wisconsin glaciated regions of the Northern Great Plains. As with most Northern Great Plains dune fields, source sediments are former proglacial outwash sands. Thus, Holocene dune construction is primarily related to spatial–temporal variations in surface cover and transport capacity, rather than renewed sediment input. However, eolian landscape reconstructions on the Northern Great Plains have been temporally constrained to recent periods of activity, as older episodes of deposition are typically reworked by younger events. In this study, sediment cores from shallow lacustrine basins and interdune areas provide an improved record of Holocene eolian sand deposition. Eolian sand accumulation in the interdunes and basins occurred between 150 and 270 years ago, 1.9 and 3.0 ka, 5.4 and 8.6 ka, and prior to ca. 10.8 ka. These episodes of sand accumulation were bracketed by lacustrine deposition and soil formation, which represented wetter conditions. Other than mid-Holocene dune activity, which may be related to peak warmth and aridity, most periods of eolian sand accumulation coincided with cooler but drier climatic events such as the Younger Dryas, late-Holocene cooling prior to the Medieval Climatic Anomaly, and the ‘Little Ice Age’. These depositional episodes are also spatially represented by other dune fields in the region, providing a broad-scale view of the connections between past climatic events and eolian landscape evolution on the Northern Great Plains.

The National Wind Erosion Research Network was established in 2014 as a collaborative effort led by the United States Department of Agriculture’s Agricultural Research Service and Natural Resources Conservation Service, and the United States Department of the Interior’s Bureau of Land Management, to address the need for a long-term research program to meet critical challenges in wind erosion research and management in the United States. The Network has three aims: (1) provide data to support understanding of basic aeolian processes across land use types, land cover types, and management practices, (2) support development and application of models to assess wind erosion and dust emission and their impacts on human and environmental systems, and (3) encourage collaboration among the aeolian research community and resource managers for the transfer of wind erosion technologies. The Network currently consists of thirteen intensively instrumented sites providing measurements of aeolian sediment transport rates, meteorological conditions, and soil and vegetation properties that influence wind erosion. Network sites are located across rangelands, croplands, and deserts of the western US. In support of Network activities, http://winderosionnetwork.org was developed as a portal for information about the Network, providing site descriptions, measurement protocols, and data visualization tools to facilitate collaboration with scientists and managers interested in the Network and accessing Network products. The Network provides a mechanism for engaging national and international partners in a wind erosion research program that addresses the need for improved understanding and prediction of aeolian processes across complex and diverse land use types and management practices.

Subglacial bed forms (drumlins, ribbed moraines, and megascale glacial lineations) are enigmatic repetitive flow-parallel and flow-transverse landforms common in glaciated landscapes. Their evolution and morphology are a potentially powerful constraint for ice sheet modeling, but there is little consensus on bed form dynamics or formative mechanisms. Here we explore shallow sediment bed form dynamics via a simple model that iterates (i) down-flow till flux, (ii) pressure gradient-driven till flux, and (iii) entrainment and deposition of sediment. Under various boundary conditions, replicas of subglacial bed forms readily emerge. Bed form dynamics mirror those in subaqueous and aeolian domains. Transitions between ribbed moraines and elongate flow-parallel bed forms are associated with increasing ice speeds and declining sediment thickness. These simulations provide quantitative flux estimates and suggest that widely observed transitions in shallow sediment subglacial bed forms (e.g., ribbed moraines to drumlinoids to megascale glacial lineations) are manifestations of subtle variations in ice velocity and sediment thickness.

Strong winds can be a dominant characteristic of the climate in the alpine biogeographic zone and can reach speeds capable of causing people to lose balance or even blowing them over. However, in contrast to urban settings, where a considerable body of literature has examined mechanical effects of wind on people, in alpine zones the hazard associated with wind is almost entirely based on anecdotal evidence and remains largely unquantified. In this article we use archival weather station data to determine the wind hazard in the alpine zone above treeline (2543m amsl) along a popular hiking trail in the Kananaskis region of Alberta, Canada. Drawing on pedestrian wind research, we define hazardous wind at this location as any recorded wind speed >22.5ms−1. We assess wind hazard based on hourly wind speed and daily maximum gust speed for the periods 2000–2013 and 2008–2013, respectively. Results indicate that hazardous winds are almost always southwesterly, consistent with the prevailing wind, and can occur at any time of the year, but are most common in autumn and winter. Daily maximum gusts >22.5ms−1 occurred every other day on average, while hourly wind speed >22.5ms−1 occurred for 1.3–6.4% of the year. Also noteworthy is that category 1 and 2 hurricane-level wind speeds (33–42 and 43–49ms−1, respectively) were recorded at this site. The peak of category 1 wind speeds occurred in 2011 (103h in total or 1.2% of the year), while the peak in category 2 wind speeds occurred in 2009 (10h total or 0.1% of the year). A review of synoptic conditions during strong wind events suggests they are likely driven by downslope winds associated with mountain wave amplification and lee cyclogenesis. Overall, this study serves as an example to demonstrate that wind hazard in the alpine zone can be considerable and should be assessed in greater detail at all locations where people are likely to encounter strong winds.

The Puna Plateau of northwestern Argentina is a promising region for analogue investigations of Martian aeolian processes owing to its high altitude, low atmospheric pressure, aridity, geology, and widespread granular and bedrock aeolian landforms. Despite a growing body of research about the region's enigmatic aeolian landforms, little is known about the contemporary aeolian environment, processes, and landscape dynamics. To address this gap, we used a combination of modelled weather data, satellite imagery, and field measurements to characterize the wind regime, aeolian sediment transport, and allied surface changes. The study focused on the Campo de Piedra Pomez (CPP) – a volcanic landscape with a variety of Mars analogue landforms: gravel-mantled megaripples, yardangs, ventifacts, periodic bedrock ridges, and aeolian rat-tails. Modelled weather data from the European Center for Medium-Range Forecasting's ERA-Interim reanalysis dataset confirm the contemporary dominance of northwesterly winds in this region, consistent with the primary orientation of yardangs. These data also indicate the presence of less frequent southeasterly winds, which may explain why re-entrant profiles are observed on the southeast flanks of a small portion of the yardang population, and why some aeolian rat-tails point to the northwest. Observations from multi-temporal satellite imagery indicate that deposition and displacement of small sediment patches overlying ignimbrite bedrock is relatively common across the region. Samples retrieved from sediment traps deployed over one year in the region suggest a broad range of particle densities are mobilized by wind, which implies a wide range of wind speed for fluid entrainment. Conventional aeolian transport models do not consider the effects of particle density variations on transport processes. However, in areas with multiple density sediment present, our results point towards a need for aeolian models to consider density when quantifying and qualifying sediment transport.

Geographic object-based image analysis (GEOBIA) is a remote sensing image analysis paradigm that defines and examines image-objects: groups of neighboring pixels that represent real-world geographic objects. Recent reviews have examined methodological considerations and highlighted how GEOBIA improves upon the 30+ year pixel-based approach, particularly for H-resolution imagery. However, the literature also exposes an opportunity to improve guidance on the application of GEOBIA for novice practitioners. In this paper, we describe the theoretical foundations of GEOBIA and provide a comprehensive overview of the methodological workflow, including: (i) software-specific approaches (open-source and commercial); (ii) best practices informed by research; and (iii) the current status of methodological research. Building on this foundation, we then review recent research on the convergence of GEOBIA with deep convolutional neural networks, which we suggest is a new form of GEOBIA. Specifically, we discuss general integrative approaches and offer recommendations for future research. Overall, this paper describes the past, present, and anticipated future of GEOBIA in a novice-accessible format, while providing innovation and depth to experienced practitioners.

We report a case study using drone-based imagery to develop a pre-disaster 3D map of downtown Victoria, British Columbia, Canada. This represents the first drone mapping mission over an urban area approved by Canada’s aviation authority. The goal was to assess the quality of the pre-disaster 3D data in the context of geospatial accuracy and building representation. The images were acquired with a senseFly eBee Plus fixed-wing drone with real-time kinematic/post-processed kinematic functionality. Results indicate that the spatial accuracies achieved with this drone would allow for sub-meter building collapse detection, but the non-gimbaled camera was insufficient for capturing building facades.

Remotely sensed glaciological measurements can be expensive, often involving a trade-off between resolution, scale, and frequency. We report on a case study in which two low-cost techniques were used to generate digital elevation models and orthomosaics of an Arctic glacier in consecutive ablation seasons. In the first aerial survey we used an unmanned aerial vehicle and acquired images autonomously. The following year we took advantage of the helicopter used for site access, and were able to acquire images manually, for little additional helicopter time. We present a preliminary assessment of accuracy and apply these data to measure glacier thinning and motion.

We present a first assessment of UAS-derived orthoimagery and digital elevation data in the context of newly-released accuracy standards for digital geospatial data developed by the American Society for Photogrammetry and Remote Sensing. We outline results from two case studies using a commercially-available UAS, photogrammetry software, and an array of ground control and check points. Radial horizontal and vertical root-mean-square-errors (RMSE) were calculated as 0.05 m and 0.06 m, respectively, for one site, and 0.08 m and 0.03 m, respectively, for the other. Under the 1990 ASPRS standards, both surveys meet the requirements for Class 1 accuracy at the 1:500 map scale and at the 0.50 m contour interval. Under the newly-developed ASPRS standards, the reported errors fulfill the requirements for both horizontal and vertical mapping at the 10 cm RMSE level. Overall, these results provide initial direction for practitioners considering UAS surveying in the context of accuracy standards.

Periodic bedrock ridges (PBRs) are unexplained aeolian landforms discovered on Mars. PBR morphology and length scale resemble megaripples or small reversing dunes, but PBRs are eroded directly into bedrock. In this article we describe the first identified terrestrial PBRs from the Puna plateau of Argentina and present a hypothesis for their formation. The PBRs have formed in ignimbrite bedrock and are morphologically similar to nearby gravel megaripples. Observations along a landscape continuum provide basis for a genetic link between PBRs and gravel megaripples. First, gravel megaripples develop from lithics and pumice eroded from ignimbrite. The lithic clasts organize on the surface, forming megaripple crests and locally protecting the underlying ignimbrite. Exposed ignimbrite in troughs between the megaripples erodes and deepens as the ignimbrite topography evolves into a series of wind-transverse bedrock ridges (incipient PBRs) that mimic the pattern of overlying megaripples. The megaripples and incipient PBRs migrate downwind together and develop patterning indicative of bedform interactions with collisions, lateral linking, and ejections. PBRs emerge when the supply of lithics decreases and the crests become exposed by megaripple detachment. With crests exposed, PBRs appear to evolve into scalloped terrain due to abrasion. On Mars, the juxtaposition of megaripples and PBRs in some areas implies a similar evolutionary pathway whereby the megaripples seed PBR pattern. It may be possible for PBRs to develop through direct abrasion of bedrock; however, the mechanism(s) required to form wind-transverse PBRs as opposed to the more common wind-parallel features (yardangs) has yet to be identified.

Yardangs are enigmatic wind-parallel ridges sculpted by aeolian processes that are found extensively in arid environments on Earth and Mars. No general theory exists to explain the long-term evolution of yardangs, curtailing modeling of landscape evolution and dynamics of suspended sediment release. We present a hypothesis of yardang evolution using relative rates of sediment flux, interyardang corridor downcutting, yardang denudation, substrate erodibility, and substrate clast content. To develop and sustain yardangs, corridor downcutting must exceed yardang vertical denudation and deflation. However, erosion of substrate yields considerable quantities of sediment that shelters corridors, slowing downcutting. We model the evolution of yardangs through various combinations of rates and substrate compositions, demonstrating the life span, suspended sediment release, and resulting landscape evolution. We find that yardangs have a distinct and predictable evolution, with inevitable demise and unexpectedly dynamic and autogenic erosion rates driven by subtle differences in substrate clast composition.

The effects of large floods on river morphology are variable and poorly understood. In this study, we apply multi-temporal datasets collected with small unmanned aircraft systems (UASs) to analyze three-dimensional morphodynamic changes associated with an extreme flood event that occurred from 19 to 23 June 2013 on the Elbow River, Alberta. We documented reach-scale spatial patterns of erosion and deposition using high-resolution (4–5 cm/pixel) orthoimagery and digital elevation models (DEMs) produced from photogrammetry. Significant bank erosion and channel widening occurred, with an average elevation change of −0.24 m. The channel pattern was reorganized and overall elevation variation increased as the channel adjusted to full mobilization of most of the bed surface sediments. To test the extent to which geomorphic changes can be predicted from initial conditions, we compared shear stresses from a two-dimensional hydrodynamic model of peak discharge to critical shear stresses for bed surface sediment sizes. We found no relation between modeled normalized shear stresses and patterns of scour and fill, confirming the complex nature of sediment mobilization and flux in high-magnitude events. However, comparing modeled peak flows through the pre- and post-flood topography showed that the flood resulted in an adjustment that contributes to overall stability, with lower percentages of bed area below thresholds for full mobility in the post-flood geomorphic configuration. Overall, this work highlights the potential of UAS-based remote sensing for measuring three-dimensional changes in fluvial settings and provides a detailed analysis of potential relationships between flood forces and geomorphic change. Copyright © 2015 John Wiley & Sons, Ltd.

In this paper we present a new software tool that automatically fetches, downloads and consolidates climate data from a Web database where the data are contained on multiple Web pages. The tool is called the Canadian Climate Data Scraping Tool (CCDST) and was developed to enhance access and simplify analysis of climate data from Canada's National Climate Data and Information Archive (NCDIA). The CCDST deconstructs a URL for a particular climate station in the NCDIA and then iteratively modifies the date parameters to download large volumes of data, remove individual file headers, and merge data files into one output file. This automated sequence enhances access to climate data by substantially reducing the time needed to manually download data from multiple Web pages. To this end, we present a case study of the temporal dynamics of blowing snow events that resulted in ~3.1 weeks time savings. Without the CCDST, the time involved in manually downloading climate data limits access and restrains researchers and students from exploring climate trends. The tool is coded as a Microsoft Excel macro and is available to researchers and students for free. The main concept and structure of the tool can be modified for other Web databases hosting geophysical data.

We present an analysis of 10 dune fields to test a model-derived hypothesis of dune field activity. The hypothesis suggests that a quantifiable threshold exists for stabilization in unidirectional wind regimes: active dunes have slipface deposition rates that exceed the vegetation deposition tolerance, and stabilizing dunes have the opposite. We quantified aeolian sand flux, slipface geometry, and vegetation deposition tolerance to directly test the hypothesis at four dune fields (Bigstick, White Sands Stable, White Sands Active, and Cape Cod). We indirectly tested the hypothesis at six additional dune fields with limited vegetation data (Hanford, Ano Nuevo, Skagen Odde, Salton Sea, Oceano Stable, and Oceano Active, “inverse calculation sites”). We used digital topographic data and estimates of aeolian sand flux to approximate the slipface deposition rates prior to stabilization. Results revealed a distinct, quantifiable, and consistent pattern despite diverse environmental conditions: the modal peak of prestabilization slipface deposition rates was 80% of the vegetation deposition tolerance at stabilized or stabilizing dune fields. Results from inverse calculation sites indicate deposition rates at stabilized sites were near a hypothesized maximum vegetation deposition tolerance (1 m a−1), and active sites had slipface deposition rates much higher. Overall, these results confirm the hypothesis and provide evidence of a globally applicable, simple, and previously unidentified predictor for the dynamics of vegetation cover in dune fields under unidirectional wind regimes.

We describe an integrated system combining an unmanned aerial vehicle (UAV) and open path methane instrument for detecting leaks in natural gas infrastructure. Reducing methane emissions from the n...

Despite almost a century of study, aeolian sediment transport remains difficult to measure. Low temporal resolution sediment traps filter sub-second scale variability hypothesized to be important, and high resolution electronic sensors are poorly tested, inconsistent, and often produce incomparable particle count outputs. No sediment transport prediction model can be validated or applied without quality empirical transport measurements. Here, we test a popular electronic laser gate sensor (Wenglor YH03PCT8, ‘the Wenglor’) in a wind tunnel. We have 3 goals: (i) assess the reproducibility of Wenglor measurements, (ii) examine saturation potential, and (iii) relate trap-measured sediment flux to particle counts. To assess reproducibility we measured particle counts with two co-located Wenglors. Temporally-autocorrelated sections of the time series occurred where one Wenglor deviated; this is likely the result of lens contamination. To examine saturation potential, we measured saltator velocity to calculate particle concentration within the airstream. Particle concentrations suggest the mean number of particles within the laser sampling volume is consistently less than one. To relate trap-measured sediment flux to particle counts, we used particle size samples to calculate an average mass per counted particle. We relate count predicted mass fluxes to trap-measured mass fluxes with linear regression and obtain the relation: trap flux = 2.1 * Wenglor predicted flux (r2 = 0.99). The constant represents aspects of the Wenglor operation that cannot be directly evaluated. Together, these investigations suggest the Wenglor provides a consistent and low-cost method to measure aeolian saltation flux at a high resolution in non-dusty settings.