Evaluation of the use of very high resolution aerial imagery for accurate ice-wedge polygon mapping (Adventdalen, Svalbard)

Lousada, M.; Pina, Pedro; Vieira, Gonçalo; Bandeira, L.; Mora, Carla

doi:10.1016/j.scitotenv.2017.09.153

Cited by 29 publications

(23 citation statements)

References 34 publications

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“…These climatically linked processes have in central Svalbard resulted in a "smoothing" of the landscape, with few sharp topographic features and a rounded topography. At the start of the 20th Century, the records have shown a strong warming trend (starting with the 1920s), where within a period of 5 years the mean annual air temperature changed from −9 • C to −4 • C. This warming is generally interpreted as representing the end of the Little Ice Age (LIA) [12].…”

Section: Study Areamentioning

confidence: 99%

“…Arctic areas have become important hot spots for studying the effects of a changing climate [8], which is felt earlier there than elsewhere on Earth [9]. The present ongoing research focuses on modelling the velocity of glaciers and ice caps [10], land cover and ice-wedge polygon mapping [11,12], the surface morphology of fans [13], retrogressive thaw slumps triggering [14,15], coastal erosion [16], human impact [17], etc. One of the most exposed Arctic areas is Svalbard, which is experiencing amplified climate change when compared to the global average [18,19].…”

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confidence: 99%

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Coastal Erosion Affecting Cultural Heritage in Svalbard. A Case Study in Hiorthhamn (Adventfjorden)—An Abandoned Mining Settlement

et al. 2020

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Hiorthhamn is an abandoned Norwegian coal mining settlement with a loading dock and a lot of industrial infrastructure left in the coastal zone. In this study, changes in the position of 1.3 km of the Hiorthhamn shoreline, which affect cultural heritage, is described for a time-period spanning 92 years . The shoreline positions were established based on a map (1927), orthophotos (2009) and a topographic survey with differential Global Positioning System (GPS) (summer 2019). Detailed geomorphological and surface sediment mapping was conducted to form a framework for understanding shoreline-landscape interaction. The shoreline was divided into three sectors to calculate the erosion/stability/accretion rates by using the DSAS (Digital Shoreline Analysis System) extension of ArcGIS. The DSAS analysis showed very high erosion in Sector 1, while Sectors 2 and 3 showed moderate accretion and moderate erosion, respectively. Sector 1 is geologically composed of easily erodible sorted beach sediments and protected remains from the mining industry such as wrecks of heavy machines, loading carts, wagons and rusty tracks that are directly exposed to coastal erosion. The all-sector average shoreline erosion rate (EPR parameter) for the 92 years period was −0.21 m/year. The high shoreline erosion rates in Sector 1, together with the high potential damage to cultural heritage, supports the urgent need of continued coastal monitoring and sustainable management of cultural heritage in Hiorthhamn.Sustainability 2020, 12, 2306 2 of 21 losses in the future. Arctic coastal areas can experience erosion rates similar to, or higher than, those in temperate regions due to the added influence of thawing permafrost and extreme temperatures.Coastal areas located at high latitudes are even more affected by the changes in the environment (e.g., air temperatures, major river discharges and open water season length have increased, and storm tracks and intensities are changing) [6]. The Arctic coastal zone is defined as the region both seaward and landward of the coastlines of the Arctic shelf areas, including all archipelagos and islands [7]. Arctic coastal areas can experience erosion rates similar to or higher than those in temperate regions due to the added influence of thawing permafrost and extreme temperatures, even though the erosional processes are usually still limited to a few months per year [6]. Arctic areas have become important hot spots for studying the effects of a changing climate [8], which is felt earlier there than elsewhere on Earth [9]. The present ongoing research focuses on modelling the velocity of glaciers and ice caps [10], land cover and ice-wedge polygon mapping [11,12], the surface morphology of fans [13], retrogressive thaw slumps triggering [14,15], coastal erosion [16], human impact [17], etc. One of the most exposed Arctic areas is Svalbard, which is experiencing amplified climate change when compared to the global average [18,19]. Svalbard's coastal area is under high pressure from natural [20] and in some area...

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Section: Study Areamentioning

confidence: 99%

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confidence: 99%

Coastal Erosion Affecting Cultural Heritage in Svalbard. A Case Study in Hiorthhamn (Adventfjorden)—An Abandoned Mining Settlement

et al. 2020

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“…The polygons remain wet throughout the summer, although the lowermost end of the polygonal field has been subject to recent gully erosion (Figure b) (cf). The polygons occur mainly as quadrangles, pentagons and hexagons with an average diameter of about 20 m and three‐way junctions (Figure ). The surface morphology shifts into small polygons (< 3 m in diameter), earth hummocks and mudboils toward the loess‐free area higher on the fan …”

Section: The Studied Ice‐wedge Sitementioning

confidence: 99%

Ice‐wedge polygon dynamics in Svalbard: Lessons from a decade of automated multi‐sensor monitoring

Matsuoka

Christiansen²,

Watanabe

2018

Permafrost & Periglacial

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Twelve years of continuous monitoring of diverse ground properties reveals the dynamics of three ice wedges and adjacent ground in a low-centered polygon area in Svalbard. The monitoring documented ground displacements, the timing of crack generation, ground thermal and moisture conditions from the surface to the top permafrost, and snow conditions. The focus is on seasonal ground deformation in and around ice-wedge troughs, interannual variability of ice-wedge activity and thermal thresholds for ice-wedge cracking. Seasonal ice-wedge activity is mainly associated with frost heave and thaw settlement, as well as thermal expansion and contraction.In mid-to late winter, temporary expansion and cracking of troughs by thermal contraction occurs during rapid cooling periods. Following intensive ground microcracking events, troughs show rapid expansion and in some cases major cracking in the frozen active layer. A common threshold for cracking is identified by a combination of ground surface cooling below −20°C and a thermal gradient steeper than −10°C m −1 in the upper meter of ground, indicating that cracking requires both a brittle frozen layer and rapid ground cooling. Our results highlight that in marginal thermal conditions for ice-wedge activity, the primary control on ice-wedge cracking is rapid winter cooling enhanced by minimum snow cover. (eg, 5-8 ). These rules, however, give only rough estimates, because they ignore ground surface conditions (snow and vegetation), and short cold events rather than seasonal conditions may control thermal contraction cracking. 9,10 To date, the widely accepted rule is that ice-wedge pseudomorphs indicate the past presence of (probably continuous) permafrost. 1 Improving the precision of paleoclimatic reconstruction using wedge structures requires more precise ----------------------------------------------------This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…The probability of such transformation is higher in areas with warmer permafrost, like the Seward Peninsula in Alaska [58]. Understanding of spatiotemporal dynamics behind the evolution of ice-wedge polygonal tundra demands for objective and detailed maps consolidating the ice wedge extent and successional stage [56,59,60].Vast geographical extent, remoteness, logistical challenges, and high cost retard field-based mapping of IWPs on large scales. Remote sensing (RS) provides transformational opportunities to observe, monitor, and measure the Arctic polygonal landscape at multiple spatial scales and varying Remote Sens.…”

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confidence: 99%

“…While the imagery supports the general delineation of polygon boundaries, LiDAR-based digital terrain models (DTM) are able further thematically discern the polygon types as HCP, LCP, or flat centered IWPs [67]. In a recent study that coupled ground-based surveys and imagery-based interpretations, Lousada et al [60] reported that ice-wedge polygonal networks could be accurately delineated and characterized exclusively from very high spatial resolution (VHSR) RS imagery.Over the years, a considerable number of studies have been conducted to map and characterize IWPs from RS data coming from different sensor platforms, such as unmanned aerial system (UAS), manned-aerial, and satellite. (1) UAS sensor platform: Muster et al [66] deployed a UAS augmented with a helium-filled dirigible to image IWPs at Samoylov Island in the Lena River Delta in the Russian Arctic at 0.18 m resolution in the visible (VIS) and near-infrared (NIR) ranges.…”

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Deep Convolutional Neural Networks for Automated Characterization of Arctic Ice-Wedge Polygons in Very High Spatial Resolution Aerial Imagery

et al. 2018

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The microtopography associated with ice-wedge polygons governs many aspects of Arctic ecosystem, permafrost, and hydrologic dynamics from local to regional scales owing to the linkages between microtopography and the flow and storage of water, vegetation succession, and permafrost dynamics. Wide-spread ice-wedge degradation is transforming low-centered polygons into high-centered polygons at an alarming rate. Accurate data on spatial distribution of ice-wedge polygons at a pan-Arctic scale are not yet available, despite the availability of sub-meter-scale remote sensing imagery. This is because the necessary spatial detail quickly produces data volumes that hamper both manual and semi-automated mapping approaches across large geographical extents. Accordingly, transforming big imagery into ‘science-ready’ insightful analytics demands novel image-to-assessment pipelines that are fueled by advanced machine learning techniques and high-performance computational resources. In this exploratory study, we tasked a deep-learning driven object instance segmentation method (i.e., the Mask R-CNN) with delineating and classifying ice-wedge polygons in very high spatial resolution aerial orthoimagery. We conducted a systematic experiment to gauge the performances and interoperability of the Mask R-CNN across spatial resolutions (0.15 m to 1 m) and image scene contents (a total of 134 km2) near Nuiqsut, Northern Alaska. The trained Mask R-CNN reported mean average precisions of 0.70 and 0.60 at thresholds of 0.50 and 0.75, respectively. Manual validations showed that approximately 95% of individual ice-wedge polygons were correctly delineated and classified, with an overall classification accuracy of 79%. Our findings show that the Mask R-CNN is a robust method to automatically identify ice-wedge polygons from fine-resolution optical imagery. Overall, this automated imagery-enabled intense mapping approach can provide a foundational framework that may propel future pan-Arctic studies of permafrost thaw, tundra landscape evolution, and the role of high latitudes in the global climate system.

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Evaluation of the use of very high resolution aerial imagery for accurate ice-wedge polygon mapping (Adventdalen, Svalbard)

Cited by 29 publications

References 34 publications

Coastal Erosion Affecting Cultural Heritage in Svalbard. A Case Study in Hiorthhamn (Adventfjorden)—An Abandoned Mining Settlement

Coastal Erosion Affecting Cultural Heritage in Svalbard. A Case Study in Hiorthhamn (Adventfjorden)—An Abandoned Mining Settlement

Ice‐wedge polygon dynamics in Svalbard: Lessons from a decade of automated multi‐sensor monitoring

Deep Convolutional Neural Networks for Automated Characterization of Arctic Ice-Wedge Polygons in Very High Spatial Resolution Aerial Imagery

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