scholarly journals Automated Recognition of Human-Built Infrastructure in the Arctic Permafrost Landscapes using Commercial Satellite Imagery

2021 ◽  
Author(s):  
Elias Manos ◽  
Amit Hasan ◽  
Mahendra Udawalpola ◽  
Anna Liljedahl ◽  
Chandi Witharana
2018 ◽  
Vol 12 (11) ◽  
pp. 3589-3604 ◽  
Author(s):  
Claire Bernard-Grand'Maison ◽  
Wayne Pollard

Abstract. Quantifying ground-ice volume on a regional scale is necessary to assess the vulnerability of permafrost landscapes to thaw-induced disturbance like terrain subsidence and to quantify potential carbon release. Ice wedges (IWs) are a ubiquitous ground-ice landform in the Arctic. Their high spatial variability makes generalizing their potential role in landscape change problematic. IWs form polygonal networks that are visible on satellite imagery from surface troughs. This study provides a first approximation of IW ice volume for the Fosheim Peninsula, Ellesmere Island, a continuous permafrost area characterized by polar desert conditions and extensive ground ice. We perform basic GIS analyses on high-resolution satellite imagery to delineate IW troughs and estimate the associated IW ice volume using a 3-D subsurface model. We demonstrate the potential of two semi-automated IW trough delineation methods, one newly developed and one marginally used in previous studies, to increase the time efficiency of this process compared to manual delineation. Our methods yield acceptable IW ice volume estimates, validating the value of GIS to estimate IW volume on much larger scales. We estimate that IWs are potentially present on 50 % of the Fosheim Peninsula (∼3000 km2), where 3.81 % of the top 5.9 m of permafrost could be IW ice.


Author(s):  
R. H. Fraser ◽  
I. Olthof ◽  
M. Maloley ◽  
R. Fernandes ◽  
C. Prevost ◽  
...  

Northern environments are changing in response to recent climate warming, resource development, and natural disturbances. The Arctic climate has warmed by 2&ndash;3°C since the 1950’s, causing a range of cryospheric changes including declines in sea ice extent, snow cover duration, and glacier mass, and warming permafrost. The terrestrial Arctic has also undergone significant temperature-driven changes in the form of increased thermokarst, larger tundra fires, and enhanced shrub growth. Monitoring these changes to inform land managers and decision makers is challenging due to the vast spatial extents involved and difficult access. <br><br> Environmental monitoring in Canada’s North is often based on local-scale measurements derived from aerial reconnaissance and photography, and ecological, hydrologic, and geologic sampling and surveying. Satellite remote sensing can provide a complementary tool for more spatially comprehensive monitoring but at coarser spatial resolutions. Satellite remote sensing has been used to map Arctic landscape changes related to vegetation productivity, lake expansion and drainage, glacier retreat, thermokarst, and wildfire activity. However, a current limitation with existing satellite-based techniques is the measurement gap between field measurements and high resolution satellite imagery. Bridging this gap is important for scaling up field measurements to landscape levels, and validating and calibrating satellite-based analyses. This gap can be filled to a certain extent using helicopter or fixed-wing aerial surveys, but at a cost that is often prohibitive. <br><br> Unmanned aerial vehicle (UAV) technology has only recently progressed to the point where it can provide an inexpensive and efficient means of capturing imagery at this middle scale of measurement with detail that is adequate to interpret Arctic vegetation (i.e. 1&ndash;5 cm) and coverage that can be directly related to satellite imagery (1&ndash;10 km<sup>2</sup>). Unlike satellite measurements, UAVs permit frequent surveys (e.g. for monitoring vegetation phenology, fires, and hydrology), are not constrained by repeat cycle or cloud cover, can be rapidly deployed following a significant event, and are better suited than manned aircraft for mapping small areas. UAVs are becoming more common for agriculture, law enforcement, and marketing, but their use in the Arctic is still rare and represents untapped technology for northern mapping, monitoring, and environmental research. <br><br> We are conducting surveys over a range of sensitive or changing northern landscapes using a variety of UAV multicopter platforms and small sensors. Survey targets include retrogressive thaw slumps, tundra shrub vegetation, recently burned vegetation, road infrastructure, and snow. Working with scientific partners involved in northern monitoring programs (NWT CIMP, CHARS, NASA ABOVE, NRCan-GSC) we are investigating the advantages, challenges, and best practices for acquiring high resolution imagery from multicopters to create detailed orthomosaics and co-registered 3D terrain models. Colour and multispectral orthomosaics are being integrated with field measurements and satellite imagery to conduct spatial scaling of environmental parameters. Highly detailed digital terrain models derived using structure from motion (SfM) photogrammetry are being applied to measure thaw slump morphology and change, snow depth, tundra vegetation structure, and surface condition of road infrastructure. <br><br> These surveys and monitoring applications demonstrate that UAV-based photogrammetry is poised to make a rapid contribution to a wide range of northern monitoring and research applications.


2020 ◽  
Author(s):  
Daria Tatsii ◽  
Natalia Fedoseeva

&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; The safe operation of aviation and shipping, particularly in areas of insufficient coverage of automatic meteorological stations in the Arctic requires accurate interpretation of satellite images. Operational detection of fog and low stratus clouds and recognizing of them on the background of snow and ice cover and cloudiness of the upper layer is very important challenge.&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; &amp;#160;The verified images obtained by Aqua and Terra satellites with a scanning radiometer MODIS, which operates in 36 spectral bands, with wavelengths from 0.4 &amp;#181;m to 14.4 &amp;#181;m, were collected.&amp;#160; With the Beam VISAT 5.0 software, which was designed to work with satellite data in raster format, thematic digital techniques of satellite multispectral information, based on difference in the values of the integral brightness of the images, both in optical and far-infrared ranges of the spectrum, have been developed. &amp;#160;These techniques, models of additive color synthesis, improve the quality of interpretation of fogs and low stratus clouds in terms of the complex structure of cloudiness and underlying surface in polar regions. Developed RGB combinations, which are based on the selected MODIS bands are:&lt;/p&gt;&lt;ol&gt;&lt;li&gt;RGB (1.6 &amp;#181;m; 0.8 &amp;#181;m; 0.6 &amp;#181;m)&lt;/li&gt; &lt;li&gt;RGB (0.8 &amp;#181;m; 3.9-8.7 &amp;#181;m; 10.8 &amp;#181;m)&lt;/li&gt; &lt;li&gt;RGB (0.8 &amp;#181;m; 1.6 &amp;#181;m; 3.9-8.7 &amp;#181;m)&lt;/li&gt; &lt;li&gt;RGB ((0-12)-(0-11) &amp;#181;m, (0-11)-(0-3.8) &amp;#181;m, (0-11) &amp;#181;m)&lt;/li&gt; &lt;/ol&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; Analysis of the obtained images has shown that the developed models of color synthesis help to distinguish the fog/low stratus clouds under different conditions of cloudiness and underlying surface accurately.&lt;/p&gt;&lt;p&gt;Key words: remote sensing, satellite imagery, additive color synthesis, fog, low stratus clouds, polar regions&lt;/p&gt;


ARTMargins ◽  
2017 ◽  
Vol 6 (2) ◽  
pp. 6-26
Author(s):  
Noelle Belanger ◽  
Anna Westerstahl Stenport

American painter Frederic Edwin Church's monumental oil painting Aurora Borealis (1865) presents a stark contrast to the dominant Western tradition of representing the Arctic as monochrome and static. This article discusses how the impressive palette of Aurora Borealis and its black semi-circle in the center allow for a revisionist understanding of Church's contributions to a rich history of Arctic representation, including in an age of climate change and rapidly melting ice. The article connects Aurora Borealis to emerging lens technologies—especially photography and astronomy, and later the cinema and composite satellite imagery, to argue for circumpolar north as globally connected—then, and now. The article furthermore draws connections to the nineteenth-century trade in pigments, the interconnected routes of slavery, and cultural modes of urban modernity.


ARCTIC ◽  
2018 ◽  
Vol 71 (3) ◽  
Author(s):  
Rosemary A. Dwight ◽  
David M. Cairns

The Arctic tundra is undergoing many environmental changes in addition to increasing temperatures: these changes include permafrost degradation and increased shrubification. Disturbances related to infrastructure can also lead to similar environmental changes. The Trans-Alaska Pipeline System (TAPS) is an example of infrastructure that has made a major imprint on the Alaskan landscape. This paper assesses changes in shrub presence along the northernmost 255 km of the TAPS. We used historical satellite imagery from before construction of the TAPS in 1974 and contemporary satellite imagery from 2010 to 2016 to examine changes in shrub presence over time. We found a 51.8% increase in shrub presence adjacent to the pipeline compared to 2.6% in control areas. Additionally, shrub presence has increased significantly more in areas where the pipeline is buried, indicating that the disturbances linked to pipeline burial have likely created favorable conditions for shrub colonization. These results are important for predicting potential responses of tundra vegetation to disturbance, which will be crucial to forecasting the future of Arctic tundra vegetation.


2013 ◽  
Vol 7 (2) ◽  
pp. 699-705 ◽  
Author(s):  
W. N. Meier ◽  
D. Gallaher ◽  
G. G. Campbell

Abstract. Visible satellite imagery from the 1964 Nimbus I satellite has been recovered, digitized, and processed to estimate Arctic and Antarctic sea ice extent for September 1964. September is the month when the Arctic sea ice reaches its minimum annual extent and the Antarctic sea ice reaches its maximum. Images from a three-week period were manually analyzed to estimate the location of the ice edge and then composited to obtain a hemispheric estimate. Uncertainties were based on limitations in the image analysis and the variation of the ice cover over the three-week period. The 1964 Antarctic extent is higher than estimates from the 1979–present passive microwave record, but is in accord with previous indications of higher extents during the 1960s. The Arctic 1964 extent is near the 1979–2000 average from the passive microwave record, suggesting relatively stable summer extents during the 1960s and 1970s preceding the downward trend since 1979 and particularly the large decrease in the last decade. These early satellite data put the recently observed record into a longer-term context.


2013 ◽  
Vol 7 (1) ◽  
pp. 35-53 ◽  
Author(s):  
W. N. Meier ◽  
D. Gallaher ◽  
G. G. Campbell

Abstract. Satellite imagery from the 1964 Nimbus I satellite has been recovered, digitized, and processed to estimate Arctic and Antarctic sea ice extent for September 1964. September is the month when the Arctic reaches its minimum annual extent and the Antarctic reaches its maximum. Images were manually analyzed over a three-week period to estimate the location of the ice edge and then composited to obtain a hemispheric average. Uncertainties were based on limitations in the image analysis and the variation of the ice cover over the three week period. The 1964 Antarctic extent is higher than estimates from the 1979–present passive microwave record, but is in accord with previous indications of higher extents during the 1960s. The Arctic 1964 extent was near the 1979–2000 average from the passive microwave record, suggesting relatively stable summer extents until the recent large decrease. This early satellite record puts the recently observed into a longer-term context.


2021 ◽  
Author(s):  
Davy Uwizera ◽  
Charles Ruranga ◽  
Patrick McSharry

<div>In this research we use data from a number of different sources of satellite imagery. Below we describe and visualize various metrics of the datasets being considered. Satellite imagery is retrieved from Google earth which is supported by Data SIO (Scripps Institution of Oceanography), NOAA (National Oceanic and Atmospheric Administration), US. Navy (United States Navy), NGA (National Geospatial-Intelligence Agency), GEBCO (General Bathymetric Chart of the Oceans), Image Landsat, and Image IBCAO (International Bathymetric Chart of the Arctic Ocean). Using random sampling of spatial area in Kigali per target area, 342,843 thousands images were retrieved under the five categories: residential high income (78941), residential low income(162501), residential middle income(101401), commercial building, (67400) and industrial zone,(24400). For the industrial zone, we also included some images from Nairobi, Kenya industrial spatial area. The average number of samples for a category is 86929. The size of the sample per category is proportional to the size of the spatial target area considered per category. Kigali is located at latitude:-1.985070 and longitude:-1.985070, coordinates. Nairobi is located at latitude:-1.286389 and longitude:36.817223, coordinates.</div>


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