Multi-temporal image analysis of historical aerial photographs and recent satellite imagery reveals evolution of water body surface area and polygonal terrain morphology in Kobuk Valley National Park, Alaska

Bogdanov²,

et al. 2017

Water

Despite the importance of thermokarst (thaw) lakes of the subarctic zone in regulating greenhouse gas exchange with the atmosphere and the flux of metal pollutants and micro-nutrients to the ocean, the inventory of lake distribution and stock of solutes for the permafrost-affected zone are not available. We quantified the abundance of thermokarst lakes in the continuous, discontinuous, and sporadic permafrost zones of the western Siberian Lowland (WSL) using Landsat-8 scenes collected over the summers of 2013 and 2014. In a territory of 105 million ha, the total number of lakes >0.5 ha is 727,700, with a total surface area of 5.97 million ha, yielding an average lake coverage of 5.69% of the territory. Small lakes (0.5-1.0 ha) constitute about one third of the total number of lakes in the permafrost-bearing zone of WSL, yet their surface area does not exceed 2.9% of the total area of lakes in WSL. The latitudinal pattern of lake number and surface coverage follows the local topography and dominant landscape zones. The role of thermokarst lakes in dissolved organic carbon (DOC) and most trace element storage in the territory of WSL is non-negligible compared to that of rivers. The annual lake storage across the WSL of DOC, Cd, Pb, Cr, and Al constitutes 16%, 34%, 37%, 57%, and 73%, respectively, of their annual delivery by WSL rivers to the Arctic Ocean from the same territory. However, given that the concentrations of DOC and metals in the smallest lakes (<0.5 ha) are much higher than those in the medium and large lakes, the contribution of small lakes to the overall carbon and metal budget may be comparable to, or greater than, their contribution to the water storage. As such, observations at high spatial resolution (<0.5 ha) are needed to constrain the reservoirs and the mobility of carbon and metals in aquatic systems. To upscale the DOC and metal storage in lakes of the whole subarctic, the remote sensing should be coupled with hydrochemical measurements in aquatic systems of boreal plains.

Section: Introductionmentioning

confidence: 99%

Size Distribution, Surface Coverage, Water, Carbon, and Metal Storage of Thermokarst Lakes in the Permafrost Zone of the Western Siberia Lowland

Bogdanov²,

et al. 2017

Water

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

“…For photogrammetric approaches, a majority of studies concern less than 5 dates and 100 km 2 . By increasing size, these papers are: (Meyer et al, 1996, Nebiker et al, 2014, Walstra et al, 2004, Mondino and Chiabrandoa, 2008, Véga and St-Onge, 2008, Kadmon and Harari-Kremer, 1999, Fox and Cziferszky, 2008, Cardenal et al, 2006, Necsoiu et al, 2013, Aguilar et al, 2013, Ayoub et al, 2009. (Micheletti et al, 2015) (9 dates), (Nurminen et al, 2015) (10) and (Korpela, 2006) (28) are the only authors that have processed more than 5 epochs.…”

Section: Fine Georeferencing Of Archival Imagesmentioning

confidence: 99%

“…During this stage, the calibration of the camera of an aerial survey is usually questioned and reestimated. This self-calibration is done automatically using the tie-points (Nurminen et al, 2015, Cardenal et al, 2006, Necsoiu et al, 2013, Fox and Cziferszky, 2008, Walstra et al, 2004. Nevertheless, it must be kept in mind that results of self-calibration often remains an approximation because the poorly geometrically constrained configuration of the image sets.…”

Section: Interior Orientationmentioning

confidence: 99%

“…The most common method is to measure Ground Control Points (GCPs) and to determine their image coordinates in the relevant aerial photographs. In the literature, GCPs are measured manually using ancillary orthoimage and a Digital Terrain Model (Nurminen et al, 2015, Nocerino et al, 2012, Necsoiu et al, 2013, Véga and St-Onge, 2008, Ellis et al, 2006, Fox and Cziferszky, 2008, field GPS (Micheletti et al, 2015, Cardenal et al, 2006, Walstra et al, 2004, or with both techniques (Aguilar et al, 2013). The number of GCPs needed is important compared to the size of the study sites: around 45 GCPs for less than 10 archival aerial images in (Nurminen et al, 2015) or (Aguilar et al, 2013), or 169 GCPs for a 20 km 2 area in (Micheletti et al, 2015), 10 to 47 GCPs per image in (Ford, 2013).…”

Section: Absolute Image Orientationmentioning

confidence: 99%

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Toward Automatic Georeferencing of Archival Aerial Photogrammetric Surveys

Giordano¹,

Bris²,

Mallet³

2018

ABSTRACT:Images from archival aerial photogrammetric surveys are a unique and relatively unexplored means to chronicle 3D land-cover changes over the past 100 years. They provide a relatively dense temporal sampling of the territories with very high spatial resolution. Such time series image analysis is a mandatory baseline for a large variety of long-term environmental monitoring studies. The current bottleneck for accurate comparison between epochs is their fine georeferencing step. No fully automatic method has been proposed yet and existing studies are rather limited in terms of area and number of dates. State-of-the art shows that the major challenge is the identification of ground references: cartographic coordinates and their position in the archival images. This task is manually performed, and extremely time-consuming. This paper proposes to use a photogrammetric approach, and states that the 3D information that can be computed is the key to full automation. Its original idea lies in a 2-step approach: (i) the computation of a coarse absolute image orientation; (ii) the use of the coarse Digital Surface Model (DSM) information for automatic absolute image orientation. It only relies on a recent orthoimage+DSM, used as master reference for all epochs. The coarse orthoimage, compared with such a reference, allows the identification of dense ground references and the coarse DSM provides their position in the archival images. Results on two areas and 5 dates show that this method is compatible with long and dense archival aerial image series. Satisfactory planimetric and altimetric accuracies are reported, with variations depending on the ground sampling distance of the images and the location of the Ground Control Points.

“…In the adjacent Yukon Flats National Wildlife Refuge, historic aerial imagery indicates that lake drying and vegetation invasion have occurred in the Boreal Biome since about the 1980s [58]. Necsoiu et al [59] …”

Section: Change Typesmentioning

confidence: 99%

Landscape Change Detected over a Half Century in the Arctic National Wildlife Refuge Using High-Resolution Aerial Imagery

Jorgenson

Jorgenson²,

Boldenow

et al. 2018

Remote Sensing

Rapid warming has occurred over the past 50 years in Arctic Alaska, where temperature strongly affects ecological patterns and processes. To document landscape change over a half century in the Arctic National Wildlife Refuge, Alaska, we visually interpreted geomorphic and vegetation changes on time series of coregistered high-resolution imagery. We used aerial photographs for two time periods, 1947-1955 and 1978-1988, and Quick Bird and IKONOS satellite images for a third period, [2000][2001][2002][2003][2004][2005][2006][2007]. The stratified random sample had five sites in each of seven ecoregions, with a systematic grid of 100 points per site. At each point in each time period, we recorded vegetation type, microtopography, and surface water. Change types were then assigned based on differences detected between the images. Overall, 23% of the points underwent some type of change over thẽ 50-year study period. Weighted by area of each ecoregion, we estimated that 18% of the Refuge had changed. The most common changes were wildfire and postfire succession, shrub and tree increase in the absence of fire, river erosion and deposition, and ice-wedge degradation. Ice-wedge degradation occurred mainly in the Tundra Biome, shrub increase and river changes in the Mountain Biome, and fire and postfire succession in the Boreal Biome. Changes in the Tundra Biome tended to be related to landscape wetting, mainly from increased wet troughs caused by ice-wedge degradation. The Boreal Biome tended to have changes associated with landscape drying, including recent wildfire, lake area decrease, and land surface drying. The second time interval, after~1982, coincided with accelerated climate warming and had slightly greater rates of change.