scholarly journals MOSAICKING VERY-HIGH-RESOLUTION HELICOPTER-BORNE IMAGES ACQUIRED OVER DRIFTING ARCTIC SEA ICE USING COTS SENSORS

2018 ◽  
Vol XLII-1 ◽  
pp. 211-215
Author(s):  
C. U. Hyun ◽  
H. C. Kim
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Image Acquisition ◽  
Satellite Image ◽  
Weather Conditions ◽  
Arctic Sea Ice ◽  
Lower Altitude ◽  
In Situ Investigation ◽  
Commercial Off The Shelf ◽  
Very High

<p><strong>Abstract.</strong> In order to observe and record conditions of the sea ice efficiently and specifically during in-situ investigation with the support of icebreaker research vessel (IBRV), the very-high-resolution (VHR) imaging systems have been used in recent past. The VHR images are generally acquired lower altitude than cloud height, therefore, the images can be acquired even in unfavourable weather conditions for optical satellite image acquisition, and can be applied to comparison with various kinds of remote sensing datasets. However, producing mosaicked image using the VHR images have suffered from drift of sea ice. The sea ice drift interrupts simultaneous geotagging in overall study area as geographic locations of sea ice moves continuously; therefore, the mosaicked image generated from improperly geotagged individual image depicts a scene of ambiguous time. In this study, we present a case study of VHR sea ice image acquisition using a helicopter equipped with commercial off-the-shelf (COTS) geotagging and imaging sensors with a support of IBRV Araon in East Siberian Sea, Arctic Ocean. We also propose an image mosaicking strategy using the improperly geotagged VHR images acquired over drifting sea ice to decrease temporal and spatial ambiguity.</p>

scholarly journals Mosaicking Opportunistically Acquired Very High-Resolution Helicopter-Borne Images over Drifting Sea Ice Using COTS Sensors

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1251
Author(s):  
Chang-Uk Hyun ◽  
Joo-Hong Kim ◽  
Hyangsun Han ◽  
Hyun-cheol Kim
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Sea Ice ◽  
Low Cost ◽  
Three Dimensional ◽  
Ground Truth ◽  
Synthetic Aperture Radar Image ◽  
Arctic Sea Ice ◽  
Sea Ice Concentration ◽  
Very High

Observing sea ice by very high-resolution (VHR) images not only improves the quality of lower-resolution remote sensing products (e.g., sea ice concentration, distribution of melt ponds and pressure ridges, sea ice surface roughness, etc.) by providing details on the ground truth of sea ice, but also assists sea ice fieldwork. In this study, two fieldwork-based methods are proposed, one for the practical acquisition of VHR images over drifting Arctic sea ice using low-cost commercial off-the-shelf (COTS) sensors equipped on a helicopter, and the other for quantifying the compensating effect from continuously drifting sea ice that reduces geolocation uncertainty in the image mosaicking procedure. The drifting trajectory of the target ice was yielded from that recorded by an icebreaker that was tightly anchored to the floe and was then used to reversely compensate the locations of acquired VHR images. After applying the compensation, three-dimensional geolocation errors of the VHR images were decreased by 79.3% and 24.2% for two pre-defined image groups, respectively. The enhanced accuracy of the imaging locations was affected by imaging duration causing variable drifting distances of individual images. Further applicability of the mosaicked VHR image was discussed by comparing it with a TerraSAR-X synthetic aperture radar image containing the target ice, suggesting that the proposed methods can be used for precise comparison with satellite remote sensing products.

scholarly journals Towards Sub-Pixel Automatic Geometric Corrections of Very-High Resolution Panchromatic Satellite Data of Urban Areas

2019 ◽  
Vol 11 (9) ◽  
pp. 1097 ◽  
Author(s):  
Aleš Marsetič ◽  
Peter Pehani
Keyword(s):  
Feature Extraction ◽  
High Resolution ◽  
Urban Areas ◽  
Satellite Images ◽  
Reference Data ◽  
Geometric Model ◽  
Control Point ◽  
Satellite Image ◽  
Extraction Algorithm ◽  
Very High

This paper presents an automatic procedure for the geometric corrections of very-high resolution (VHR) optical panchromatic satellite images. The procedure is composed of three steps: an automatic ground control point (GCP) extraction algorithm that matches the linear features that were extracted from the satellite image and reference data; a geometric model that applies a rational function model; and, the orthorectification procedure. Accurate geometric corrections can only be achieved if GCPs are employed to precisely correct the geometric biases of images. Due to the high resolution and the varied acquisition geometry of images, we propose a fast, segmentation based method for feature extraction. The research focuses on densely populated urban areas, which are very challenging in terms of feature extraction and matching. The proposed algorithm is capable of achieving results with a root mean square error of approximately one pixel or better, on a test set of 14 panchromatic Pléiades images. The procedure is robust and it performs well in urban areas, even for images with high off-nadir angles.

scholarly journals Characterizing Arctic sea ice topography using high-resolution IceBridge data

2016 ◽  
Vol 10 (3) ◽  
pp. 1161-1179 ◽  
Author(s):  
Alek A. Petty ◽  
Michel C. Tsamados ◽  
Nathan T. Kurtz ◽  
Sinead L. Farrell ◽  
Thomas Newman ◽  
...  
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
Surface Feature ◽  
Ice Thickness ◽  
First Year ◽  
Data Set ◽  
Surface Features ◽  
Developed Surface ◽  
Arctic Sea

Abstract. We present an analysis of Arctic sea ice topography using high-resolution, three-dimensional surface elevation data from the Airborne Topographic Mapper, flown as part of NASA's Operation IceBridge mission. Surface features in the sea ice cover are detected using a newly developed surface feature picking algorithm. We derive information regarding the height, volume and geometry of surface features from 2009 to 2014 within the Beaufort/Chukchi and Central Arctic regions. The results are delineated by ice type to estimate the topographic variability across first-year and multi-year ice regimes. The results demonstrate that Arctic sea ice topography exhibits significant spatial variability, mainly driven by the increased surface feature height and volume (per unit area) of the multi-year ice that dominates the Central Arctic region. The multi-year ice topography exhibits greater interannual variability compared to the first-year ice regimes, which dominates the total ice topography variability across both regions. The ice topography also shows a clear coastal dependency, with the feature height and volume increasing as a function of proximity to the nearest coastline, especially north of Greenland and the Canadian Archipelago. A strong correlation between ice topography and ice thickness (from the IceBridge sea ice product) is found, using a square-root relationship. The results allude to the importance of ice deformation variability in the total sea ice mass balance, and provide crucial information regarding the tail of the ice thickness distribution across the western Arctic. Future research priorities associated with this new data set are presented and discussed, especially in relation to calculations of atmospheric form drag.

scholarly journals Consistent ice and open water classification combining historical synthetic aperture radar satellite images from ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1A/B

2020 ◽  
Vol 61 (82) ◽  
pp. 40-50 ◽  
Author(s):  
A. Malin Johansson ◽  
Eirik Malnes ◽  
Sebastian Gerland ◽  
Anca Cristea ◽  
Anthony P. Doulgeris ◽  
...  
Keyword(s):  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Satellite Images ◽  
Satellite Image ◽  
Open Water ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Synthetic Aperture ◽  
Envisat Asar ◽  
Aperture Radar

AbstractSynthetic Aperture Radar (SAR) satellite images are used to monitor Arctic sea ice, with systematic data records dating back to 1991. We propose a semi-supervised classification method that separates open water from sea ice and can utilise ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1 SAR images. The classification combines automatic segmentation with a manual segment selection stage. The segmentation algorithm requires only the backscatter intensities and incidence angle values as input, therefore can be used to establish a consistent decadal sea ice record. In this study we investigate the sea ice conditions in two Svalbard fjords, Kongsfjorden and Rijpfjorden. Both fjords have a seasonal ice cover, though Rijpfjorden has a longer sea ice season. The satellite image dataset has weekly to daily records from 2002 until now, and less frequent records between 1991 and 2002. Time overlap between different sensors is investigated to ensure consistency in the reported sea ice cover. The classification results have been compared to high-resolution SAR data as well as in-situ measurements and sea ice maps from Ny-Ålesund. For both fjords the length of the sea ice season has shortened since 2002 and for Kongsfjorden the maximum sea ice coverage is significantly lower after 2006.

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