SIOS’s airborne remote sensing campaigns in Svalbard 

2021 ◽  
Author(s):  
Shridhar Jawak ◽  
Agnar Sivertsen ◽  
Veijo Pohjola ◽  
Małgorzata Błaszczyk ◽  
Jack Kohler ◽  
...  
Keyword(s):  
Remote Sensing ◽  
3D Models ◽  
Hyperspectral Data ◽  
Aerial Images ◽  
Airborne Remote Sensing ◽  
Aerial Photos ◽  
Travel Restrictions ◽  
Field Campaigns ◽  
Local Company ◽  
Hyperspectral Sensor

<p>Svalbard Integrated Arctic Earth Observing System (SIOS) is an international collaboration of 24 research institutions from 9 countries studying the environment and climate in and around Svalbard. The global pandemic of Coronavirus disease (Covid-19) has affected the Svalbard research in a number of ways due to nationwide lockdown in many countries, strict travel restrictions in Svalbard, and quarantine regulations. Many field campaigns to Svalbard were cancelled in 2020 and campaigns in 2021 are still uncertain. In response to this challenge, we conducted practical activities to support the Svalbard science community in filling gaps in scientific observations. One of our activities involved conducting airborne remote sensing campaigns in Svalbard to support scientific projects. In 2020, SIOS supported 10 scientific projects by conducting 25 hours of aircraft and unmanned aerial vehicle (UAV)-based data collection in Svalbard. This is one of the finest ways to fill the data gap in the current situation as it is practically possible to conduct field campaigns using airborne platforms in spite of travel restrictions. We are using the aerial camera and hyperspectral sensor installed onboard the Dornier DO228 aircraft operated by the local company Lufttransport to acquire aerial images and hyperspectral data from various locations in Svalbard. The hyperspectral sensor image the ground in 186 spectral bands covering the range 400-1000 nm. Hyperspectral data can be used to map and characterise earth, ice and ocean surface features, such as minerals, vegetation, glaciers and snow cover, colour and pollutants. Further, it can be used to make 3D models of the terrain as well as searching for the presence of animals (e.g. counting seals). In addition, aerial photos are particularly useful tool to follow the seasonal dynamic changes and extent in sea ice cover, tracking icebergs, ocean productivity (Chlorophyll a) and river runoff (turbidity). Data collected from the SIOS funded airborne missions will not only help to fill a few of the data gaps resulting from the lockdown but also will be used by glaciologists, biologists, hydrologists, and other Earth system scientists to understand the state of the environment of Svalbard during these times. In 2021, we are continuing this activity by conducting more airborne campaigns in Svalbard. In this presentation, we will specifically focus on the overview of projects supported by airborne remote sensing campaigns.</p>

scholarly journals Integrating airborne remote sensing and field campaigns for ecology and Earth system science

2020 ◽  
Vol 11 (11) ◽  
pp. 1492-1508
Author(s):  
K. Dana Chadwick ◽  
Philip G. Brodrick ◽  
Kathleen Grant ◽  
Tristan Goulden ◽  
Amanda Henderson ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Earth System ◽  
Airborne Remote Sensing ◽  
Earth System Science ◽  
System Science ◽  
Field Campaigns

scholarly journals AIRBORNE TECHNOLOGIES FOR DISASTER MANAGEMENT

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 387-393
Author(s):  
J. Schulz
Keyword(s):  
Remote Sensing ◽  
Water Masses ◽  
Aerial Images ◽  
Airborne Remote Sensing ◽  
Optimal Method ◽  
Individual Tree ◽  
Flood Peak ◽  
Sensing Technology ◽  
Aircraft System ◽  
The Individual

<p><strong>Abstract.</strong> Currently, satellite-based systems and UAVs are very popular in the investigation of natural disasters. Both systems have their justification and advantages &amp;ndash; but one should not forget the airborne remote sensing technology. The presentation shows with three examples very clearly how airborne remote sensing is still making great progress and in many cases represents the optimal method of data acquisition.</p> <p>The airborne detection of forest damages (especially currently the bark beetle in spruce stands) can determine the pest attack using CIR aerial images in combination with ALS and hyperspectral systems &amp;ndash; down to the individual tree. Large forest areas of 100 sqkm and more can be recorded from planes on one day (100 sqkm with 10cm GSD on one day).</p> <p>Flood events &amp;ndash; such as on the Elbe in 2013 &amp;ndash; were recorded by many satellites. However, many evaluations require highresolution data (GSD 10cm), e.g. to clarify insurance claims. Here the aircraft system, which was able to fly below the cloud cover and was constantly flying at the height level of the flood peak, proved to be unbeatable.</p> <p>The phenomenon of urban flash floods is one of the consequences of climate change. Cities are not in a position to cope with the water masses of extreme rain events and so are confronted with major damages. In Germany, a number of cities are already preparing to manage short-term but extreme water masses. The complicated hydrographic and hydraulic calculations and simulations require above all one thing &amp;ndash; a precise data basis. This involves, for example, the height of kerbstones and the recording of every gully and every obstacle. Such city-wide data can only be collected effectively by photogrammetric analysis of aerial photography (GSD 5 to 10cm).</p>

Frozen data? Polar research and fieldwork in a pandemic era

Polar Record ◽  
2021 ◽  
Vol 57 ◽  
Author(s):  
Sophie Duveau
Keyword(s):  
Remote Sensing ◽  
Data Acquisition ◽  
Decisive Role ◽  
Airborne Remote Sensing ◽  
Human Presence ◽  
Multiple Dimensions ◽  
Data Gaps ◽  
Field Campaigns

Abstract Drawing on an ethnographic survey in Svalbard before and during the coronavirus outbreak, this commentary reflects on the multiple dimensions of fieldwork highlighted by the pandemic. Firstly, the cancellation of many field campaigns has revealed the decisive role of personnel inhabiting scientific bases in the maintenance of scientific activities in Svalbard. Automatic and remote-controlled instruments are autonomous only in appearance as the crucial phases of data acquisition often call for human presence. Secondly, airborne remote sensing can be perceived as a response to fill data gaps. Although embedded in a long history, the use of remote sensed data has taken on a new meaning in the context of the pandemic. Finally, the fact that several researchers endeavour to go to the field whatever the travel conditions underlines a certain need of being in Svalbard as well as limitations of science performed remotely.

Application of remote sensing methods for assessment of anthropogenic transformation of rangelands

2000 ◽  
pp. 16-25
Author(s):  
E. I. Rachkovskaya ◽  
S. S. Temirbekov ◽  
R. E. Sadvokasov
Keyword(s):  
Remote Sensing ◽  
New Technology ◽  
Field Studies ◽  
Digital Data ◽  
Aerial Images ◽  
Expert Assessment ◽  
Automated Classification ◽  
Anthropogenic Transformation ◽  
Initial Processing ◽  
Remote Sensing Methods

Capabilities of the remote sensing methods for making maps of actual and potential vegetation, and assessment of the extent of anthropogenic transformation of rangelands are presented in the paper. Study area is a large intermountain depression, which is under intensive agricultural use. Color photographs have been made by Aircraft camera Wild Heerburg RC-30 and multispectral scanner Daedalus (AMS) digital aerial data (6 bands, 3.5m resolution) have been used for analysis of distribution and assessment of the state of vegetation. Digital data were processed using specialized program ENVI 3.0. Main stages of the development of cartographic models have been described: initial processing of the aerial images and their visualization, preliminary pre-field interpretation (classification) of the images on the basis of unsupervised automated classification, field studies (geobotanical records and GPS measurements at the sites chosen at previous stage). Post-field stage had the following sub-stages: final geometric correction of the digital images, elaboration of the classification system for the main mapping subdivisions, final supervised automated classification on the basis of expert assessment. By systematizing clusters of the obtained classified image the cartographic models of the study area have been made. Application of the new technology of remote sensing allowed making qualitative and quantitative assessment of modern state of rangelands.

scholarly journals Archaeological Surveying of Subarctic and Arctic Landscapes: Comparing the Performance of Airborne Laser Scanning and Remote Sensing Image Data

2021 ◽  
Vol 13 (4) ◽  
pp. 1917
Author(s):  
Alma Elizabeth Thuestad ◽  
Ole Risbøl ◽  
Jan Ingolf Kleppe ◽  
Stine Barlindhaug ◽  
Elin Rose Myrvoll
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Image Data ◽  
Remote Sensing Image ◽  
Airborne Laser Scanning ◽  
Aerial Images ◽  
Detection Rates ◽  
Airborne Laser ◽  
Pros And Cons

What can remote sensing contribute to archaeological surveying in subarctic and arctic landscapes? The pros and cons of remote sensing data vary as do areas of utilization and methodological approaches. We assessed the applicability of remote sensing for archaeological surveying of northern landscapes using airborne laser scanning (LiDAR) and satellite and aerial images to map archaeological features as a basis for (a) assessing the pros and cons of the different approaches and (b) assessing the potential detection rate of remote sensing. Interpretation of images and a LiDAR-based bare-earth digital terrain model (DTM) was based on visual analyses aided by processing and visualizing techniques. 368 features were identified in the aerial images, 437 in the satellite images and 1186 in the DTM. LiDAR yielded the better result, especially for hunting pits. Image data proved suitable for dwellings and settlement sites. Feature characteristics proved a key factor for detectability, both in LiDAR and image data. This study has shown that LiDAR and remote sensing image data are highly applicable for archaeological surveying in northern landscapes. It showed that a multi-sensor approach contributes to high detection rates. Our results have improved the inventory of archaeological sites in a non-destructive and minimally invasive manner.

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