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![An example of the processing chain for the Scheteligfjellet camera: (a) a raw time-lapse photograph (10:31Z 03.06.2016); (b) the orthorectified version of this photo (the area of interest [AOI] is in the yellow polygon); (c) the same orthoimage cropped to the AOI; and (d) the final classified orthoimage with bare ground pixels in grey and snow-covered pixels in blue. Adapted from Aalstad et al. (2020).](profile/Kristoffer-Aalstad/publication/348416089/figure/fig4/AS:979168351223816@1610463335540/An-example-of-the-processing-chain-for-the-Scheteligfjellet-camera-a-a-raw-time-lapse.png)
An example of the processing chain for the Scheteligfjellet camera: (a) a raw time-lapse photograph (10:31Z 03.06.2016); (b) the orthorectified version of this photo (the area of interest [AOI] is in the yellow polygon); (c) the same orthoimage cropped to the AOI; and (d) the final classified orthoimage with bare ground pixels in grey and snow-covered pixels in blue. Adapted from Aalstad et al. (2020).
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Ground-based observations are critical requirements for many disciplines that are trying to monitor climate change in a remote environment such as the Svalbard archipelago. This overview of cameras operating in Svalbard has been complied by searching for specific applications that monitor the snow cover and by collecting information about images th...
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Context 1
... each of these images was individually and manually classified into binary snow-covered and snow-free pixels using an image-specific threshold on the blue band histogram. These highresolution orthorectified binary snow cover images can be spatially aggregated and applied to validate satellite retrievals of FSC ( Figure 5). ...
Citations
... The snow-cover extent (SCE) over the study area was estimated using the terrestrial photography approach based on ground-based cameras located at the Zeppelin Observatory (380 m a.s.l.) [52] and at the Amundsen-Nobile Climate Change Tower at 15 m above the ground [53] (Figure 3). The Zeppelin system was an Axis Q6128-E device equipped with an 8-megapixel sensor, shooting four different views of the coastal area once per day, at about 12 AM local time. ...
The occurrence of extreme warm events in the Arctic has been increasing in recent years in terms of their frequency and intensity. The assessment of the impact of these episodes on the snow season requires further observation capabilities, where spatial and temporal resolutions are key constraints. This study targeted the snow season of 2022 when a winter rain-on-snow event occurred at Ny-Ålesund in mid-March. The selected methodology was based on a multi-scale and multi-platform approach, combining ground-based observations with satellite remote sensing. The ground-based observation portfolio included meteorological measurements, nivological information, and the optical description of the surface in terms of spectral reflectance and snow-cover extent. The satellite data were obtained by the Sentinel-2 platforms, which provided ten multi-spectral acquisitions from March to July. The proposed strategy supported the impact assessment of heat waves in a periglacial environment, describing the relation and the timing between rain-on-snow events and the surface water drainage system. The integration between a wide range of spectral, time, and spatial resolutions enhanced the capacity to monitor the evolution of the surface water drainage system, detecting two water discharge pulsations, different in terms of duration and effects. This preliminary study aims to improve the description of the snow dynamics during those extreme events and to assess the impact of the produced break during the snow accumulation period.
... The dynamics of seasonal snow is a key element of changing ecosystems in Arctic regions, and the ability to monitor it requires filling the gap that exists between in situ and satellite observations (Salzano et al. 2021b). The outcomes of PASSES (Salzano et al. 2021a) gave an overview of terrestrial photography applications on the snow cover, but future actions focused on enhancing and maintaining snow observations must include data integration and assimilation while considering different platforms and spatio-temporal resolutions. ...
... One key recommendation of our previous SESS report (Salzano et al., 2021a) was to establish a shared protocol for terrestrial applications. Such applications support the definition of different metrics about the snow cover: the Snow-Covered Area (SCA) and the Fractional Snow-Covered Area (FSCA), also known as the Fractional Snow Cover (FSC) or Snow Cover Fraction (SCF). ...
... As such, we performed an initial validation of LIS in the high-Arctic and compared it to other retrieval algorithms. For the validation, we used the Zeppelin dataset described in Salzano et al. (2021a), where images were ortho-rectified and classified using SS to yield FSCA at 10 m resolution. To avoid artefacts, we cropped the area of interest to exclude the village and airport of Ny-Ålesund. ...
The SESS report is established as an authoritative source of information about the state of the environment in and around Svalbard and is an important tool to convey knowledge to stakeholders and the public. The report addresses the scientific community, as well as stakeholders and the public. This format ensures that there is synergy between the scientific investigations and the knowledge needed by society to sustainably develop and safeguard the Arctic environment. The SESS report is the main driving force for the science-based development of the observing system and contributing to the report is an opportunity for research groups to actively influence the prioritisation within SIOS.
The report is available at https://sios-svalbard.org/SESS_Issue4
... The dynamics of seasonal snow is a key element of changing ecosystems in Arctic regions, and the ability to monitor it requires filling the gap that exists between in situ and satellite observations (Salzano et al. 2021b). The outcomes of PASSES (Salzano et al. 2021a) gave an overview of terrestrial photography applications on the snow cover, but future actions focused on enhancing and maintaining snow observations must include data integration and assimilation while considering different platforms and spatio-temporal resolutions. The wide availability of time-lapse cameras highlighted their significant potential as a bridging point, enabling comparison of detailed descriptions of the snow cover with large-scale assessments of the snow variability obtained by satellite platforms (Aalstad et al. 2020;Gascoin et al. 2020). ...
... One key recommendation of our previous SESS report (Salzano et al., 2021a) was to establish a shared protocol for terrestrial applications. Such applications support the definition of different metrics about the snow cover: the Snow-Covered Area (SCA) and the Fractional Snow-Covered Area (FSCA), also known as the Fractional Snow Cover (FSC) or Snow Cover Fraction (SCF). ...
... As such, we performed an initial validation of LIS in the high-Arctic and compared it to other retrieval algorithms. For the validation, we used the Zeppelin dataset described in Salzano et al. (2021a), where images were ortho-rectified and classified using SS to yield FSCA at 10 m resolution. To avoid artefacts, we cropped the area of interest to exclude the village and airport of Ny-Ålesund. ...
Three actions are required to improve terrestrial photography applications in Svalbard, according to the SESS report recommendations. The first one is focused on maintaining the dataset on terrestrial photography applications in Svalbard, widening the range of involved disciplines. The second one is aimed at defining a harmonised protocol based on established experience and describing guidelines for developing novel applications with a network perspective. Finally, exploring integration with remotely sensed data, it is possible to highlight potential ways of solving multi-scale gaps by combining ground based and remotely sensed data. This novel knowledge highlights even more the need for a strategic network of terrestrial cameras located in key locations where different disciplines could benefit from the description of snow cover evolution during the melting seasons.
... In addition, radiometric measurements can be integrated with visual information from webcam images, which are cost-effective powerful tools for monitoring large areas, and ground-based observations can contribute to fill the gap between in situ measurements and satellite products in the framework of global climate change studies. A new ground-based apparatus has been recently developed to monitor the variations of snowcovered surfaces during the melting period through the continuous collection of albedo data (Salzano et al. 2019(Salzano et al. , 2021. ...
The monitoring of surface albedo using radiometric measurements is a simple but effective way to study variations in snow cover and melt timing in the high northern latitudes, where there is a clear indication of warming in response to the changing global climate. In this paper, we investigate these phenomena in the Northwest region of Svalbard using a 40-year record, combining previous data from 1981 to 1997, radiation measurements from the Baseline Surface Radiation Network (BSRN) station since 1993, and the Amundsen Nobile Climate Change Tower (CCT) since 2009. A methodology has been developed to estimate the start, duration, and end date of the spring snow melt. This has been applied to the integrated dataset for the period 1981 to 2019. Our results are in good agreement with qualitative information on snow persistence provided by webcam images archived since 2000. The date of snow melt has advanced at a rate of about 3 days per decade during the period of study, from Julian calendar date (doy) 180 in the early 1980s to 165–170 in the late 2010s. There is indication the trend has accelerated since 2010. The footprint of the radiation measurements is a crucial factor in the evaluation of surface albedo; the larger the area within the field of view of the instrument, the more representative is the measure. The assimilated 40-year dataset will provide a base for future monitoring of snow persistence at Ny-Ålesund as the climate continues to change in the region. Our work highlights the importance of technical improvements made in measurement systems and combining different techniques to monitor surface albedo. In particular, terrestrial photography, combined with broadband radiation measurements, will contribute to increased knowledge of underlying processes that determine the surface energy budget in the Arctic region. In addition, the combined ground-based measurements can be used to validate those derived from space-born platforms.
... For broader relevance in the future, the team created strong synergies with international partners aimed at creating a network and harmonising the different procedures related to terrestrial camera infrastructure operations. Furthermore, the creation of a network focused on "terrestrial Photography ApplicationS on Snow covEr in Svalbard" (PASSES) [37] could be a seed for the growth of a camera network useful to the research community for compensating, at least partially, the lack of field observations in future. ...
Svalbard Integrated Arctic Earth Observing System (SIOS) is an international partnership of research institutions studying the environment and climate in and around Svalbard. SIOS is developing an efficient observing system, where researchers share technology, experience, and data, work together to close knowledge gaps, and decrease the environmental footprint of science. SIOS maintains and facilitates various scientific activities such as the State of the Environmental Science in Svalbard (SESS) report, international access to research infrastructure in Svalbard, Earth observation and remote sensing services, training courses for the Arctic science community, and open access to data. This perspective paper highlights the activities of SIOS Knowledge Centre, the central hub of SIOS, and the SIOS Remote Sensing Working Group (RSWG) in response to the unprecedented situation imposed by the global pandemic coronavirus (SARS-CoV-2) disease 2019 (COVID-19). The pandemic has affected Svalbard research in several ways. When Norway declared a nationwide lockdown to decrease the rate of spread of the COVID-19 in the community, even more strict measures were taken to protect the Svalbard community from the potential spread of the disease. Due to the lockdown, travel restrictions, and quarantine regulations declared by many nations, most physical meetings, training courses, conferences, and workshops worldwide were cancelled by the first week of March 2020. The resumption of physical scientific meetings is still uncertain in the foreseeable future. Additionally, field campaigns to polar regions, including Svalbard, were and remain severely affected. In response to this changing situation, SIOS initiated several operational activities suitable to mitigate the new challenges resulting from the pandemic. This article provides an extensive overview of SIOS’s Earth observation (EO), remote sensing (RS) and other operational activities strengthened and developed in response to COVID-19 to support the Svalbard scientific community in times of cancelled/postponed field campaigns in Svalbard. These include (1) an initiative to patch up field data (in situ) with RS observations, (2) a logistics sharing notice board for effective coordinating field activities in the pandemic times, (3) a monthly webinar series and panel discussion on EO talks, (4) an online conference on EO and RS, (5) the SIOS’s special issue in the Remote Sensing (MDPI) journal, (6) the conversion of a terrestrial remote sensing training course into an online edition, and (7) the announcement of opportunity (AO) in airborne remote sensing for filling the data gaps using aerial imagery and hyperspectral data. As SIOS is a consortium of 24 research institutions from 9 nations, this paper also presents an extensive overview of the activities from a few research institutes in pandemic times and highlights our upcoming activities for the next year 2021. Finally, we provide a critical perspective on our overall response, possible broader impacts, relevance to other observing systems, and future directions. We hope that our practical services, experiences, and activities implemented in these difficult times will motivate other similar monitoring programs and observing systems when responding to future challenging situations. With a broad scientific audience in mind, we present our perspective paper on activities in Svalbard as a case study.
... These differences are not a limitation but represent an opportunity to develop a multi-scale analysis and obtain reliable input for climate and ecological models. The chapter 'PASSES' (Salzano et al. 2021), focuses on terrestrial photography applications, provides an overview of the cameras operating in Svalbard looking at specific applications on the snow cover and collecting information about the images discoverable and/or accessible on the web. These data sources can provide information about the state of the snow cover that is limited in terms of spatial extension (10 m 2 up to 10 km 2 ) but almost independent from the meteorological conditions and characterised by high time resolution. ...
Data on snow properties such as cover fraction, depth, water equivalents, and melt date are important per se, but also as input in various models, and to verify model results. Earth observation (EO) gathers information on these parameters. Different EO methods for snow have different strengths. Manual measurements and locally deployed sensors give precise data, but only at individual sites. Satellite-based methods give huge amounts of data covering vast areas, but at lower resolution, and only when the satellite passes over relevant sites.
Three SIOS projects attempt to bridge the spatial and temporal gaps between remote sensing data and point measurements of snow cover.
... In the case of comparing terrestrial snow and sea-ice cover, a parallel study using the MODIS snow cover dataset was carried out by Vickers et al. (2020), which is a pre-cursor to the current SESS project. Salzano R. et al. (2021): 'Terrestrial Photography Applications on Snow cover in Svalbard'. The methods used by Salzano should have synergies when validating satellite data. ...
... For example, this report also includes chapters dedicated to improving our knowledge on snow cover distribution and enhancing snow cover date collection, thus contributing to minimising errors in the water budget calculations. PASSES (Salzano et al. 2021) provides a picture of terrestrial photography applications, while SvalSCESIE (Killie et al. 2021) compares an existing satellite-based, long-term climate data record with the model output for snow water equivalent and in-situ measurements. Lastly, SATMODSNOW (Malnes et al. 2021) studies the relationships between satellite observations and hydrological snow models and quantifies the difference. ...
Moreno-Ibáñez M, Hagen JO, Hübner C, Lihavainen H, Zaborska A (eds) 2021: SESS report 2020, Svalbard Integrated Arctic Earth Observing System, Longyearbyen
The Arctic region is warming at over twice the mean rate of the Northern Hemisphere and nearly four times faster than the globe since 1979. The local rate of warming is even higher in the European archipelago of Svalbard. This warming is transforming the terrestrial snow cover, which modulates surface energy exchanges with the atmosphere, accounts for most of the runoff in Arctic catchments and is also a transient reservoir of atmospherically deposited compounds, including pollutants. Improved observations, understanding and modelling of changes in Arctic snow cover are needed to anticipate the effects these changes will have on the Arctic climate, atmosphere, terrestrial ecosystems and socioeconomic factors. Svalbard has been an international hub of polar research for many decades and benefits from a well-developed science infrastructure. Here, we present an agenda for the future of snow research in Svalbard, jointly developed by a multidisciplinary community of experts. We review recent trends in snow research, identify key knowledge gaps, prioritize future research efforts and recommend supportive actions to advance our knowledge of present and future snow conditions pertaining to glacier mass balance, permafrost, surface hydrology, terrestrial ecology, the cycling and fate of atmospheric contaminants, and remote sensing of snow cover. This perspective piece addresses issues relevant to the circumpolar North and could be used as a template for other national or international Arctic research plans.
Many characteristics of atmospheric air are measured in Svalbard, including levels of chemical pollution, dark dust connected to soot, and living organisms, but most of these studies happen in Ny-Ålesund. Air monitoring was initiated as early as the 1970s, and multiple atmospheric components have been added to the monitoring over time (especially since 2010; in the early 2000s a few parameters measured at Hornsund joined the regular programme). New types of contaminants are being discovered and measured in Svalbard. Methods for detecting simpler substances and particles have been established for a long time, while certain complex chemicals and small living organisms are more difficult to capture and study. Laboratory and field equipment upgrades help improve understanding of the Svalbard environment. In this chapter, we find that collecting information on many characteristics of the air at the same time helps solve long-standing scientific questions in Svalbard, such as the origins of pollution in the Arctic air and the future of the Arctic atmosphere in a changing world. This is especially important since the Arctic is changing fast, both due to global warming and to the shift in local people’s activity from mining to services, e.g. tourism.
