SwissEnvEO: A FAIR National Environmental Data Repository for Earth Observation Open Science

Giuliani, Gaston; Cazeaux, Hugues; Bürgi, Pierre-Yves; Poussin, Charlotte; Richard, Jean-Philippe; Chatenoux, Bruno

doi:10.5334/dsj-2021-022

Cited by 11 publications

(6 citation statements)

References 62 publications

(43 reference statements)

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“…In the Open Science paradigm this is indicated as Reproducible Research, and it can be guaranteed only if the same source code, dataset, and configuration used in the study is available. For geospatial data, while the presented OGC standards enable an almost FAIR [19] and modern data sharing, they do not adequately support the reproducibility concept as pursued in Open Science. In other words, they do not offer any guarantee that the geodata accessed in a given instant can be persistently accessed, immutably, in the future.…”

Section: Reproducibility Research In the Geospatial Sectormentioning

confidence: 96%

“…These satellites produce a continuous and increasing stream of observations from space. Among the different benefits of using satellite imagery for environmental monitoring, Merodio Gómez et al [41] listed (1) Temporal resolution: capacity to capture data at different frequency of revisit (e.g., 5 days for Sentinel-2, 16 days for Landsat, up to 2.9 days in combined use mode and closer to the equator); and (2) Time-series: capacity to provide continuous data starting as early as 1972 (e.g., Landsat) as two important aspects [19].…”

Section: Updates and Changes In Time Of Raster Servicesmentioning

confidence: 99%

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The Challenges of Reproducibility for Research Based on Geodata Web Services

Cannata,

Collombin,

Ertz

et al. 2023

Preprint

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Modern research applies the Open Science approach that fosters the production and sharing of Open Data according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. In the geospatial context this is generally achieved through the setup of OGC Web services that implements open standards that satisfies the FAIR requirements. Nevertheless, the requirement of Findability is not fully satisfied by those services since there’s no use of persistent identifiers and no guarantee that the same dataset used for a study can be immutably accessed in a later period: a fact that hinders the replicability of research. This is particularly true in recent years where data-driven research and technological advances have boosted frequent updates of datasets. Here, we review needs and practices, supported by some real case examples, on frequent data or metadata updates in geo-datasets of different data types. Additionally we assess the currently available tools that support data versioning for databases, files and log-structured tables. Finally we discuss challenges and opportunities to enable geospatial web services that are fully FAIR: a fact that would provide, due to the massive use and increasing availability of geospatial data, a great push toward open science compliance with ultimately impacts on the science transparency and credibility.

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Section: Reproducibility Research In the Geospatial Sectormentioning

confidence: 96%

Section: Updates and Changes In Time Of Raster Servicesmentioning

confidence: 99%

The Challenges of Reproducibility for Research Based on Geodata Web Services

Cannata,

Collombin,

Ertz

et al. 2023

Preprint

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show abstract

“…In response to the need for a system to make big Earth observation data available in their region, SwissEnvEO was developed. The system consists of an SDI that is complemented with digital repository capabilities with the objective of facilitating the publication of Ready-to-Use information products that are derived from satellite EO data (Giuliani et al, 2021) (Huntington et al, 2021, Cudennec et al, 2020.…”

Section: Implementations Of Fair and Trust In Geoportals And Eo Appli...mentioning

confidence: 99%

Systems and Architectural Support for Open Data Principles: A Marine Earth Observation Perspective

Sibolla,

Molapo,

Vhengani

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The GMES and Africa, MarCOSIO project, promotes the sustainable management of marine resources, improves marine governance, and stimulates the growth of the blue economy in the Southern African and Indian ocean region. Because of its mandate, a wide range of applications, and regional view that incorporates eight countries, the MarCOSIO Information Management System adopts and continues to strive towards implementation of open data principles. This paper presents considerations of the MarCOSIO information management systems towards the adoption and implementation of open data, FAIR and TRUST principles, to ensure the sustainability of its services and offerings. The implementation of the system is evaluated against criteria that assess the alignment to FAIR, TRUST, and Open Data principles. An assessment of the results shows that the system aligns closely, though not fully, with the FAIR and TRUST principles. This is mainly due to the use of reputable open-source tools that implement well-known and accepted standards. On the basis of the services provided, the system cannot be fully open, as in some cases the need for security outweighs the openness. This is specifically true for cases where there is a need to protect personal information, and public disclosures are prohibited by law. The use of open data from the European Commission has allowed the rapid development of regionally relevant solutions that, in turn, have remarkably improved decision making in promoting the protection and growth of the ocean economy. It is one of the goals of the open data directive to increase public participation in the achievement of economic growth.

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“…Therefore, to improve the spatial and temporal resolution of land cover data of Switzerland, while keeping the thematic richness of the "Arealstatistik", the availability of more than 39 years of satellite EO Analysis Ready Data over Switzerland, made available by the Swiss Data Cube (https://www.swissdatacube.ch, accessed on 29 May 2023) [74][75][76], together with ML/DL techniques [77,78], allow the envisioning of innovative approaches to produce a yearly 10/30 m consistent time-series of LC and its changes, informing on class stability and transitions [79,80], to support effective national environmental monitoring [81,82].…”

Section: Perspectivesmentioning

confidence: 99%

Exploring Switzerland’s Land Cover Change Dynamics Using a National Statistical Survey

Thomas

Giuliani

2023

Land

Self Cite

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Timely and reliable Land Use and Cover change information is crucial to efficiently mitigate the negative impact of environmental changes. Switzerland has the ambitious objective of being a sustainable country while remaining an attractive business location with a high level of well-being. However, this aspiration is hampered by increasing pressures that are significantly impacting the environment and putting serious demands on land. In the present study, we used the national Land Cover (LC) dataset, named ArealStatistik, produced by the Federal Statistical Office, to explore the spatiotemporal patterns of Land Cover in Switzerland, providing a comprehensive assessment of land cover change at the national scale. Results indicate that, in general, Switzerland has undergone small, spatially dispersed, dynamic, and gradual change trends, with high rates of transition between low growing Brush Vegetation and forest LC classes in recent years. These pixel-level trends are more important in the lower altitude plateau and Jura regions, while greater changes in the spatial configuration of LC are observed in the alpine regions. However, findings also suggest that identifying drivers and understanding the rate of change are limited by the spatial resolution and temporal update frequency of the ArealStatistik. The ability to understand these drivers would benefit from a high-resolution annual LC dataset. Such a data product can be produced using the ArealStatistik together with dense satellite data time-series and Machine/Deep Learning techniques.

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SwissEnvEO: A FAIR National Environmental Data Repository for Earth Observation Open Science

Cited by 11 publications

References 62 publications

The Challenges of Reproducibility for Research Based on Geodata Web Services

The Challenges of Reproducibility for Research Based on Geodata Web Services

Systems and Architectural Support for Open Data Principles: A Marine Earth Observation Perspective

Exploring Switzerland’s Land Cover Change Dynamics Using a National Statistical Survey

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