International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLIII-B3-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1491–1496, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1491-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1491–1496, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1491-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  22 Aug 2020

22 Aug 2020

EARTH OBSERVATIONS AS A TOOL FOR DETECTING AND MONITORING POTENTIAL ENVIRONMENTAL VIOLATIONS AND POLICY IMPLEMENTATION

P. Patias1, G. Mallinis1, V. Tsioukas1, C. Georgiadis1, D. Kaimaris1, M. Tassopoulou1, N. Verde1, M. Dohr2, and M. Riffler2 P. Patias et al.
  • 1Aristotle University of Thessaloniki, Laboratory of Photogrammetry and Remote Sensing, Thessaloniki, Greece
  • 2Geoville Information Systems and Data Processing GmbH, Innsbruck, Austria

Keywords: Sentinel-2, Change – Detection, Time Series, Image Analysis, Object – Based

Abstract. In recent years advances in Earth Observation (EO) have increased our ability to inventory, monitor, and understand Earth’s natural and artificial ecosystems. In particular, recent technological developments in the instrument characteristics of the remote sensing systems enabled large-scale usage of EO in environmental governance and protection. Remote sensing can be a potent tool employed in the field of environmental compliance. However, to extract and distribute relevant information to potential stakeholders, simple, yet efficient and robust approaches are needed. The focus of our research is the development of EO algorithms and the corresponding EO processing chains that could be used operationally for providing cost-efficient information to end-users to address environmental compliance and tackle environmental violations over specific thematic domains using freely available Copernicus data. The EO algorithms and the relevant EO processing chains have been developed as part of the EU-H2020 funded project: “EnviroLENS-Copernicus for environmental law enforcement support” where the demonstration area of our approach is in the Montenegro – Albania border. The case considers several sites along the border to Albania, from the coastal area of Velika Plaža to the North Lake Skadar National Park. All sites have been designated in the past as protected areas, due to their rich biodiversity and threatened habitats. The focus of this contribution is on the deforestation detection processing chain. The developed EO processing chains rely on the use and analysis of multi-temporal Sentinel-2 images, while it adopts an object-based perspective for detecting, quantifying, and mapping potential environmental violations.