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Assessment of Sustainable Development Goals Achieving with Use of NEXUS Approach in the Framework of GEOEssential ERA-PLANET Project

  • Nataliia Kussul
  • Mykola Lavreniuk
  • Leonid Sumilo
  • Andrii Kolotii
  • Olena Rakoid
  • Bohdan Yailymov
  • Andrii Shelestov
  • Vladimir Vasiliev
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 836)

Abstract

In this paper, we propose methodology for calculating indicators of sustainable development goals within the GEOEssential project, that is a part of ERA-PLANET Horizon 2020 project. We consider indicators 15.1.1 Forest area as proportion of total land area, 15.3.1 Proportion of land that is degraded over total land area, and 2.4.1. Proportion of agricultural area under productive and sustainable agriculture. For this, we used remote sensing data, weather and climatic models’ data and in-situ data. Accurate land cover maps are important for precisely land cover changes assessment. To improve the resolution and quality of existing global land cover maps, we proposed our own deep learning methodology for country level land cover providing. For calculating essential variables, that are vital for achieving indicators, NEXUS approach based on idea of fusion food, energy, and water was applied. Long-term land cover change maps connected with land productivity maps are essential for determining environment changes and estimation of consequences of anthropogenic activity.

Keywords

ERA-PLANET Classification maps Essential variables GEOEssential 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Nataliia Kussul
    • 1
    • 2
  • Mykola Lavreniuk
    • 1
    • 2
    • 3
  • Leonid Sumilo
    • 1
    • 2
    • 3
  • Andrii Kolotii
    • 1
    • 2
    • 3
  • Olena Rakoid
    • 4
  • Bohdan Yailymov
    • 1
    • 2
    • 3
  • Andrii Shelestov
    • 1
    • 2
    • 3
  • Vladimir Vasiliev
    • 3
  1. 1.Space Research Institute NASU-SSAUKyivUkraine
  2. 2.Igor Sikorsky Kyiv Polytechnic InstituteKyivUkraine
  3. 3.EOS Data AnalyticsKyivUkraine
  4. 4.National University of Life and Environmental Sciences of UkraineKyivUkraine

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