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Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery in Google Earth and Microsoft Bing Maps as a Source of Reference Data

Author

Listed:
  • Myroslava Lesiv

    (Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), A-2361 Laxenburg, Austria)

  • Linda See

    (Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), A-2361 Laxenburg, Austria)

  • Juan Carlos Laso Bayas

    (Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), A-2361 Laxenburg, Austria)

  • Tobias Sturn

    (Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), A-2361 Laxenburg, Austria)

  • Dmitry Schepaschenko

    (Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), A-2361 Laxenburg, Austria)

  • Mathias Karner

    (Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), A-2361 Laxenburg, Austria)

  • Inian Moorthy

    (Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), A-2361 Laxenburg, Austria)

  • Ian McCallum

    (Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), A-2361 Laxenburg, Austria)

  • Steffen Fritz

    (Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), A-2361 Laxenburg, Austria)

Abstract

Very high resolution (VHR) satellite imagery from Google Earth and Microsoft Bing Maps is increasingly being used in a variety of applications from computer sciences to arts and humanities. In the field of remote sensing, one use of this imagery is to create reference data sets through visual interpretation, e.g., to complement existing training data or to aid in the validation of land-cover products. Through new applications such as Collect Earth, this imagery is also being used for monitoring purposes in the form of statistical surveys obtained through visual interpretation. However, little is known about where VHR satellite imagery exists globally or the dates of the imagery. Here we present a global overview of the spatial and temporal distribution of VHR satellite imagery in Google Earth and Microsoft Bing Maps. The results show an uneven availability globally, with biases in certain areas such as the USA, Europe and India, and with clear discontinuities at political borders. We also show that the availability of VHR imagery is currently not adequate for monitoring protected areas and deforestation, but is better suited for monitoring changes in cropland or urban areas using visual interpretation.

Suggested Citation

  • Myroslava Lesiv & Linda See & Juan Carlos Laso Bayas & Tobias Sturn & Dmitry Schepaschenko & Mathias Karner & Inian Moorthy & Ian McCallum & Steffen Fritz, 2018. "Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery in Google Earth and Microsoft Bing Maps as a Source of Reference Data," Land, MDPI, vol. 7(4), pages 1-18, October.
    • Handle: RePEc:gam:jlands:v:7:y:2018:i:4:p:118-:d:175058
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    References listed on IDEAS

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    1. Jean-François Pekel & Andrew Cottam & Noel Gorelick & Alan S. Belward, 2016. "High-resolution mapping of global surface water and its long-term changes," Nature, Nature, vol. 540(7633), pages 418-422, December.
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    2. Pinhati, Filipe Sampaio Casulari & Rodrigues, Lineu Neiva & Aires de Souza, Saulo, 2020. "Modelling the impact of on-farm reservoirs on dry season water availability in an agricultural catchment area of the Brazilian savannah," Agricultural Water Management, Elsevier, vol. 241(C).
    3. Chloe Brown & Anna Daniels & Doreen S. Boyd & Andrew Sowter & Giles Foody & Siddharth Kara, 2020. "Investigating the Potential of Radar Interferometry for Monitoring Rural Artisanal Cobalt Mines in the Democratic Republic of the Congo," Sustainability, MDPI, vol. 12(23), pages 1-20, November.
    4. Prishchepov, Alexander V. & Ponkina, Elena V. & Sun, Zhanli & Bavorova, Miroslava & Yekimovskaja, Olga A., 2021. "Revealing the intentions of farmers to recultivate abandoned farmland: A case study of the Buryat Republic in Russia," Land Use Policy, Elsevier, vol. 107(C).
    5. Giuseppe Molinario & Matthew Hansen & Peter Potapov & Alexandra Tyukavina & Stephen Stehman, 2020. "Contextualizing Landscape-Scale Forest Cover Loss in the Democratic Republic of Congo (DRC) between 2000 and 2015," Land, MDPI, vol. 9(1), pages 1-22, January.

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