Preprints
https://doi.org/10.5194/essd-2018-13
https://doi.org/10.5194/essd-2018-13
23 Mar 2018
 | 23 Mar 2018
Status: this preprint has been withdrawn by the authors.

Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery for Monitoring Applications

Myroslava Lesiv, Linda See, Juan Carlos Laso Bayas, Tobias Sturn, Dmitry Schepaschenko, Matthias Karner, Inian Moorthy, Ian McCallum, and Steffen Fritz

Abstract. Very high resolution (VHR) satellite imagery from Google Earth and Bing Maps is increasingly being used in a variety of applications from computer sciences to arts and humanities. In the field of remote sensing, this imagery is used to create detailed time-sensitive maps, e.g. for emergency response purposes, or to validate coarser resolution products such as global land cover maps. However, little is known about where VHR satellite imagery exists globally or the dates of the imagery. Here we present a global snapshot of the spatial and temporal distribution of VHR satellite imagery in Google Earth and Bing Maps. The results show an uneven availability globally, with biases in certain areas such as the USA, Europe and India. 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. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885767.

This preprint has been withdrawn.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Myroslava Lesiv, Linda See, Juan Carlos Laso Bayas, Tobias Sturn, Dmitry Schepaschenko, Matthias Karner, Inian Moorthy, Ian McCallum, and Steffen Fritz

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Myroslava Lesiv, Linda See, Juan Carlos Laso Bayas, Tobias Sturn, Dmitry Schepaschenko, Matthias Karner, Inian Moorthy, Ian McCallum, and Steffen Fritz

Data sets

A global snapshot of the spatial and temporal distribution of very high resolution satellite imagery in Google Earth and Bing Maps as of 11th of January, M. Lesiv, L. See, J. C. Laso Bayas, T. Sturn, D. Schepaschenko, M. Karner, I. Moorthy, I. McCallum, and S. Fritz https://doi.org/10.1594/PANGAEA.885767

Myroslava Lesiv, Linda See, Juan Carlos Laso Bayas, Tobias Sturn, Dmitry Schepaschenko, Matthias Karner, Inian Moorthy, Ian McCallum, and Steffen Fritz

Viewed

Total article views: 2,909 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,262 548 99 2,909 277 132 161
  • HTML: 2,262
  • PDF: 548
  • XML: 99
  • Total: 2,909
  • Supplement: 277
  • BibTeX: 132
  • EndNote: 161
Views and downloads (calculated since 23 Mar 2018)
Cumulative views and downloads (calculated since 23 Mar 2018)

Viewed (geographical distribution)

Total article views: 2,640 (including HTML, PDF, and XML) Thereof 2,623 with geography defined and 17 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 05 Dec 2024
Download

This preprint has been withdrawn.

Short summary
The paper presents a global snapshot of the spatial and temporal distribution of VHR satellite imagery in Google Earth and Bing Maps. The results show an uneven availability globally, with biases in certain areas such as the USA, Europe and India. 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.
Altmetrics