the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery for Monitoring Applications
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.
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Interactive discussion
- RC1: 'Minor Adjustments: Very good submission!', Anonymous Referee #1, 21 Apr 2018
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RC2: 'Review ESSD-2018-13 High Resolution Spatial Imagery', Anonymous Referee #2, 19 Jun 2018
- AC1: 'Authors response to the Comments', Myroslava Lesiv, 17 Jul 2018
- SC2: 'Useful study', Nandin-Erdene Tsendbazar, 05 Jul 2018
- SC3: 'Good discussion on VHR data availability', Victor Maus, 13 Jul 2018
- SC4: 'A neat and concise study, which is useful for community', Alexander V. Prishchepov, 19 Jul 2018
Interactive discussion
- RC1: 'Minor Adjustments: Very good submission!', Anonymous Referee #1, 21 Apr 2018
-
RC2: 'Review ESSD-2018-13 High Resolution Spatial Imagery', Anonymous Referee #2, 19 Jun 2018
- AC1: 'Authors response to the Comments', Myroslava Lesiv, 17 Jul 2018
- SC2: 'Useful study', Nandin-Erdene Tsendbazar, 05 Jul 2018
- SC3: 'Good discussion on VHR data availability', Victor Maus, 13 Jul 2018
- SC4: 'A neat and concise study, which is useful for community', Alexander V. Prishchepov, 19 Jul 2018
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
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Cited
17 citations as recorded by crossref.
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- Cost-Effective Groundwater Potential Mapping by Integrating Multiple Remote Sensing Data and the Index–Overlay Method L. Nainggolan et al. 10.3390/rs16030502
- Tree Cover Estimation in Global Drylands from Space Using Deep Learning E. Guirado et al. 10.3390/rs12030343
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Myroslava Lesiv
Linda See
Juan Carlos Laso Bayas
Tobias Sturn
Dmitry Schepaschenko
Matthias Karner
Inian Moorthy
Ian McCallum
Steffen Fritz
This preprint has been withdrawn.
- Preprint
(1876 KB) - Metadata XML
-
Supplement
(617 KB) - BibTeX
- EndNote