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https://doi.org/10.5194/essd-2018-13
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2018-13
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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Status: this preprint has been withdrawn by the authors.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
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This preprint has been withdrawn.
How to cite. Lesiv, M., See, L., Laso Bayas, J. C., Sturn, T., Schepaschenko, D., Karner, M., Moorthy, I., McCallum, I., and Fritz, S.: Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery for Monitoring Applications, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2018-13, 2018.
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.
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Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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- Supplement
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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
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AC1: 'Authors response to the Comments', Myroslava Lesiv, 17 Jul 2018
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AC1: 'Authors response to the Comments', Myroslava Lesiv, 17 Jul 2018
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SC2: 'Useful study', Nandin-Erdene Tsendbazar, 05 Jul 2018
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SC3: 'Good discussion on VHR data availability', Victor Maus, 13 Jul 2018
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SC4: 'A neat and concise study, which is useful for community', Alexander V. Prishchepov, 19 Jul 2018
Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
- Printer-friendly version
- Supplement
-
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
-
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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- Web Mapping for Farm Management Information Systems: A Review and Australian Orchard Case Study H. Dhonju et al. 10.3390/agronomy13102563
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- Tree Cover Estimation in Global Drylands from Space Using Deep Learning E. Guirado et al. 10.3390/rs12030343
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Latest update: 20 Nov 2024
Myroslava Lesiv
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg A-2361, Austria
Linda See
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg A-2361, Austria
Juan Carlos Laso Bayas
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg A-2361, Austria
Tobias Sturn
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg A-2361, Austria
Dmitry Schepaschenko
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg A-2361, Austria
Matthias Karner
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg A-2361, Austria
Inian Moorthy
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg A-2361, Austria
Ian McCallum
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg A-2361, Austria
Steffen Fritz
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg A-2361, Austria
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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.
The paper presents a global snapshot of the spatial and temporal distribution of VHR satellite...
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