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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLII-4
https://doi.org/10.5194/isprs-archives-XLII-4-209-2018
© 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/isprs-archives-XLII-4-209-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
19 Sep 2018
| 19 Sep 2018
CLASSIFICATION OF BUILDING FUNCTION USING AVAILABLE SOURCES OF VGI
C. C. Fonte
Department of Mathematics, University of Coimbra, Coimbra, Portugal
Institute for Systems Engineering and Computers at Coimbra (INESCC), Coimbra, Portugal
M. Minghini
Department of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy
V. Antoniou
Geographic Directorate, Hellenic Army General Staff, Athens, Greece
J. Patriarca
Institute for Systems Engineering and Computers at Coimbra (INESCC), Coimbra, Portugal
International Institute for Applied Systems Analysis, Laxenburg, Austria
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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.
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W2, 51–55, https://doi.org/10.5194/isprs-archives-XLII-4-W2-51-2017, https://doi.org/10.5194/isprs-archives-XLII-4-W2-51-2017, 2017
M. Minghini, M. A. Brovelli, D. Vandenbroucke, M. Carbonaro, S. Prüller, M. Painho, G. Martirano, and D. Frigne
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W2, 129–135, https://doi.org/10.5194/isprs-archives-XLII-4-W2-129-2017, https://doi.org/10.5194/isprs-archives-XLII-4-W2-129-2017, 2017
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 913–917, https://doi.org/10.5194/isprs-archives-XLI-B7-913-2016, https://doi.org/10.5194/isprs-archives-XLI-B7-913-2016, 2016
M. A. Brovelli, M. Minghini, and M. E. Molinari
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 919–925, https://doi.org/10.5194/isprs-archives-XLI-B7-919-2016, https://doi.org/10.5194/isprs-archives-XLI-B7-919-2016, 2016
M. A. Brovelli, M. Minghini, M. E. Molinari, and M. Molteni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 609–614, https://doi.org/10.5194/isprs-archives-XLI-B2-609-2016, https://doi.org/10.5194/isprs-archives-XLI-B2-609-2016, 2016
M. A. Brovelli, M. Minghini, M. E. Molinari, and G. Zamboni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 615–620, https://doi.org/10.5194/isprs-archives-XLI-B2-615-2016, https://doi.org/10.5194/isprs-archives-XLI-B2-615-2016, 2016
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