- Article
(8699 KB) - Metadata XML
- May 09, 2025
- |
- Home
- |
- Sitemap
- |
- The ISPRS Foundation
- |
- 𝕏
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
Related authors
D. Duarte and C. C. Fonte
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 813–820, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-813-2023, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-813-2023, 2023
D. Duarte, C. C. Fonte, J. Patriarca, and I. Jesus
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 25–31, https://doi.org/10.5194/isprs-annals-V-3-2022-25-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-25-2022, 2022
C. C. Fonte, J. Patriarca, and D. Duarte
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-4-2021, 49–54, https://doi.org/10.5194/isprs-annals-V-4-2021-49-2021, https://doi.org/10.5194/isprs-annals-V-4-2021-49-2021, 2021
C. C. Fonte, L. See, J. C. Laso-Bayas, M. Lesiv, and S. Fritz
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 669–674, https://doi.org/10.5194/isprs-annals-V-3-2020-669-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-669-2020, 2020
C. C. Fonte, L. See, M. Lesiv, and S. Fritz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1213–1220, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1213-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1213-2019, 2019
C. C. Fonte, J. Patriarca, J. Estima, J.-P. de Almeida, and A. Cardoso
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 217–224, https://doi.org/10.5194/isprs-archives-XLII-4-217-2018, https://doi.org/10.5194/isprs-archives-XLII-4-217-2018, 2018
Nicolas Lampach, Jon Olav Skoien, Helena Ramos, Julien Gaffuri, Renate Koeble, Linda See, and Marijn Van der Velde
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-59, https://doi.org/10.5194/essd-2025-59, 2025
Preprint under review for ESSD
Short summary
Short summary
Eurostat and JRC developed a new methodology to make geospatial data from agricultural census available to users, while ensuring that no confidential information from individuals is disclosed. The geospatial data presented in the article correspond to the contextual indicators of the monitoring and evaluation framework of the Common Agricultural Policy. Our exploratory analysis reveals several interesting patterns which contribute to the broader debate on the future of European agriculture.
Yuanxin Pan, Grzegorz Kłopotek, Laura Crocetti, Rudi Weinacker, Tobias Sturn, Linda See, Galina Dick, Gregor Möller, Markus Rothacher, Ian McCallum, Vicente Navarro, and Benedikt Soja
Atmos. Meas. Tech., 17, 4303–4316, https://doi.org/10.5194/amt-17-4303-2024, https://doi.org/10.5194/amt-17-4303-2024, 2024
Short summary
Short summary
Crowdsourced smartphone GNSS data were processed with a dedicated data processing pipeline and could produce millimeter-level accurate estimates of zenith total delay (ZTD) – a critical atmospheric variable. This breakthrough not only demonstrates the feasibility of using ubiquitous devices for high-precision atmospheric monitoring but also underscores the potential for a global, cost-effective tropospheric monitoring network.
Evelyn Uuemaa, Marco Ciolli, and Marco Minghini
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W12-2024, 1–2, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-1-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-1-2024, 2024
Margherita Di Leo, Manlio Bacco, Albana Kona, and Marco Minghini
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W12-2024, 43–49, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-43-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-43-2024, 2024
Marco Minghini, Sara Thabit Gonzalez, and Lorenzo Gabrielli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W12-2024, 97–103, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-97-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-97-2024, 2024
C. E. Kilsedar, M. Dowell, M. Di Leo, J. Dusart, A. Kotsev, M. Minghini, and A. Kona
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 953–958, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-953-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-953-2023, 2023
D. Duarte and C. C. Fonte
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 813–820, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-813-2023, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-813-2023, 2023
M. Minghini, M. Ciolli, and G. Neziri
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W7-2023, 1–2, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-1-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-1-2023, 2023
M. Di Leo, M. Minghini, A. Kona, N. Spadaro, A. Kotsev, J. Dusart, S. Lumnitz, C. M. Ilie, C. E. Kilsedar, and A. Tzotsos
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W7-2023, 33–40, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-33-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-33-2023, 2023
A. Sarretta, M. Napolitano, and M. Minghini
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W7-2023, 193–200, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-193-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-193-2023, 2023
P. Mooney and M. Minghini
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W1-2022, 307–313, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-307-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-307-2022, 2022
M. A. Brovelli, M. Ciolli, and M. Minghini
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W1-2022, 1–3, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-1-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-1-2022, 2022
D. Duarte, C. C. Fonte, J. Patriarca, and I. Jesus
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 25–31, https://doi.org/10.5194/isprs-annals-V-3-2022-25-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-25-2022, 2022
A. Sarretta and M. Minghini
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W2-2021, 159–166, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-159-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-159-2021, 2021
C. C. Fonte, J. Patriarca, and D. Duarte
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-4-2021, 49–54, https://doi.org/10.5194/isprs-annals-V-4-2021-49-2021, https://doi.org/10.5194/isprs-annals-V-4-2021-49-2021, 2021
Michele Ferri, Uta Wehn, Linda See, Martina Monego, and Steffen Fritz
Hydrol. Earth Syst. Sci., 24, 5781–5798, https://doi.org/10.5194/hess-24-5781-2020, https://doi.org/10.5194/hess-24-5781-2020, 2020
Short summary
Short summary
As part of the flood risk management strategy of the
Brenta-Bacchiglione catchment (Italy), a citizen observatory for flood risk management is currently being implemented. A cost–benefit analysis of the citizen observatory was undertaken to demonstrate the value of this approach in monetary terms. Results show a reduction in avoided damage of 45 % compared to a scenario without implementation of the citizen observatory. The idea is to promote this methodology for future flood risk management.
Miao Lu, Wenbin Wu, Liangzhi You, Linda See, Steffen Fritz, Qiangyi Yu, Yanbing Wei, Di Chen, Peng Yang, and Bing Xue
Earth Syst. Sci. Data, 12, 1913–1928, https://doi.org/10.5194/essd-12-1913-2020, https://doi.org/10.5194/essd-12-1913-2020, 2020
Short summary
Short summary
Global cropland distribution is critical for agricultural monitoring and food security. We propose a new Self-adapting Statistics Allocation Model (SASAM) to develop the global map of cropland distribution. SASAM is based on the fusion of multiple existing cropland maps and multilevel statistics of cropland area, which is independent of training samples. The synergy map has higher accuracy than the input datasets and better consistency with the cropland statistics.
C. C. Fonte, L. See, J. C. Laso-Bayas, M. Lesiv, and S. Fritz
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 669–674, https://doi.org/10.5194/isprs-annals-V-3-2020-669-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-669-2020, 2020
Michele Ferri, Uta Wehn, Linda See, and Steffen Fritz
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-627, https://doi.org/10.5194/hess-2019-627, 2019
Manuscript not accepted for further review
Short summary
Short summary
Citizen observatories involve citizens in making environmental observations that help to inform the decision making of local authorities. Although citizen observatories can generate many benefits, they also have an associated cost. In this paper, we undertook a cost-benefit analysis of a citizen observatory on flooding in northern Italy. The results show that the benefits outweigh the costs by 2 to 1. Implementation of other citizen observatories could help to reduce flood risk in the future.
M. Minghini, A. Kotsev, and M. Lutz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W14, 167–174, https://doi.org/10.5194/isprs-archives-XLII-4-W14-167-2019, https://doi.org/10.5194/isprs-archives-XLII-4-W14-167-2019, 2019
C. C. Fonte, L. See, M. Lesiv, and S. Fritz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1213–1220, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1213-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1213-2019, 2019
O. Danylo, I. Moorthy, T. Sturn, L. See, J.-C. Laso Bayas, D. Domian, D. Fraisl, C. Giovando, B. Girardot, R. Kapur, P.-P. Matthieu, and S. Fritz
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4, 27–32, https://doi.org/10.5194/isprs-annals-IV-4-27-2018, https://doi.org/10.5194/isprs-annals-IV-4-27-2018, 2018
M. A. Brovelli, H. Wu, M. Minghini, M. E. Molinari, C. E. Kilsedar, X. Zheng, P. Shu, and J. Chen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 61–68, https://doi.org/10.5194/isprs-archives-XLII-4-61-2018, https://doi.org/10.5194/isprs-archives-XLII-4-61-2018, 2018
C. C. Fonte, J. Patriarca, J. Estima, J.-P. de Almeida, and A. Cardoso
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 217–224, https://doi.org/10.5194/isprs-archives-XLII-4-217-2018, https://doi.org/10.5194/isprs-archives-XLII-4-217-2018, 2018
M. A. Brovelli, M. Minghini, M. E. Molinari, H. Wu, X. Zheng, and J. Chen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W8, 15–22, https://doi.org/10.5194/isprs-archives-XLII-4-W8-15-2018, https://doi.org/10.5194/isprs-archives-XLII-4-W8-15-2018, 2018
S. Coetzee, M. Minghini, P. Solis, V. Rautenbach, and C. Green
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W8, 35–42, https://doi.org/10.5194/isprs-archives-XLII-4-W8-35-2018, https://doi.org/10.5194/isprs-archives-XLII-4-W8-35-2018, 2018
M. Minghini, M. A. Brovelli, and F. Frassinelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W8, 147–154, https://doi.org/10.5194/isprs-archives-XLII-4-W8-147-2018, https://doi.org/10.5194/isprs-archives-XLII-4-W8-147-2018, 2018
Myroslava Lesiv, Linda See, Juan Carlos Laso Bayas, Tobias Sturn, Dmitry Schepaschenko, Matthias Karner, Inian Moorthy, Ian McCallum, and Steffen Fritz
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2018-13, https://doi.org/10.5194/essd-2018-13, 2018
Preprint withdrawn
Short summary
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.
M. A. Brovelli, M. Minghini, C. E. Kilsedar, M. Zurbarán, M. Aiello, and M. Gianinetto
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
M. A. Brovelli, F. C. Fahl, M. Minghini, and M. E. Molinari
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
The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.
Useful Links
Useful External Links
Our Contact
c/o
Leibniz University Hannover
Institute of Photogrammetry and GeoInformation
Nienburger Str. 1
D-30167 Hannover
GERMANY
Email: isprs-sg@isprs.org