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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLIII-B2-2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-959-2022
© Author(s) 2022. 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-XLIII-B2-2022-959-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
30 May 2022
| 30 May 2022
MODELLING COLOUR ABSORPTION OF UNDERWATER IMAGES USING SFM-MVS GENERATED DEPTH MAPS
M. Vlachos
Cyprus University of Technology, Civil Engineering and Geomatics Dept., Lab of Photogrammetric Vision 2-6 Saripolou str., 3036, Limassol, Cyprus
A. Calantropio
Laboratory of Geomatics for Cultural Heritage (LabG4CH), Department of Architecture and Design (DAD), Polytechnic University of Turin, Viale Pier Andrea Mattioli, 39, 10125 Torino (TO), Italy
D. Skarlatos
Cyprus University of Technology, Civil Engineering and Geomatics Dept., Lab of Photogrammetric Vision 2-6 Saripolou str., 3036, Limassol, Cyprus
F. Chiabrando
Laboratory of Geomatics for Cultural Heritage (LabG4CH), Department of Architecture and Design (DAD), Polytechnic University of Turin, Viale Pier Andrea Mattioli, 39, 10125 Torino (TO), Italy
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W5, 605–612, https://doi.org/10.5194/isprs-archives-XLII-2-W5-605-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W5-605-2017, 2017
F. Chiabrando, M. Naretto, G. Sammartano, L. Sambuelli, A. Spanò, and L. Teppati Losè
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5-W1, 227–234, https://doi.org/10.5194/isprs-archives-XLII-5-W1-227-2017, https://doi.org/10.5194/isprs-archives-XLII-5-W1-227-2017, 2017
Eleni Savvidou, Andreas Efstratiadis, Antonis D. Koussis, Antonis Koukouvinos, and Dimitrios Skarlatos
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-627, https://doi.org/10.5194/hess-2016-627, 2016
Manuscript not accepted for further review
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A systematic framework for delineating Hydrological Response Units (HRUs) is proposed, based on a modified Curve Number (CN) approach that accounts, by means of classes, for the soil permeability, land cover, and drainage capacity of a river basin. The aim is to reduce the subjectivity introduced by HRUs and provide a parsimonious modelling scheme. Results showed optimal performance of the CN approach in calibration and particularly in validation, compared against alternative HRU approaches.
Andreas Georgiou and Dimitrios Skarlatos
Geosci. Instrum. Method. Data Syst., 5, 321–332, https://doi.org/10.5194/gi-5-321-2016, https://doi.org/10.5194/gi-5-321-2016, 2016
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The objective of this paper is to present a general integrated framework to evaluate land suitability for the optimal placement of solar park, which is based on a combination of a GIS, remote sensing techniques, and multi-criteria decision-making methods. Innovative aspect derives from the proposed tool as currently implemented within a local GIS, which provides a versatile platform of analysis and semi-automation of the operations, which might also extended into full automation.
D. Skarlatos and S. Yiatros
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-5, 35–41, https://doi.org/10.5194/isprs-annals-III-5-35-2016, https://doi.org/10.5194/isprs-annals-III-5-35-2016, 2016
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