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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLII-3/W3
https://doi.org/10.5194/isprs-archives-XLII-3-W3-171-2017
© Author(s) 2017. 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-3-W3-171-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
20 Oct 2017
| 20 Oct 2017
UAV-BASED PHOTOGRAMMETRIC POINT CLOUDS AND HYPERSPECTRAL IMAGING FOR MAPPING BIODIVERSITY INDICATORS IN BOREAL FORESTS
N. Saarinen
Dept. of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 University of Helsinki, Finland
Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute FGI, National Land Survey of Finland, 04310 Masala, Finland
M. Vastaranta
Dept. of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 University of Helsinki, Finland
Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute FGI, National Land Survey of Finland, 04310 Masala, Finland
R. Näsi
Dept. of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, National Land Survey, Geodeetinrinne 2, 04310 Masala, Finland
T. Rosnell
Dept. of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, National Land Survey, Geodeetinrinne 2, 04310 Masala, Finland
T. Hakala
Dept. of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, National Land Survey, Geodeetinrinne 2, 04310 Masala, Finland
E. Honkavaara
Dept. of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, National Land Survey, Geodeetinrinne 2, 04310 Masala, Finland
M. A. Wulder
Pacific Forestry Centre, National Resources Canada, 506 West Burnside Road, Victoria, British Columbia, V8Z 1M5, Canada
V. Luoma
Dept. of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 University of Helsinki, Finland
Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute FGI, National Land Survey of Finland, 04310 Masala, Finland
A. M. G. Tommaselli
Dept. of Cartography, São Paulo State University, Roberto Simonsen 305, 19060-900 Presidente Prudente, Brazil
N. N. Imai
Dept. of Cartography, São Paulo State University, Roberto Simonsen 305, 19060-900 Presidente Prudente, Brazil
E. A. W. Ribeiro
Catarinense Federal Institute, Rodovia Duque de Caxias – km 6 – s/n, 89240-000 São Francisco do Sul, Brazil
R. B. Guimarães
Dept. of Geography, São Paulo State University, Roberto Simonsen 305, 19060-900 Presidente Prudente, Brazil
M. Holopainen
Dept. of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 University of Helsinki, Finland
Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute FGI, National Land Survey of Finland, 04310 Masala, Finland
J. Hyyppä
Dept. of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, National Land Survey, Geodeetinrinne 2, 04310 Masala, Finland
Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute FGI, National Land Survey of Finland, 04310 Masala, Finland
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1875–1880, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1875-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1875-2019, 2019
É. A. S. Moriya, N. N. Imai, A. M. G. Tommaselli, A. Berveglieri, E. Honkavaara, M. A. Soares, and M. Marino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1881–1886, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1881-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1881-2019, 2019
N. N. Imai, A. M. G. Tommaselli, A. Berveglieri, and E. A. S. Moriya
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 371–377, https://doi.org/10.5194/isprs-archives-XLII-2-W13-371-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-371-2019, 2019
M. V. Machado, A. M. G. Tommaselli, V. M. Tachibana, R. P. Martins-Neto, and M. B. Campos
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 449–454, https://doi.org/10.5194/isprs-archives-XLII-2-W13-449-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-449-2019, 2019
R. A. Oliveira, R. Näsi, O. Niemeläinen, L. Nyholm, K. Alhonoja, J. Kaivosoja, N. Viljanen, T. Hakala, S. Nezami, L. Markelin, L. Jauhiainen, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 489–494, https://doi.org/10.5194/isprs-archives-XLII-2-W13-489-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-489-2019, 2019
M. Weinmann, R. Müller, R. Reulke, E. Honkavaara, D. Tuia, and S. Keller
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 607–608, https://doi.org/10.5194/isprs-annals-IV-2-W5-607-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-607-2019, 2019
L. Markelin, J. Suomalainen, T. Hakala, R. A. Oliveira, N. Viljanen, R. Näsi, B. Scott, T. Theocharous, C. Greenwell, N. Fox, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 283–288, https://doi.org/10.5194/isprs-archives-XLII-1-283-2018, https://doi.org/10.5194/isprs-archives-XLII-1-283-2018, 2018
G. T. Miyoshi, N. N. Imai, A. M. G. Tommaselli, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 301–305, https://doi.org/10.5194/isprs-archives-XLII-1-301-2018, https://doi.org/10.5194/isprs-archives-XLII-1-301-2018, 2018
A. M. G. Tommaselli, L. D. Santos, A. Berveglieri, R. A. Oliveira, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 429–436, https://doi.org/10.5194/isprs-archives-XLII-1-429-2018, https://doi.org/10.5194/isprs-archives-XLII-1-429-2018, 2018
T. Hakala, I. Pölönen, E. Honkavaara, R. Näsi, T. Hakala, and A. Lindfors
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 411–417, https://doi.org/10.5194/isprs-archives-XLII-2-411-2018, https://doi.org/10.5194/isprs-archives-XLII-2-411-2018, 2018
R. A. Oliveira, E. Khoramshahi, J. Suomalainen, T. Hakala, N. Viljanen, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 789–795, https://doi.org/10.5194/isprs-archives-XLII-2-789-2018, https://doi.org/10.5194/isprs-archives-XLII-2-789-2018, 2018
R. Näsi, N. Viljanen, R. Oliveira, J. Kaivosoja, O. Niemeläinen, T. Hakala, L. Markelin, S. Nezami, J. Suomalainen, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1305–1310, https://doi.org/10.5194/isprs-archives-XLII-3-1305-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1305-2018, 2018
Eliisa S. Lotsari, Mikel Calle, Gerardo Benito, Antero Kukko, Harri Kaartinen, Juha Hyyppä, Hannu Hyyppä, and Petteri Alho
Earth Surf. Dynam., 6, 163–185, https://doi.org/10.5194/esurf-6-163-2018, https://doi.org/10.5194/esurf-6-163-2018, 2018
Short summary
Short summary
This paper analyses the timing of topographical changes of a gravel bed ephemeral river channel during consecutive and moderate- and low-magnitude floods by applying a morphodynamic model calibrated with pre- and post-event surveys using RTK-GPS and mobile laser scanning. The channel acted as a braided river during lower flows but as a meandering river during higher flows. The channel changes can be greater during the long-lasting receding phase than during the rising phase of the floods.
S. Tuominen, R. Näsi, E. Honkavaara, A. Balazs, T. Hakala, N. Viljanen, I. Pölönen, H. Saari, and J. Reinikainen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 185–194, https://doi.org/10.5194/isprs-archives-XLII-3-W3-185-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-185-2017, 2017
A. Berveglieri, A. M. G. Tommaselli, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 19–25, https://doi.org/10.5194/isprs-archives-XLII-3-W3-19-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-19-2017, 2017
N. N. Imai, E. A. S. Moriya, E. Honkavaara, G. T. Miyoshi, M. V. A. de Moraes, A. M. G. Tommaselli, and R. Näsi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 73–79, https://doi.org/10.5194/isprs-archives-XLII-3-W3-73-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-73-2017, 2017
S. Junttila, M. Vastaranta, R. Linnakoski, J. Sugano, H. Kaartinen, A. Kukko, M. Holopainen, H. Hyyppä, and J. Hyyppä
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 81–85, https://doi.org/10.5194/isprs-archives-XLII-3-W3-81-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-81-2017, 2017
M. Katoh, S. Deng, Y. Takenaka, K. Cheung, K. Oono, M. Horisawa, J. Hyyppä, X. Yu, X. Liang, and Y. Wang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 95–100, https://doi.org/10.5194/isprs-archives-XLII-3-W3-95-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-95-2017, 2017
W. Liu, J. Atherton, M. Mõttus, A. MacArthur, H. Teemu, K. Maseyk, I. Robinson, E. Honkavaara, and A. Porcar-Castell
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 107–111, https://doi.org/10.5194/isprs-archives-XLII-3-W3-107-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-107-2017, 2017
L. Markelin, E. Honkavaara, R. Näsi, N. Viljanen, T. Rosnell, T. Hakala, M. Vastaranta, T. Koivisto, and M. Holopainen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 113–118, https://doi.org/10.5194/isprs-archives-XLII-3-W3-113-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-113-2017, 2017
L. Matikainen, K. Karila, J. Hyyppä, E. Puttonen, P. Litkey, and E. Ahokas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 119–122, https://doi.org/10.5194/isprs-archives-XLII-3-W3-119-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-119-2017, 2017
G. T. Miyoshi, N. N. Imai, M. V. A. de Moraes, A. M. G. Tommaselli, and R. Näsi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 123–128, https://doi.org/10.5194/isprs-archives-XLII-3-W3-123-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-123-2017, 2017
R. Näsi, N. Viljanen, J. Kaivosoja, T. Hakala, M. Pandžić, L. Markelin, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 137–141, https://doi.org/10.5194/isprs-archives-XLII-3-W3-137-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-137-2017, 2017
E. Honkavaara, T. Hakala, O. Nevalainen, N. Viljanen, T. Rosnell, E. Khoramshahi, R. Näsi, R. Oliveira, and A. Tommaselli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 77–82, https://doi.org/10.5194/isprs-archives-XLI-B7-77-2016, https://doi.org/10.5194/isprs-archives-XLI-B7-77-2016, 2016
A. M. G. Tommaselli and F. M. Torres
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 711–715, https://doi.org/10.5194/isprs-archives-XLI-B1-711-2016, https://doi.org/10.5194/isprs-archives-XLI-B1-711-2016, 2016
R. Näsi, E. Honkavaara, S. Tuominen, H. Saari, I. Pölönen, T. Hakala, N. Viljanen, J. Soukkamäki, I. Näkki, H. Ojanen, and J. Reinikainen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 1143–1148, https://doi.org/10.5194/isprs-archives-XLI-B1-1143-2016, https://doi.org/10.5194/isprs-archives-XLI-B1-1143-2016, 2016
A. Berveglieri and A. M. G. Tommaselli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3-W4, 45–50, https://doi.org/10.5194/isprs-archives-XL-3-W4-45-2016, https://doi.org/10.5194/isprs-archives-XL-3-W4-45-2016, 2016
A. M. G. Tommaselli, A. Berveglieri, R. A. Oliveira, L. Y. Nagai, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3-W4, 109–115, https://doi.org/10.5194/isprs-archives-XL-3-W4-109-2016, https://doi.org/10.5194/isprs-archives-XL-3-W4-109-2016, 2016
J. I. Peltoniemi, M. Gritsevich, T. Hakala, P. Dagsson-Waldhauserová, Ó. Arnalds, K. Anttila, H.-R. Hannula, N. Kivekäs, H. Lihavainen, O. Meinander, J. Svensson, A. Virkkula, and G. de Leeuw
The Cryosphere, 9, 2323–2337, https://doi.org/10.5194/tc-9-2323-2015, https://doi.org/10.5194/tc-9-2323-2015, 2015
Short summary
Short summary
Light-absorbing impurities change the reflectance of snow in different ways. Some particles are heated by the Sun and they sink out of sight. During the process, snow may look darker than pure snow when observed by nadir, but at larger view zenith angles the snow may look as white as clean snow. Thus an observer on the ground may overestimate the albedo, while a satellite underestimates the albedo. Climate studies need to examine how the contaminants behave in snow, not only their total amounts.
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.
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