- Article
(6034 KB) - Metadata XML
- June 30, 2024
- |
- Home
- |
- Sitemap
- |
- The ISPRS Foundation
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLVIII-2-2024
https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-167-2024
© Author(s) 2024. 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-XLVIII-2-2024-167-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
11 Jun 2024
| 11 Jun 2024
Autonomous robotic drone system for mapping forest interiors
Väinö Karjalainen
Finnish Geospatial Research Institute in National Land Survey of Finland, Vuorimiehentie 5, 02150 Espoo, Finland
Niko Koivumäki
Finnish Geospatial Research Institute in National Land Survey of Finland, Vuorimiehentie 5, 02150 Espoo, Finland
Teemu Hakala
Finnish Geospatial Research Institute in National Land Survey of Finland, Vuorimiehentie 5, 02150 Espoo, Finland
Anand George
Finnish Geospatial Research Institute in National Land Survey of Finland, Vuorimiehentie 5, 02150 Espoo, Finland
Jesse Muhojoki
Finnish Geospatial Research Institute in National Land Survey of Finland, Vuorimiehentie 5, 02150 Espoo, Finland
Eric Hyyppa
Finnish Geospatial Research Institute in National Land Survey of Finland, Vuorimiehentie 5, 02150 Espoo, Finland
Juha Suomalainen
Finnish Geospatial Research Institute in National Land Survey of Finland, Vuorimiehentie 5, 02150 Espoo, Finland
Eija Honkavaara
Finnish Geospatial Research Institute in National Land Survey of Finland, Vuorimiehentie 5, 02150 Espoo, Finland
Related authors
V. Karjalainen, T. Hakala, A. George, N. Koivumäki, J. Suomalainen, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 597–603, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-597-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-597-2023, 2023
Lauri Markelin, Mikko Sippo, Petri Leiso, and Eija Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-2024, 219–224, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-219-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-219-2024, 2024
A.-M. Raita-Hakola, S. Rahkonen, J. Suomalainen, L. Markelin, R. Oliveira, T. Hakala, N. Koivumäki, E. Honkavaara, and I. Pölönen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1771–1778, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1771-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1771-2023, 2023
R. A. Oliveira, R. Näsi, P. Korhonen, A. Mustonen, O. Niemeläinen, N. Koivumäki, T. Hakala, J. Suomalainen, J. Kaivosoja, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1861–1866, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1861-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1861-2023, 2023
V. Karjalainen, T. Hakala, A. George, N. Koivumäki, J. Suomalainen, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 597–603, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-597-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-597-2023, 2023
T. Faitli, T. Hakala, H. Kaartinen, J. Hyyppä, and A. Kukko
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 145–150, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-145-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-145-2023, 2023
J. Suomalainen, R. A. Oliveira, T. Hakala, N. Koivumäki, L. Markelin, R. Näsi, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 67–72, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-67-2022, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-67-2022, 2022
L. E. Christovam, M. H. Shimabukuro, M. L. B. T. Galo, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 823–828, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-823-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-823-2021, 2021
Terhikki Manninen, Kati Anttila, Emmihenna Jääskeläinen, Aku Riihelä, Jouni Peltoniemi, Petri Räisänen, Panu Lahtinen, Niilo Siljamo, Laura Thölix, Outi Meinander, Anna Kontu, Hanne Suokanerva, Roberta Pirazzini, Juha Suomalainen, Teemu Hakala, Sanna Kaasalainen, Harri Kaartinen, Antero Kukko, Olivier Hautecoeur, and Jean-Louis Roujean
The Cryosphere, 15, 793–820, https://doi.org/10.5194/tc-15-793-2021, https://doi.org/10.5194/tc-15-793-2021, 2021
Short summary
Short summary
The primary goal of this paper is to present a model of snow surface albedo (brightness) accounting for small-scale surface roughness effects. It can be combined with any volume scattering model. The results indicate that surface roughness may decrease the albedo by about 1–3 % in midwinter and even more than 10 % during the late melting season. The effect is largest for low solar zenith angle values and lower bulk snow albedo values.
G. T. Miyoshi, N. N. Imai, A. M. G. Tommaselli, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W12-2020, 49–54, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-49-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-49-2020, 2020
E. Honkavaara, R. Näsi, R. Oliveira, N. Viljanen, J. Suomalainen, E. Khoramshahi, T. Hakala, O. Nevalainen, L. Markelin, M. Vuorinen, V. Kankaanhuhta, P. Lyytikäinen-Saarenmaa, and L. Haataja
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 429–434, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-429-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-429-2020, 2020
J. I. Peltoniemi, M. Gritsevich, J. Markkanen, T. Hakala, J. Suomalainen, N. Zubko, O. Wilkman, and K. Muinonen
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 375–382, https://doi.org/10.5194/isprs-annals-V-1-2020-375-2020, https://doi.org/10.5194/isprs-annals-V-1-2020-375-2020, 2020
A. M. G. Tommaselli, M. B. Campos, L. F. Castanheiro, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W18, 167–171, https://doi.org/10.5194/isprs-archives-XLII-2-W18-167-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W18-167-2019, 2019
A. Berveglieri, A. M. G. Tommaselli, G. Santos, L. D. Santos, and E. Honkavaara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1625–1629, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1625-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1625-2019, 2019
M. Weinmann, R. Müller, R. Reulke, E. Honkavaara, D. Tuia, and S. Keller
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1825–1826, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1825-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1825-2019, 2019
G. T. Miyoshi, N. N. Imai, A. M. G. Tommaselli, and E. Honkavaara
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
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
Marinka E. B. van Puijenbroek, Corjan Nolet, Alma V. de Groot, Juha M. Suomalainen, Michel J. P. M. Riksen, Frank Berendse, and Juul Limpens
Biogeosciences, 14, 5533–5549, https://doi.org/10.5194/bg-14-5533-2017, https://doi.org/10.5194/bg-14-5533-2017, 2017
Short summary
Short summary
Understanding the contribution of the vegetation and dune size to nebkha dune growth could improve model predictions on coastal dune development. We monitored a natural nebkha dune field with a drone with camera. Our results show that dune growth in summer is mainly determined by dune size, whereas in winter dune growth was determined by vegetation. In our study area the growth of exposed dunes was restricted by storm erosion, whereas growth of sheltered dunes was restricted by sand supply.
N. Saarinen, M. Vastaranta, R. Näsi, T. Rosnell, T. Hakala, E. Honkavaara, M. A. Wulder, V. Luoma, A. M. G. Tommaselli, N. N. Imai, E. A. W. Ribeiro, R. B. Guimarães, M. Holopainen, and J. Hyyppä
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 171–175, https://doi.org/10.5194/isprs-archives-XLII-3-W3-171-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-171-2017, 2017
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
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
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
M. H. D. Franceschini, H. Bartholomeus, D. van Apeldoorn, J. Suomalainen, and L. Kooistra
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 109–112, https://doi.org/10.5194/isprs-archives-XLII-2-W6-109-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-109-2017, 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, 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.
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