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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLVIII-3-2024
https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-57-2024
© 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-3-2024-57-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
07 Nov 2024
| 07 Nov 2024
Experimental assessment of IMU data processing techniques for a backpack mobile laser scanning system
Letícia F. Castanheiro
Department of Cartography, São Paulo State University (UNESP) at Presidente Prudente, São Paulo, Brazil
Antonio M. G. Tommaselli
Department of Cartography, São Paulo State University (UNESP) at Presidente Prudente, São Paulo, Brazil
Heikki Hyyti
Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute (FGI), National Land Survey of Finland, Espoo, Finland
Antero Kukko
Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute (FGI), National Land Survey of Finland, Espoo, Finland
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Short summary
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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.
L. F. Castanheiro, A. M. G. Tommaselli, M. B. Campos, A. Berveglieri, and G. Santos
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W12-2020, 7–12, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-7-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-7-2020, 2020
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
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 389–396, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-389-2020, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-389-2020, 2020
A. Kukko, H. Kaartinen, G. Osinski, and J. Hyyppä
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 749–756, https://doi.org/10.5194/isprs-annals-V-2-2020-749-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-749-2020, 2020
C. Sothe, L. E. C. la Rosa, C. M. de Almeida, A. Gonsamo, M. B. Schimalski, J. D. B. Castro, R. Q. Feitosa, M. Dalponte, C. L. Lima, V. Liesenberg, G. T. Miyoshi, and A. M. G. Tommaselli
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 193–199, https://doi.org/10.5194/isprs-annals-V-3-2020-193-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-193-2020, 2020
A. Berveglieri, A. M. G. Tommaselli, and L. D. Santos
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W18, 7–12, https://doi.org/10.5194/isprs-archives-XLII-2-W18-7-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W18-7-2019, 2019
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
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
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
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
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The Cryosphere, 12, 1461–1478, https://doi.org/10.5194/tc-12-1461-2018, https://doi.org/10.5194/tc-12-1461-2018, 2018
Short summary
Short summary
Water accumulated at the base of ice sheets is the main driver of glacier acceleration and loss of ice mass in Arctic regions. Previously glaciated landscapes sculpted by this water carry information about how ice sheets collapse and ultimately disappear. The search for these landscapes took us to the high Arctic, to explore channels that formed under kilometers of ice during the last ice age. In this work we describe how subglacial channels look and how they helped to drain an ice sheet.
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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.
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
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
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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
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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
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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
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
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
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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