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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLII-3
https://doi.org/10.5194/isprs-archives-XLII-3-1305-2018
© 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-3-1305-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
30 Apr 2018
| 30 Apr 2018
OPTIMIZING RADIOMETRIC PROCESSING AND FEATURE EXTRACTION OF DRONE BASED HYPERSPECTRAL FRAME FORMAT IMAGERY FOR ESTIMATION OF YIELD QUANTITY AND QUALITY OF A GRASS SWARD
R. Näsi
National Land Survey of Finland, Finnish Geospatial Research Institute FGI, FI-00521 Helsinki, Finland
N. Viljanen
National Land Survey of Finland, Finnish Geospatial Research Institute FGI, FI-00521 Helsinki, Finland
R. Oliveira
National Land Survey of Finland, Finnish Geospatial Research Institute FGI, FI-00521 Helsinki, Finland
J. Kaivosoja
Natural Resources Institute Finland - LUKE, Latokartanonkaari 9, FI-00790 Helsinki, Finland
O. Niemeläinen
Natural Resources Institute Finland - LUKE, Latokartanonkaari 9, FI-00790 Helsinki, Finland
T. Hakala
National Land Survey of Finland, Finnish Geospatial Research Institute FGI, FI-00521 Helsinki, Finland
L. Markelin
National Land Survey of Finland, Finnish Geospatial Research Institute FGI, FI-00521 Helsinki, Finland
S. Nezami
National Land Survey of Finland, Finnish Geospatial Research Institute FGI, FI-00521 Helsinki, Finland
J. Suomalainen
National Land Survey of Finland, Finnish Geospatial Research Institute FGI, FI-00521 Helsinki, Finland
E. Honkavaara
National Land Survey of Finland, Finnish Geospatial Research Institute FGI, FI-00521 Helsinki, Finland
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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.
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M. Weinmann, R. Müller, R. Reulke, E. Honkavaara, D. Tuia, and S. Keller
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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
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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
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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.
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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.
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