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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLIII-B3-2022
https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-691-2022
© 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-B3-2022-691-2022
© 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
USE OF TREE HEIGHT FOR MANGROVE SPECIES CLASSIFICATION
L. Roy
ISEA Laboratory, University of New Caledonia, Nouméa, New Caledonia
C. Marchand
ISEA Laboratory, University of New Caledonia, Nouméa, New Caledonia
T. Landes
University of Strasbourg, CNRS, INSA Strasbourg, ICube Laboratory UMR 7357, Photogrammetry and Geomatics Group, 67000, France
H. Macher
University of Strasbourg, CNRS, INSA Strasbourg, ICube Laboratory UMR 7357, Photogrammetry and Geomatics Group, 67000, France
P. Grussenmeyer
University of Strasbourg, CNRS, INSA Strasbourg, ICube Laboratory UMR 7357, Photogrammetry and Geomatics Group, 67000, France
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A. Murtiyoso, P. Grussenmeyer, and D. Suwardhi
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S. W. Trisyanti, D. Suwardhi, A. Murtiyoso, and P. Grussenmeyer
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Short summary
Short summary
Little is known about how hypoxia influences mangrove fish assemblages. In situ video observations reveal species-specific avoidance strategies in response to developing hypoxia in a mangrove forest. Taxa commonly using mangroves could withstand hypoxia, while others usually associated with reef habitats were not recorded below 70 % saturation. These results suggest that hypoxia is an important factor shaping mangrove fish assemblages and could explain the low species richness usually observed.
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 1083–1087, https://doi.org/10.5194/isprs-archives-XLII-2-W15-1083-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-1083-2019, 2019
H. Macher, M. Boudhaim, P. Grussenmeyer, M. Siroux, and T. Landes
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 719–725, https://doi.org/10.5194/isprs-archives-XLII-2-W15-719-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-719-2019, 2019
A. Murtiyoso and P. Grussenmeyer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 821–827, https://doi.org/10.5194/isprs-archives-XLII-2-W15-821-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-821-2019, 2019
A. Murtiyos, P. Grussenmeyer, D. Suwardhi, W. A. Fadilah, H. A. Permana, and D. Wicaksono
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 829–834, https://doi.org/10.5194/isprs-archives-XLII-2-W15-829-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-829-2019, 2019
V. Girardet, P. Grussenmeyer, O. Reis, J. Kieffer, S. Guillemin, and E. Moisan
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 527–532, https://doi.org/10.5194/isprs-archives-XLII-2-W15-527-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-527-2019, 2019
R. Assi, T. Landes, A. Murtiyoso, and P. Grussenmeyer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 133–138, https://doi.org/10.5194/isprs-archives-XLII-2-W15-133-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-133-2019, 2019
O. Al Khalil and P. Grussenmeyer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 55–62, https://doi.org/10.5194/isprs-archives-XLII-2-W15-55-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-55-2019, 2019
R. Assi, T. Landes, H. Macher, and P. Grussenmeyer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 747–752, https://doi.org/10.5194/isprs-archives-XLII-2-W13-747-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-747-2019, 2019
H. Macher, L. Chow, and S. Fai
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W9, 455–460, https://doi.org/10.5194/isprs-archives-XLII-2-W9-455-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W9-455-2019, 2019
A. Murtiyoso and P. Grussenmeyer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W9, 523–528, https://doi.org/10.5194/isprs-archives-XLII-2-W9-523-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W9-523-2019, 2019
N. Börlin, A. Murtiyoso, P. Grussenmeyer, F. Menna, and E. Nocerino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 133–140, https://doi.org/10.5194/isprs-archives-XLII-2-133-2018, https://doi.org/10.5194/isprs-archives-XLII-2-133-2018, 2018
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 551–558, https://doi.org/10.5194/isprs-archives-XLII-2-551-2018, https://doi.org/10.5194/isprs-archives-XLII-2-551-2018, 2018
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 699–705, https://doi.org/10.5194/isprs-archives-XLII-2-699-2018, https://doi.org/10.5194/isprs-archives-XLII-2-699-2018, 2018
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