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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-2-2024-301-2024
© 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-2-2024-301-2024
© 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
Development of a Precise Tree Structure from LiDAR Point Clouds
Abdul Nurunnabi
Geodesy and Geospatial Engineering, Faculty of Science, Technology and Medicine, University of Luxembourg, Luxembourg
Institute for Advanced Studies, University of Luxembourg, Luxembourg
Felicia Teferle
Geodesy and Geospatial Engineering, Faculty of Science, Technology and Medicine, University of Luxembourg, Luxembourg
Debra F. Laefer
Center for Urban Science + Progress; Department of Civil and Urban Engineering, Tandon School of Engineering, New York University, NY, USA
Meida Chen
Institute for Creative Technologies, University of Southern California, Los Angeles, CA 90094, USA
Mir Masoom Ali
Department of Mathematical Sciences, Ball State University, Muncie, IN 47306, USA
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A. V. Vo, N. Chauhan, D. F. Laefer, and M. Bertolotto
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A. Nurunnabi, Y. Sadahiro, and R. Lindenbergh
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Anna Klos, Addisu Hunegnaw, Felix Norman Teferle, Kibrom Ebuy Abraha, Furqan Ahmed, and Janusz Bogusz
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-385, https://doi.org/10.5194/amt-2016-385, 2016
Revised manuscript not accepted
Short summary
Short summary
GPS can remotely sense integrated atmospheric water vapour and in-doing so improve e.g. the accuracy of assimilated numerical weather models. Specially, GPS is well suited in the study of the atmospheric conditions since it is increasingly deployed ever widely around the globe. In this research, we used trend estimates of Zenith Total Delay series and provide a most recent picture of trend and their uncertainties which are used widely to interpret a change in climate.
Tzvetan Simeonov, Dmitry Sidorov, Felix Norman Teferle, Georgi Milev, and Guergana Guerova
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-152, https://doi.org/10.5194/amt-2016-152, 2016
Revised manuscript not accepted
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