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Keywords = Culuene rapids

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8 pages, 6150 KiB  
Data Descriptor
UAV-Based 3D Point Clouds of Freshwater Fish Habitats, Xingu River Basin, Brazil
by Margaret Kalacska, Oliver Lucanus, Leandro Sousa, Thiago Vieira and Juan Pablo Arroyo-Mora
Data 2019, 4(1), 9; https://doi.org/10.3390/data4010009 - 10 Jan 2019
Cited by 5 | Viewed by 4984
Abstract
Dense 3D point clouds were generated from Structure-from-Motion Multiview Stereo (SFM-MVS) photogrammetry for five representative freshwater fish habitats in the Xingu river basin, Brazil. The models were constructed from Unmanned Aerial Vehicle (UAV) photographs collected in 2016 and 2017. The Xingu River is [...] Read more.
Dense 3D point clouds were generated from Structure-from-Motion Multiview Stereo (SFM-MVS) photogrammetry for five representative freshwater fish habitats in the Xingu river basin, Brazil. The models were constructed from Unmanned Aerial Vehicle (UAV) photographs collected in 2016 and 2017. The Xingu River is one of the primary tributaries of the Amazon River. It is known for its exceptionally high aquatic biodiversity. The dense 3D point clouds were generated in the dry season when large areas of aquatic substrate are exposed due to the low water level. The point clouds were generated at ground sampling distances of 1.20–2.38 cm. These data are useful for studying the habitat characteristics and complexity of several fish species in a spatially explicit manner, such as calculation of metrics including rugosity and the Minkowski–Bouligand fractal dimension (3D complexity). From these dense 3D point clouds, substrate complexity can be determined more comprehensively than from conventional arbitrary cross sections. Full article
(This article belongs to the Special Issue Open Data and Robust & Reliable GIScience)
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