SiDroForest: Orthomosaics, SfM point clouds and products from aerial image data of expedition vegetation plots in 2018 in Central Yakutia and Chukotka, Siberia

This orthomosaics and Structure from Motion (SfM) point clouds dataset is a part of the SiDroForest data collection (van Geffen et al., 2021). The aim of SiDroForest is to gain a clear picture of the current vegetation dynamics in the pan-arctic region of Siberia. The dataset presented here contains...

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Bibliographic Details
Main Authors: Kruse, Stefan, Farkas, Luca, Brieger, Frederic, Geng, Rongwei, Heim, Birgit, Pestryakova, Luidmila A, Zakharov, Evgenii S, Herzschuh, Ulrike, van Geffen, Femke
Format: Dataset
Language:English
Published: PANGAEA 2021
Subjects:
CHM
DEM
DSM
DTM
Online Access:https://doi.pangaea.de/10.1594/PANGAEA.933263
https://doi.org/10.1594/PANGAEA.933263
Description
Summary:This orthomosaics and Structure from Motion (SfM) point clouds dataset is a part of the SiDroForest data collection (van Geffen et al., 2021). The aim of SiDroForest is to gain a clear picture of the current vegetation dynamics in the pan-arctic region of Siberia. The dataset presented here contains orthomosaics and structure from motion (SfM) point clouds and point cloud products for plots visited in Siberia during a 2-month fieldwork expedition in 2018 by the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research in Germany (Kruse et al., 2019). During the fieldwork, 53 vegetation plots were covered by Unmanned Aerial Vehicle (UAV) flights and Red Green Blue (RGB) photographs were taken with a consumer grade DJI Phantom 4 quadcopter and MAPIR Survey3W RGNIR camera with a standardized flight plan (double-gridded in near-nadir position and circular facing the plot center at take-off elevation) on a 50 x 50 m area (further details in Kruse et al., 2019, Brieger et al., 2019). From these UAV images, SfM point clouds and orthoimages were constructed. The UAV data and the products that were constructed are described below. Data Collection Because of the availability of multiple overlapping images from different camera viewpoints, point cloud processing and generation of 3-dimensional (3D) products and successive generation of orthoimages were possible. We manually rejected images that have been taken during take-off and landing, and blurry, under- or overexposed images from further processing. The remaining images were then used to generate the 3D point cloud and related products directly from the point cloud data.