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. 2024 Jan 29:53:110108.
doi: 10.1016/j.dib.2024.110108. eCollection 2024 Apr.

Terrestrial LiDAR point cloud dataset of cocoa trees grown in agroforestry systems in Cameroon

Emilie Peynaud  1 , Stéphane Momo Takoudjou  2   3
Affiliations

Terrestrial LiDAR point cloud dataset of cocoa trees grown in agroforestry systems in Cameroon

Emilie Peynaud et al. Data Brief. .

Abstract

This paper presents a dataset aimed at characterizing cocoa trees cultivated within complex agroforestry systems managed by smallholder farmers in the Central region of Cameroon. The dataset highlights the architectural structure of the trees as well as the distribution of their leaves and wood using 3D point clouds obtained through the Leica ScanStation C10 terrestrial LiDAR. The data collection campaign was conducted in August 2019 in the district of Bokito (latitude 4°34' N and longitude 11°07' E), specifically within the village of Yorro located in a transition zone between forest and savannah. The dataset includes information on 55 cocoa trees, spread over five distinct architectural types. These trees were sampled from various age stands ranging from 5- to 70-year-old. For 29 of these trees, a leaf/wood segmentation of the point clouds was performed. For each of these trees, the dataset comprises the raw point cloud of the entire tree, as well as separate point clouds for the leaves and wood, each in two distinct sets of 3D points. The data provides the foundation for conducting numerous cocoa tree measurements based on their representation in point clouds, allowing for a more comprehensive understanding of their architecture, photosynthetic capacity, and distribution of above-ground biomass.

Keywords: Agroecological forestry; Biomass; Leaf/wood segmentation; LiDAR; Theobroma; Tree architecture.

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Figures

Fig. 1
Fig. 1
Satellite view of different sampling units in Yorro village where the LiDAR data have been taken. Remark: the data collected at sampling unit 5 was discarded from the dataset. Credit: Stéphane Momo Takoudjou.
Fig. 2:
Fig. 2
Scanning a cocoa based agroforestry system in Cameroon. The scanner is in the background (in grey and green). One of the spherical targets used to adjust the successive scan positions is in the left foreground. Credit: Stéphane Momo Takoudjou.
Fig. 3
Fig. 3
The scanning positions in a plot according to the pathway method. Credit: Stéphane Momo Takoudjou.
Fig. 4:
Fig. 4
Configuration of the scan station and the two targets for one position of the pathway. The pathway method consists in scanning the trees from different positions. The successive positions form a path through the plot. Target 1 and 2 materialize respectively the previous and the next scan station positions. Credit: Emilie Peynaud.
Fig. 5:
Fig. 5
Raw point clouds of cocoa trees of types 0 to 4 according to the classification of . Credit: Stéphane Momo Takoudjou.
Fig. 6:
Fig. 6
Leaf/wood segmentation. From left to right: raw point cloud of an entire coco tree, point cloud of the woody part of the tree, point cloud of the leafy part of the tree. Credit: Stéphane Momo Takoudjou.
See this image and copyright information in PMC

References

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