Data · dataset · 2024
Cocoa tree point clouds obtained by terrestrial Lidar scanning in agroforestry systems in Cameroon
Listed in DataSuds
This data set concerns a total of 55 cocoa trees grown in cocoa based agroforestry systems from Central region of Cameroon.
Description
The data collection campaign was carried out in the district of Bokito (4°34 latitude N and 11°07 longitude E), in the village of Yorro located in a forest-savannah transition zone. The cocoa trees of this data set belong to five different architectural types [Jagoret et al 2017].
The cocoa trees has been sampled in 5 different plots (in 4 different sites) of ages ranging from 5 to 70 year old. The data set consists in Terrestrial Lidar scanning data acquired using a Leica C10 scan station. For each tree, the data set contains the point cloud of the whole tree.
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There are also the point clouds of the leaves and the point clouds of the wood for 29 of the trees for which the leaf/wood segmentation has been done using the LeWoS software [Di Wang et al 2018]. From all those point clouds, many in silico measurements of the trees can be done to better characterize their architecture, their photosynthetic capacity and the biomass distribution. The scans have been done from the 27th to the 30th of August in 2019.
Links
Where it is published
- Dataverse dataset page dataverse.ird.fr/dataset.xhtml?persistentId=doi%3A10.18167%2FDVN1%2F5HZB1F ↗
landing page · from dataverse ird fr
- DOI doi.org/10.18167/dvn1/5hzb1f ↗
DOI / persistent id · from dataverse ird fr
Catalogue records · 1
- Dataverse API dataverse.ird.fr/api/datasets/:persistentId/?persistentId=doi%3A10.18167%2FDVN1… ↗
metadata API · from dataverse ird fr
Topics
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataSuds | doi:10.18167/DVN1/5HZB1F | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:field:401304 | mapping · dataverse ird fr | vocabulary-mapper@1.0.0 | keywords['remote sensing'] |
| concepts[field].local:field:earth-environmental | mapping · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | /subjects |
| concepts[field].local:field:mathematics-statistics | mapping · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | /subjects |
| concepts[modality].local:modality:remote-sensing | mapping · dataverse ird fr | vocabulary-mapper@1.0.0 | keywords['remote sensing'] |
| created_date | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | |
| description | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | /description |
| publication_date | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | |
| title | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | /name |
| updated_date | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 |