Data · dataset · 2026
Multiplatform laser scanning point clouds of subtropical forests: A case study of major tree species in Gaofeng Forest Farm, Guangxi
Listed in ScienceDB
Subtropical forests are characterized by complex species composition, diverse vertical structures, and strong spatial heterogeneity.
Description
Detailed characterization of their three-dimensional (3D) structures is essential for forest resource surveys, structural parameter estimation, and ecosystem assessment. Laser scanning technology can rapidly acquire high-precision 3D spatial information.
It therefore provides important support for the digital representation of forest structures. However, most publicly available forest laser scanning datasets focus on temperate forests. Multi-platform and multi-scale laser scanning datasets that capture the complex structures of subtropical forests remain limited.This dataset was developed in a typical subtropical plantation forest at Gaofeng Forest Farm, Guangxi, China.
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It integrates point cloud data from airborne laser scanning (ALS), unmanned aerial vehicle laser scanning (ULS), and terrestrial laser scanning (TLS). The dataset contains 25 standardized forest plots. The plots cover three major tree species: Eucalyptus spp., Chinese fir (Cunninghamia lanceolata), and Masson pine (Pinus massoniana).
The dataset provides laser scanning point clouds acquired at different observation scales. It also includes corresponding field survey data, such as plot location, individual tree position, diameter at breast height (DBH), tree height, height to crown base, and crown width.This dataset integrates 3D forest observations from different platforms, viewing perspectives, and spatial resolutions. It can support research on multi-platform laser scanning data fusion, individual tree structure analysis, and forest parameter estimation.
The dataset also provides a benchmark data resource for laser scanning applications in digital forest surveys of subtropical forests.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00232.0000x ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Geomatic engineering 72%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00232.0000x | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4013 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (72%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |