Evidence map›Paper›PMID 39587111›Full record

ArticleScientific data2024

LiPheStream - A 18-month high spatiotemporal resolution point cloud time series of Boreal trees from Finland.

Samantha Wittke, Mariana Campos, Lassi Ruoppa, Rami Echriti, Yunsheng Wang, Antoni Gołoś, Antero Kukko, Juha Hyyppä, Eetu Puttonen

Abstract read
In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Samantha Wittke *Finnish Geospatial Research Institute in the National Land Survey of Finland, Department of Remote Sensing and Photogrammetry, Espoo, 02150, Finland.
Mariana Campos *Finnish Geospatial Research Institute in the National Land Survey of Finland, Department of Remote Sensing and Photogrammetry, Espoo, 02150, Finland. mariana.campos@maanmittauslaitos.fi.ORCID http://orcid.org/0000-0003-3430-7521
Lassi RuoppaFinnish Geospatial Research Institute in the National Land Survey of Finland, Department of Remote Sensing and Photogrammetry, Espoo, 02150, Finland.ORCID http://orcid.org/0009-0002-4267-572X
Rami EchritiFinnish Geospatial Research Institute in the National Land Survey of Finland, Department of Remote Sensing and Photogrammetry, Espoo, 02150, Finland.
Yunsheng WangFinnish Geospatial Research Institute in the National Land Survey of Finland, Department of Remote Sensing and Photogrammetry, Espoo, 02150, Finland.
Antoni GołośAalto University, Department of Built Environment, Espoo, 02150, Finland.ORCID http://orcid.org/0009-0008-0246-0306
Antero KukkoFinnish Geospatial Research Institute in the National Land Survey of Finland, Department of Remote Sensing and Photogrammetry, Espoo, 02150, Finland.
Juha HyyppäFinnish Geospatial Research Institute in the National Land Survey of Finland, Department of Remote Sensing and Photogrammetry, Espoo, 02150, Finland.ORCID http://orcid.org/0000-0001-5360-4017
Eetu PuttonenFinnish Geospatial Research Institute in the National Land Survey of Finland, Department of Remote Sensing and Photogrammetry, Espoo, 02150, Finland.ORCID http://orcid.org/0000-0003-0985-4443

Funding

Academy of Finland (Suomen Akatemia) 331708Academy of Finland (Suomen Akatemia) 334060Academy of Finland (Suomen Akatemia) 337811Academy of Finland (Suomen Akatemia) 356137Academy of Finland (Suomen Akatemia) 357908Academy of Finland (Suomen Akatemia) 359203
6 · The paper itself

Abstract

In the present paper, we introduce a high-resolution spatiotemporal point cloud time series, acquired using a LiDAR sensor mounted 30 metres above ground on a flux observation tower monitoring a boreal forest. The dataset comprises a 18-month long (April 2020 - September 2021) time series with an average interval of 3.5 days between observations. The data acquisition, transfer, and storage systems established at Hyytiälä (Finland) are named the LiDAR Phenology station (LiPhe). The dataset consists of 103 time points of LiDAR point clouds covering a total of 458 individual trees, comprising three distinct Boreal species. Additional reference information includes the respective location, the species, and the initial height (at the first time point) of each individual tree. The processing scripts are included to outline the workflow used to generate the individual tree point clouds (LiPheKit). The presented dataset offers a comprehensive insight into inter- and intra-species variations of the individual trees regarding their growth strategies, phenological dynamics, and other functioning processes over two growth seasons.

Identifiers

PMID39587111
PMCPMC11589874

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.