Evidence map›Paper›PMID 29943069›Full record

ArticleCarbon balance and management2018

Estimating urban above ground biomass with multi-scale LiDAR.

Phil Wilkes, Mathias Disney, Matheus Boni Vicari, Kim Calders, Andrew Burt

Abstract read
In one paragraph

Article in Carbon balance and management, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
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  4. Article
  5. Urban tree carbon density and COEnvironmental monitoring and assessment · 2021
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  9. Article
  10. An architectural understanding of natural sway frequencies in trees.Journal of the Royal Society, Interface · 2019
    Article
  11. 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

5 authors.

Phil WilkesDepartment of Geography, University College London, Gower Street, London, WC1E 6BT, UK. p.wilkes@ucl.ac.uk.ORCID http://orcid.org/0000-0001-6048-536X
Mathias DisneyDepartment of Geography, University College London, Gower Street, London, WC1E 6BT, UK.
Matheus Boni VicariDepartment of Geography, University College London, Gower Street, London, WC1E 6BT, UK.
Kim CaldersDepartment of Geography, University College London, Gower Street, London, WC1E 6BT, UK.
Andrew BurtDepartment of Geography, University College London, Gower Street, London, WC1E 6BT, UK.

Funding

Horizon2020 640176Metrology for Earth Observation and Climate ENV55National Council of Technological and Scientific Development 233849/2014-9Natural Environment Research Council (GB) NE/K002554/1Natural Environment Research Council (GB) NE/N00373X/1Natural Environment Research Council (GB) NE/P011780/1
6 · The paper itself

Abstract

backgroundUrban trees have long been valued for providing ecosystem services (mitigation of the "heat island" effect, suppression of air pollution, etc.); more recently the potential of urban forests to store significant above ground biomass (AGB) has also be recognised. However, urban areas pose particular challenges when assessing AGB due to plasticity of tree form, high species diversity as well as heterogeneous and complex land cover. Remote sensing, in particular light detection and ranging (LiDAR), provide a unique opportunity to assess urban AGB by directly measuring tree structure. In this study, terrestrial LiDAR measurements were used to derive new allometry for the London Borough of Camden, that incorporates the wide range of tree structures typical of an urban setting. Using a wall-to-wall airborne LiDAR dataset, individual trees were then identified across the Borough with a new individual tree detection (ITD) method. The new allometry was subsequently applied to the identified trees, generating a Borough-wide estimate of AGB.

resultsCamden has an estimated median AGB density of 51.6 Mg ha

conclusionOver the coming century global populations are predicted to become increasingly urbanised, leading to an unprecedented expansion of urban land cover. Urban areas will become more important as carbon sinks and effective tools to assess carbon densities in these areas are therefore required. Using multi-scale LiDAR presents an opportunity to achieve this, providing a spatially explicit map of urban forest structure and AGB.

Indexed as

Above ground biomassAirborne LiDARAllometryTerrestrial LiDARUrban forest

Identifiers

PMID29943069
PMCPMC6020103

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.