Evidence map›Paper›PMID 33501565›Full record

ArticleEnvironmental monitoring and assessment2021

New tools for old problems - comparing drone- and field-based assessments of a problematic plant species.

Jens Oldeland, Rasmus Revermann, Jona Luther-Mosebach, Tillmann Buttschardt, Jan R K Lehmann

Abstract read
In one paragraph

Article in Environmental monitoring and assessment, 2021. 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

5 authors.

Jens OldelandInsitute of Plant Sciences and Microbiology, University of Hamburg, Ohnhorststr. 18, 22609, Hamburg, Germany. jens.oldeland@uni-hamburg.de.ORCID http://orcid.org/0000-0002-7833-4903
Rasmus RevermannNetzwerk für Angewandte Ökologie, Hamburg, Germany.ORCID https://orcid.org/0000-0002-7044-768X
Jona Luther-MosebachNetzwerk für Angewandte Ökologie, Hamburg, Germany.
Tillmann ButtschardtInstitute of Landscape Ecology, University of Münster, Münster, Germany.ORCID https://orcid.org/0000-0002-2453-4141
Jan R K LehmannInstitute of Landscape Ecology, University of Münster, Münster, Germany.ORCID https://orcid.org/0000-0002-4790-4942

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plant species that negatively affect their environment by encroachment require constant management and monitoring through field surveys. Drones have been suggested to support field surveyors allowing more accurate mapping with just-in-time aerial imagery. Furthermore, object-based image analysis tools could increase the accuracy of species maps. However, only few studies compare species distribution maps resulting from traditional field surveys and object-based image analysis using drone imagery. We acquired drone imagery for a saltmarsh area (18 ha) on the Hallig Nordstrandischmoor (Germany) with patches of Elymus athericus, a tall grass which encroaches higher parts of saltmarshes. A field survey was conducted afterwards using the drone orthoimagery as a baseline. We used object-based image analysis (OBIA) to segment CIR imagery into polygons which were classified into eight land cover classes. Finally, we compared polygons of the field-based and OBIA-based maps visually and for location, area, and overlap before and after post-processing. OBIA-based classification yielded good results (kappa = 0.937) and agreed in general with the field-based maps (field = 6.29 ha, drone = 6.22 ha with E. athericus dominance). Post-processing revealed 0.31 ha of misclassified polygons, which were often related to water runnels or shadows, leaving 5.91 ha of E. athericus cover. Overlap of both polygon maps was only 70% resulting from many small patches identified where E. athericus was absent. In sum, drones can greatly support field surveys in monitoring of plant species by allowing for accurate species maps and just-in-time captured very-high-resolution imagery.

Indexed as

Environmental MonitoringPoaceaeGermanyImage Processing, Computer-AssistedElymus athericusHalligNature conservationNordstrandischmoorOBIASalt marshUAVVegetation mapping

Identifiers

PMID33501565
PMCPMC7838141

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Registered trials

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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.