Evidence map›Paper›PMID 37300059›Full record

ReviewSensors (Basel, Switzerland)2023

Review of Shoreline Extraction Methods from Aerial Laser Scanning.

Andrzej Stateczny, Armin Halicki, Mariusz Specht, Cezary Specht, Oktawia Lewicka

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Andrzej StatecznyDepartment of Geodesy, Gdańsk University of Technology, Gabriela Narutowicza 11-12, 80-233 Gdańsk, Poland.ORCID 0000-0002-4671-6827
Armin HalickiMarine Technology Ltd., Wiktora Roszczynialskiego 4-6, 81-521 Gdynia, Poland.
Mariusz SpechtMarine Technology Ltd., Wiktora Roszczynialskiego 4-6, 81-521 Gdynia, Poland.ORCID 0000-0002-6026-306X
Cezary SpechtDepartment of Geodesy and Oceanography, Gdynia Maritime University, Morska 81-87, 81-225 Gdynia, Poland.ORCID 0000-0001-5631-6969
Oktawia LewickaDepartment of Geodesy and Oceanography, Gdynia Maritime University, Morska 81-87, 81-225 Gdynia, Poland.ORCID 0000-0002-0382-2793

Funding

Gdynia Maritime University WN/2023/PZ/05National Centre for Research and Development in Poland LIDER/10/0030/L-11/19/NCBR/2020
6 · The paper itself

Abstract

Autonomous technologies are increasingly used in various areas of science. The use of unmanned vehicles for hydrographic surveys in shallow coastal areas requires accurate estimation of shoreline position. This is a nontrivial task, which can be performed using a wide range of sensors and methods. The aim of the publication is to review shoreline extraction methods based solely on data from aerial laser scanning (ALS). This narrative review discusses and critically analyses seven publications drawn up in the last ten years. The discussed papers employed nine different shoreline extraction methods based on aerial light detection and ranging (LiDAR) data. It should be noted that unambiguous evaluation of shoreline extraction methods is difficult or impossible. This is because not all of the methods reported achieved accuracy, the methods were assessed on different datasets, the measurements were conducted using different devices, the water areas differed in geometrical and optical properties, the shorelines had different geometries, and the extent of anthropogenic transformation. The methods proposed by the authors were compared with a wide range of reference methods.

Indexed as

aerial laser scanning (ALS)light detection and ranging (LiDAR)shoreline detectionshoreline extraction

Identifiers

PMID37300059
PMCPMC10255956

What OpenQuestion holds

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LicenceCC BY
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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.