Evidence map›Paper›PMID 41684884›Full record

ArticleData in brief2026

UAV-LiDAR dataset of Pangandaran coastal tourism hotspots for tsunami and climate risk valuation and exposure mapping.

Mega Laksmini Syamsuddin, Umar Abdurrahman, Ajeng Riska Puspita, Sunarto, Qurnia Wulan Sari, Fadli Syamsudin, Indrawan Fadhil Pratyaksa, Iqbal Maulana Cipta, Ivonne Milichristi Radjawane, Hansan Park

Abstract read
In one paragraph

Article in Data in brief, 2026. 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

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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

10 authors.

Mega Laksmini SyamsuddinDepartment of Marine, Faculty of Fisheries and Marine Sciences, Universitas Padjadjaran, 45363 Jatinangor, West Java, Indonesia.
Umar AbdurrahmanDepartment of Marine, Faculty of Fisheries and Marine Sciences, Universitas Padjadjaran, 45363 Jatinangor, West Java, Indonesia.
Ajeng Riska PuspitaMaster of Marine Conservation Study Program, Faculty of Fisheries and Marine Sciences, Universitas Padjadjaran, 45363 Jatinangor, West Java, Indonesia.
SunartoDepartment of Marine, Faculty of Fisheries and Marine Sciences, Universitas Padjadjaran, 45363 Jatinangor, West Java, Indonesia.
Qurnia Wulan SariDepartment of Marine, Faculty of Fisheries and Marine Sciences, Universitas Padjadjaran, 45363 Jatinangor, West Java, Indonesia.
Fadli SyamsudinCenter of Climate and Maritime Regional Management, Faculty of Fisheries and Marine Sciences, Universitas Padjadjaran, 45363 Jatinangor, West Java, Indonesia.
Indrawan Fadhil PratyaksaKorea-Indonesia Marine Technology Cooperation Research Center, Cirebon Center, West Java 45611, Indonesia.
Iqbal Maulana CiptaKorea-Indonesia Marine Technology Cooperation Research Center, Cirebon Center, West Java 45611, Indonesia.
Ivonne Milichristi RadjawaneKorea-Indonesia Marine Technology Cooperation Research Center, Cirebon Center, West Java 45611, Indonesia.
Hansan ParkKorea-Indonesia Marine Technology Cooperation Research Center, Cirebon Center, West Java 45611, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article presents a high-resolution UAV-LiDAR dataset acquired over the main coastal tourism hotspots of Pangandaran, West Java, Indonesia (WGS84 / UTM Zone 49S). The survey was conducted using a DJI Matrice 300 RTK equipped with a CHCNAV AA450 LiDAR system at altitudes of 77-83 m AGL, following grid-based flight lines with 80% forward and 70% side overlap. The final point cloud, delivered in LAS format, exhibits a mean density of approximately 865 pts/m², with dominant values of 600-800 pts/m² across roads, roofs, and open terrain, and localized peaks exceeding 3,000 pts/m² in areas of flight-line overlap. Ground control was established using three static base stations, with 14 calibration control points and 8 independent validation check points. Accuracy assessment yields RMSE values of 0.072 m (Easting), 0.062 m (Northing), and 0.138 m (Elevation), with corresponding mean biases of 0.017 m, 0.017 m, and 0.044 m, confirming centimeter-level positional precision suitable for detailed coastal mapping. The dataset includes DSM and DTM derivatives, block-based tiles, metadata, and processing reports, supporting its use in tsunami exposure assessment, climate-risk valuation, urban coastal planning, and remote-sensing education. As one of the first openly accessible UAV-LiDAR datasets for an Indonesian coastal tourism hotspot, it provides a reproducible, high-density 3D resource for research, hazard analysis, and sustainable coastal development.

Indexed as

High-resolution coastal mappingLiDARTourism hotspotUnmanned aerial vehicle

Identifiers

PMID41684884
PMCPMC12891782

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LicenceCC BY-NC
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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.