Bridging the Seismic Vulnerability Data Gap Through UAV and 360° Imagery: The Case of Nejapa, El Salvador

In Latin America, high seismic activity drives countries to develop disaster risk reduction policies based on seismic risk studies. This work demonstrates the feasibility of creating a seismic exposure and vulnerability database using remotely sensed data. In Nejapa, El Salvador, a drone flight and 360° photo capture were conducted to generate a 3D model of the city. Buildings were identified, characterised, and assigned a vulnerability model. This database was used to estimate seismic risk for a simulated Mw 6.7 earthquake on the Guaycume fault near the city. Results show that 71% of buildings would suffer complete damage and 68% of the population would be homeless, with losses exceeding USD 15 million. Findings were shared with relevant institutions in El Salvador through a dashboard. The country is currently collecting the same type of data used in the present study to update its cadastre and census. This is an opportunity to replicate this pilot experience in many other cities across the country and to provide open data access, positioning El Salvador at the forefront of civil protection in the Latin American region.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2025-10-23
DOI
https://doi.org/10.3390/app152111350
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bridging the Seismic Vulnerability Data Gap Through UAV and 360° Imagery: The Case of Nejapa, El Salvador

Jorge M. Gaspar‐Escribano, Joaquín Martín‐Calleja, Sandra Martínez Cuevas, Alejandra Staller et al.
Applied Sciences
Anomaly Detection Techniques and Applications
article

Bridging the Seismic Vulnerability Data Gap Through UAV and 360° Imagery: The Case of Nejapa, El Salvador

Jorge M. Gaspar‐Escribano, Joaquín Martín‐Calleja, Sandra Martínez Cuevas, Alejandra Staller, Yolanda Torres
article en

Abstract

In Latin America, high seismic activity drives countries to develop disaster risk reduction policies based on seismic risk studies. This work demonstrates the feasibility of creating a seismic exposure and vulnerability database using remotely sensed data. In Nejapa, El Salvador, a drone flight and 360° photo capture were conducted to generate a 3D model of the city. Buildings were identified, characterised, and assigned a vulnerability model. This database was used to estimate seismic risk for a simulated Mw 6.7 earthquake on the Guaycume fault near the city. Results show that 71% of buildings would suffer complete damage and 68% of the population would be homeless, with losses exceeding USD 15 million. Findings were shared with relevant institutions in El Salvador through a dashboard. The country is currently collecting the same type of data used in the present study to update its cadastre and census. This is an opportunity to replicate this pilot experience in many other cities across the country and to provide open data access, positioning El Salvador at the forefront of civil protection in the Latin American region.

Applied SciencesVol. 15(21)
Universidad Nueva San Salvador (SV), University of El Salvador (SV), Universidad Politécnica de Madrid (ES)
Openalex Percentile: Top 84%
Anomaly Detection Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Bridging the Seismic Vulnerability Data Gap Through UAV and 360° Imagery: The Case of Nejapa, El Salvador — Jorge M. Gaspar‐Escribano, Joaquín Martín‐Calleja, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS