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ZENODO
Software . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Software . 2025
License: CC BY
Data sources: Datacite
ZENODO
Software . 2025
License: CC BY
Data sources: Datacite
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Flood Impact Simulation and Criticality Analysis and rban Traffic and Flood Analysis Scripts in R Software

Authors: García-Ramírez, Yasmany;

Flood Impact Simulation and Criticality Analysis and rban Traffic and Flood Analysis Scripts in R Software

Abstract

Script 1 – Urban Traffic Analysis under Flood ScenariosThis R script provides a comprehensive framework for assessing the impact of floods on urban road networks. It downloads and preprocesses OpenStreetMap (OSM) data, integrates Google Traffic information with field-measured speeds, and applies correction factors to improve accuracy. The program computes and visualizes optimal travel routes under both normal and user-defined flood conditions, incorporating statistical validation through paired t-tests. Outputs include statistical summaries, travel time metrics, and high-resolution maps, offering a robust and data-driven perspective on flood-related traffic disruption. Script 2 – Flood Scenario Simulation and Traffic Flow AnalysisThis advanced R script simulates multiple flood scenarios to evaluate their effects on urban mobility. By combining OSM data with Google and field-based traffic measurements, it identifies critical days and peak congestion periods. The program models three levels of road blockage (100%, 75%, and 50%) and calculates shortest travel paths for each case. Results include comparative indicators such as average travel time and congestion index, as well as visualizations in the form of detailed maps and justification plots. The script is particularly suited for urban planning, risk assessment, and disaster management applications.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average