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Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
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Related Experiment Video

Updated: Jan 16, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
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Mapping flood susceptibility using Random Forest exploiting satellite observations and geomorphic features.

Jorge Saavedra Navarro1, Ruodan Zhuang1, Cinzia Albertini1

  • 1Department of Civil, Construction and Environmental Engineering (DICEA), University of Naples Federico II, Naples, Italy.

The Science of the Total Environment
|September 25, 2025
PubMed
Summary

This study enhances flood susceptibility mapping in Italy using the Random Forest model and 26 flood conditioning factors. The best model, incorporating Geomorphic Flood Index, improved accuracy, aiding risk management.

Keywords:
Flood conditioning factorsFlood susceptibilityGeomorphic Flood IndexRandom ForestSatellite observations

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Area of Science:

  • Environmental Science
  • Geosciences
  • Data Science

Background:

  • Flood events pose significant destructive risks, necessitating effective risk management strategies.
  • Accurate flood susceptibility mapping is crucial for societal and environmental protection.

Purpose of the Study:

  • To assess flood susceptibility in Italy using the Random Forest (RF) model.
  • To evaluate the effectiveness of 26 flood conditioning factors (FCFs) and identify optimal predictor sets.
  • To improve the accuracy and efficiency of flood-prone area identification.

Main Methods:

  • Employed the Random Forest (RF) model for flood susceptibility assessment.
  • Utilized Average Merit of Information (AMI) to maximize FCF information and Pearson correlation/VIF to address collinearity.
  • Calibrated the model with satellite observations and historical flood records; evaluated eleven factor sets (SoFs) against official maps.

Main Results:

  • The RF model trained with SoF-1 (including mean maximum daily precipitation, Geomorphic Flood Index (GFI), distance from river, elevation, lithology, soil, NDVI, land cover) showed superior generalization.
  • Inclusion of GFI significantly enhanced prediction accuracy, particularly in previously unmapped areas.
  • Challenges remain in predicting susceptibility in flat terrains and data-scarce regions.

Conclusions:

  • Integrating satellite data, complementary datasets, and optimized predictors (like GFI) improves flood susceptibility mapping accuracy.
  • The developed approach streamlines computational processes for preliminary analysis.
  • Findings provide valuable insights for decision-makers in flood risk management.