Power of GIS Mapping: ATLAS Flood Maps 2022 (Short Paper)

Authors Munazza Usmani , Hafiz Muhammad Tayyab Bhatti, Francesca Bovolo, Maurizio Napolitano



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Author Details

Munazza Usmani
  • University of Trento, Italy
  • Fondazione Bruno Kessler, Trento, Italy
Hafiz Muhammad Tayyab Bhatti
  • University of Punjab, Lahore, Pakistan
Francesca Bovolo
  • Fondazione Bruno Kessler, Trento, Italy
Maurizio Napolitano
  • Fondazione Bruno Kessler, Trento, Italy

Cite AsGet BibTex

Munazza Usmani, Hafiz Muhammad Tayyab Bhatti, Francesca Bovolo, and Maurizio Napolitano. Power of GIS Mapping: ATLAS Flood Maps 2022 (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 75:1-75:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.GIScience.2023.75

Abstract

In this paper, we are introducing an efficient method based on the GIS technology, to design data immediate and analysis-ready mapping from open GIS and remote sensing data, vector and raster data into a single visualization to facilitate fast and flexible mapping, also referred to as ATLAS maps. The Google Earth Engine approach is used to pre-process the satellite data, while ArcGIS software is to integrate all the data layers. Since the ArcGIS software is included as a default dependency in GIS and remote sensing data, the proposed method provides a cross-platform and single-technology solution for handling flood mapping. For now, we conducted flood analysis using the latest open data for Pakistan and Nigeria countries, then elaborated on the advantages of each data for flood mapping with respect to inundated areas, rainfall analysis, and affected populations, health, and education facilities. Given a wide range of tasks that can benefit from the method, future work will extend the methodology to heterogeneous geodata (vector and raster) to support seamless and make it automatic interfaces.

Subject Classification

ACM Subject Classification
  • Information systems → Geographic information systems
Keywords
  • GIS
  • Disaster Mapping
  • Open Data
  • Geospatial Technology
  • Remote Sensing

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References

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