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.
Power of GIS Mapping: ATLAS Flood Maps 2022 / Usmani, Munazza; Bhatti, Hafiz Muhammad Tayyab; Bovolo, Francesca; Napolitano, Maurizio. - ELETTRONICO. - 277:(2023), p. 75. (Intervento presentato al convegno GIScience 2023 tenutosi a Leeds, UK nel 12th-15th September 2023) [10.4230/LIPIcs.GIScience.2023.75].
Power of GIS Mapping: ATLAS Flood Maps 2022
Usmani, Munazza
Primo
;Bovolo, FrancescaPenultimo
;Napolitano, MaurizioUltimo
2023-01-01
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.File | Dimensione | Formato | |
---|---|---|---|
LIPIcs.GIScience.2023.75.pdf
accesso aperto
Tipologia:
Versione editoriale (Publisher’s layout)
Licenza:
Creative commons
Dimensione
2.86 MB
Formato
Adobe PDF
|
2.86 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione