The Geological Survey of Brazil (SGB) has, among its institutional responsibilities, the development of studies aimed at territorial planning, directly related to the country’s geological and geomorphological characteristics. In this context, municipal susceptibility maps for landslides and floods stand out as essential tools for identifying areas prone to natural disasters and supporting risk management.
This work presents a case study describing the implementation of an integrated workflow for the production of these maps, covering stages from the preliminary identification of susceptible areas to field validation and final cartographic outputs. The proposed workflow uses QGIS for office-based activities and QField for field data collection and validation, with data storage and integration through GeoPackage and a PostGIS database.
The research emphasizes the transition from traditional processes—often manual and reliant on proprietary solutions—to an automated model based on free and open-source geospatial tools (FOSS4G). The main objective is to optimize the cost–quality–time balance in the production of cartographic products for geological risk management.
Key methodological innovations include the customization of editable layers in QGIS, using intelligent forms based on Qt widgets, standardization of typologies, and the implementation of automated calculations through virtual layers. These features enable field operators to obtain derived information in real time without the need for auxiliary instruments. Additionally, the use of triggers in the PostGIS database automates the population of spatial attributes, such as municipality and state, after synchronization of collected data. Each record is assigned a UUID, ensuring data integrity and traceability in a decentralized data collection environment.
The adoption of this integrated workflow resulted in an estimated productivity gain of approximately 67%, while also significantly improving the standardization of final products. The incorporation of these routines directly into QField enabled greater consistency in field surveys and data structuring, resulting in more reliable and comparable cartographic outputs.
The results demonstrate that the combined use of QGIS and QField not only accelerates the production of susceptibility maps but also enhances their technical quality and standardization. This methodological advancement has enabled SGB to increase the number of published maps with greater efficiency and reliability.
Finally, the adoption of integrated open-source platforms represents a strategic advancement in natural disaster prevention projects, directly contributing to the generation of critical information for population protection and risk reduction, with a direct impact on saving lives and promoting sustainable territorial planning.