Background
In March 2024, the municipality of Mimoso do Sul, Espírito Santo, Brazil, faced a devastating natural disaster. Heavy rains in the early hours of March 23 led to severe flooding, resulting in major loss: deaths of people and property damage. Among the hardest-hit areas in the region, Mimoso do Sul experienced the most significant destruction, with 18 out of the 20 confirmed deaths and thousands of homes and businesses submerged.
In response to this crisis, the Jones dos Santos Neves Institute (IJSN) collaborated with the Espírito Santo State Military Fire Brigade (CBMES), the State Civil Protection and Defense Coordination (CEPDEC), and the Operations and Air Transport Center (NOTAER) to assess the damage.
Challenge
The main challenge after the flooding was the unavailability of up-to-date imaging of the area. Dense cloud cover in the region made orbital optical sensors unusable for several days, causing delays in obtaining satellite images.
The first available satellite image, captured by WorldView 3 on April 2, provided imagery of lower resolution than what was needed for detailed damage assessment. This delay and lack of clarity became a significant obstacle to accurately mapping the extent of the flooding and deploying timely rescue efforts.
Solution and Outcome
To overcome this challenge, the IJSN and its partners turned to SPH Engineering’s UAV technology. Luckily, using UgCS drone flight planning software resulted in a rapid solution for capturing geospatial data.
Over two days, the team conducted drone flights that captured approximately 1,200 high-resolution images of the affected areas. These images were used to create an orthophoto—a detailed, georeferenced image of the region—which allowed the team to accurately map the flood's impact on the city.
By integrating these images with data from the Brazilian Institute of Geography and Statistics (IBGE), which provided the locations of households affected by the flood, the team was able to quantify the extent of the damage with precision.
As a result, this initiative delivered significant results. The team identified that 3,989 properties in the city were affected by the flooding, including 2,996 homes, 12 schools, 29 health facilities, 806 businesses, and 29 churches.
Apart from identifying affected areas, the UAV data also helped validate a mathematical model known as HAND (Height Above the Nearest Drainage), which was used to predict the flood extent in other regions and could serve as a preventative tool for future disasters.
Conclusion
Jones dos Santos Neves Institute and its partners using UgCS drone flight planning software in the aftermath of the Mimoso do Sul floods showcase a powerful example of how technology can be leveraged to mitigate the effects of natural disasters.
The detailed mapping and subsequent data analysis facilitated by UgCS have set a new standard for disaster management in the region, offering a replicable model that can be applied to similar events in the future.