Aluizio Brito Maia
@inpe.br
Masters Student - Remote Sensing
National Institute for Space Research
Master's student in Remote Sensing at the National Institute for Space Research (INPE), where he conducts research related to the detection of flooded areas in cloud-covered images using optical sensors, integrating attributes extracted from digital elevation models and cloud/shadow detection techniques. He holds a Bachelor's degree in Geography from the Federal University of Minas Gerais - UFMG (2022). During his undergraduate studies, he gained experience in research focused on Remote Sensing, geotechnologies, Cartography, and Disaster Risk Management.
EDUCATION
Geography Degree - Federal University of Minas Gerais (UFMG) 2019-2022
Remote Sensing Masters Student - National Instiute for Space Research (INPE) 2023-2025
RESEARCH, TEACHING, or OTHER INTERESTS
Geophysics, Earth and Planetary Sciences, Computers in Earth Sciences, Space and Planetary Science
FUTURE PROJECTS
Detection of Flooded Areas Under Cloud Cover Conditions: Integration with Digital Elevation Models
Floods are hydrological processes directly associated with precipitation characteristics (intensity, frequency, and spatial distribution) and the geomorphometric features of the river basins where they occur. The detection of flooded areas using orbital images through remote sensing techniques requires robust models aimed at accurately identifying surface water. However, certain challenges hinder their detection. In optical sensors, the issue of cloud cover stands out, which leads to omission and inclusion errors of shadows during the image classification process. Several studies have analyzed the potential of image processing techniques for rapid disaster response, particularly for detecting flooded areas. However, few of these methods explore ways to extract information from cloud-covered images by integrating data of different natures. In this context, this dissertation proposes to develop a method for detecting flooded areas in images partially covered by clouds.
Applications Invited
Scopus Publications
Scopus Publications
Ítalo Rafael Costa de Mira, Aluizio Brito Maia, Antônio Miguel Vieira Monteiro, Leonardo Bacelar Lima Santos, and Camilo Daleles Rennó
Wiley
ABSTRACT Understanding the occurrence of urban floods and their conditioning factors is essential for effective management of urban watersheds. However, few studies have explored the spatial variability of these factors in detail. This study investigates the spatial relationships between conditioning factors and flood occurrences in the Tamanduateí River Basin, São Paulo, Brazil. Multi‐source geospatial data were integrated to analyze spatial patterns using kernel density estimation, spatial autocorrelation, and geographically weighted regression at multiple scales. The results reveal strong spatial dependence and highlight the combined influence of environmental factors on flood susceptibility. Flatter, highly urbanized areas exhibited the greatest concentration of flood hotspots, confirming the importance of local topographic control. These findings contribute to a better understanding of spatial heterogeneity in urban flood dynamics and provide a replicable methodological framework for identifying high‐risk areas, supporting more precise and spatially informed mitigation and adaptation strategies in rapidly urbanizing regions.
Aluizio Brito Maia, Camilo Daleles Rennó, Evlyn Márcia Leão de Moraes Novo, and Ítalo Rafael Costa de Mira
Institute of Electrical and Electronics Engineers (IEEE)