Water tank and swimming pool detection based on remote sensing and deep learning: Relationship with socioeconomic level and applications in dengue control

This study aims to detect water tanks installed on rooftops and swimming pools in digital images to identify and classify areas based on the socioeconomic index, in order to assist public health programs in the control of diseases linked to the Aedes aegypti mosquito.

Pipeline

The work methodology followed for this work is presented below

Description of the folders

• Dataset: it contains images in extension .jpg with 6000x6000 pixels for the 4 areas of the Campinas, São Paulo, Brazil.
• Pool Detection: it contains scripts for the pool detection
• Water Tank Detection: it contains scripts for the water tank detection
• Utils: it contais useful scripts for this work
• aux_images: it contains images for README

Citation

If you use DL-Aedes in an academic manuscript, please cite:

1. Cunha, H. S., Sclauser, B. S., Wildemberg, P. F., Fernandes, E. A. M., Dos Santos, J. A., Lage, M. D. O., ... & Chiaravalloti-Neto, F. (2021). Water tank and swimming pool detection based on remote sensing and deep learning: Relationship with socioeconomic level and applications in dengue control. PloS one, 16(12), e0258681.
2. Fernandes E, Wildemberg P, dos Santos, J. Water Tanks and Swimming Pools Detection in Satellite Images: Exploiting Shallow and Deep-Based Strategies. In Anais do XVI Workshop de Visão Computacional. 2020; 117-122. Porto Alegre: SBC. doi: 10.5753/wvc.2020.13491.

Convenient BibTeX code:

@article{cunha2021water,
  title={Water tank and swimming pool detection based on remote sensing and deep learning: Relationship with socioeconomic level and applications in dengue control},
  author={Cunha, Higor Souza and Sclauser, Brenda Santana and Wildemberg, Pedro Fonseca and Fernandes, Eduardo Augusto Milit{\~a}o and Dos Santos, Jefersson Alex and Lage, Mariana de Oliveira and Lorenz, Camila and Barbosa, Gerson Laurindo and Quintanilha, Jos{\'e} Alberto and Chiaravalloti-Neto, Francisco},
  journal={PloS one},
  volume={16},
  number={12},
  pages={e0258681},
  year={2021},
  publisher={Public Library of Science San Francisco, CA USA}
}