1. A multimodal framework for extraction and fusion of satellite images and public health data.
- Author
-
Moukheiber, Dana, Restrepo, David, Cajas, Sebastián Andrés, Montoya, María Patricia Arbeláez, Celi, Leo Anthony, Kuo, Kuan-Ting, López, Diego M., Moukheiber, Lama, Moukheiber, Mira, Moukheiber, Sulaiman, Osorio-Valencia, Juan Sebastian, Purkayastha, Saptarshi, Paddo, Atika Rahman, Wu, Chenwei, and Kuo, Po-Chih
- Subjects
REMOTE-sensing images ,IMAGE analysis ,PUBLIC health ,IMAGE fusion ,MIDDLE-income countries ,METADATA ,ACQUISITION of data ,RIGHT to education - Abstract
In low- and middle-income countries, the substantial costs associated with traditional data collection pose an obstacle to facilitating decision-making in the field of public health. Satellite imagery offers a potential solution, but the image extraction and analysis can be costly and requires specialized expertise. We introduce SatelliteBench, a scalable framework for satellite image extraction and vector embeddings generation. We also propose a novel multimodal fusion pipeline that utilizes a series of satellite imagery and metadata. The framework was evaluated generating a dataset with a collection of 12,636 images and embeddings accompanied by comprehensive metadata, from 81 municipalities in Colombia between 2016 and 2018. The dataset was then evaluated in 3 tasks: including dengue case prediction, poverty assessment, and access to education. The performance showcases the versatility and practicality of SatelliteBench, offering a reproducible, accessible and open tool to enhance decision-making in public health. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF