Description
Carlos Mougan y Sunayana Ghosh nos presentan "Creating a well-being data layer using machine learning, satellite imagery and ground-truth data"
Resumen:
Conducting economic surveys requires huge resources; thus, modern means of acquiring this information using publicly available data and open source technologies create the possibilities of replacing current processes. Satellite images can act as a proxy for existing data collection techniques such as surveys and census to predict the economic well-being of a region. The aim of the project is to build on a prototype that was created using Census data and LandSat data for India. In the next iteration, opportunities for Demographic Health Surveys, Open Street Map, Sentinel and nightlight data will be explored. The initial prototype created a model that had an accuracy of almost 70 percent. The aim is to create a model for India that can be adapted and scaled to other countries.
---
La novena edición de la PyConES se celebra como un evento en línea y totalmente gratuito durante los días 2 y 3 de Octubre de 2021.
Web: https://2021.es.pycon.org
Agenda: https://2021.es.pycon.org/#schedule
Improve this page
