Logo Lanfrica

ChidinmaMadukife/GDP-Estimation-Using-Satellite-Images

Domaine:

socioeconomicgeospatial

Type de record:

project
Créateur:
Chi
Hôte:
A project on predicting provincial GDP in South Africa using satellite data and machine learning. A project on predicting provincial GDP in South Africa using satellite data and machine learning. @ Explore AI Internship # Estimating GDP Using Satellite Data ## Project description - This project aims to investigate the use of satellite imagery to predict economic activity at a provincial level in South Africa. - GDP is important because **it gives information about the size of the economy and how an economy is performing**. The growth rate of real GDP is often used as an indicator of the general health of the economy. In broad terms, an increase in real GDP is interpreted as a sign that the economy is doing well. - The team sourced relevant datasets and employed ML techniques to develop a model capable of predicting GDP figures for a given year using only data from the first few months of that year. - Various sources were used to collect satellite images, these include: (list sources here). - This project can potentially become a unique data product and showcase the capabilities of AI in predicting economic development patterns using satellite images. ## Team Members - Obinna Ekenonu - Chidinma Madukife - Tolulope Adeleke - Samuel Olaniyi - Mabel Yusuf - Kgotso Makhalimele ## Environment It's highly recommended to use a virtual environment for your project, there are many ways to do this, below we have provided one example of how this can be achieved. Ensure when working on your project to keep this section up-to-date so if anyone needs to run your code they know the exact steps needed to get the appropriate environment ready. A person should be able to clone your repo and get up and running with the instructions provided here. ### Setup - you only need to do this once ```bash # make sure your pip in your base Python installation is up-to-date python3 -m pip install -U pip # install the virtualenv package python3 -m pip install virtualenv ``` ### Create the virtual environment - also typically only run when needed ```bash # create a virtual environme …