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According to the International Energy Agency (IEA), the transportation sector was responsible for approximately 24% of energy-related greenhouse gas emissions in 2020. In efforts to reduce individual carbon footprints, environmentally-friendly physical activities such as cycling are becoming increasingly important. This presentation focuses on utilizing programming, specifically Python and JavaScript, to extract and analyze physical activity data sampled from athletes on widely-used sport applications like Strava, leveraging their APIs.

Data collection methods utilize accessible and collaborative platforms. The collected data includes metrics such as distance traveled, speed, elevation, and estimates of carbon savings from cycling activities. Detailed calculations of carbon savings are provided to estimate the amount of carbon emissions avoided.

The presentation demonstrates the potential of computational technologies, using Python for data extraction and analysis and JavaScript for data visualization, to analyze and visualize the environmental impacts of physical activities such as cycling, using sampled data from Strava's athlete community. Consequently, this investigation provides insights into the benefits of reducing carbon emissions through cycling and individual contributions to environmental conservation.

Successful extraction and analysis of data from athlete samples on commonly used applications are expected to enhance understanding and awareness of environmental issues. This is anticipated to provide better insights into the environmental impact of physical activities, such as cycling, and to reinforce global awareness of the importance of environmental conservation.