Video: Statistical Analysis – Daynan Crull | Geo4Dev 2020

Remotely sensed data (e.g. satellite data) is rapidly becoming a critical component in geo-spatial analysis, particularly in international development when other sources of data are scarce. But the perception is that these data are too complex or costly (in terms of time and money) for general analysts to use.

Our Nighttime Lights workshop on Dec 11th broke down that perception using open source tools like Python and Google Earth Engine. Through a series of hands-on modules, experts trained researchers and policymakers–especially those based in low- and middle-income countries (LMICs)–in the application of Nighttime Lights data to important policy questions. We covered Nighttime Lights data access, as well as interpretation, processing, visualization, and statistical analysis (including time series analysis).

Whether you are an analyst just starting out with Python, or a seasoned data scientist looking to sharpen your remote sensing skills, you may find this workshop helpful. After honing your skills, not even the sky will be the limit! Familiarity with Python or programming is preferred (beginner is OK) to get the most from the session, but we’ll also point to resources for training at all levels.

For more information on the event and the Geo4Dev initiative, visit the website: geo4.dev