In mid-September I got an email that said “ditt arbete med Birding Therapy som en av de nominerade av Årets Miljöhjälte i kategorin biologisk mångfald” (your work with Birding Therapy is one of the nominees for this year’s Environmental Hero award in the biodiversity category"). At first I didn’t know what to think and thought it was a phishing/malware type of spam. But then it sunk in that this is real, and it’s difficult to put into words how I felt. I didn’t think that anyone was paying attention to the small side project I started to get more people, particularly underrepresented groups, out into nature and birding.
My TEDx talk is now available on YouTube. The basic premise of the talk is that when you put all the recent advances in perspective, it results in a democratization of data on one hand, and science on the other. It means that anyone with a computer and a decent internet connection can have access to satellite data, process them using open source methods and extract information for their own use. This not only helps accelerate the rate at which scientific discoveries are made but also makes knowledge sharing and international development more equitable and inclusive.
Note: This tutorial was updated on April 20th, 2020 based on reader feedback.
In this short post, I would like to help you conduct your own machine learning classification of Sentinel-2 data using the open source package R. The process is pretty straightforward if you have experience in remote sensing and image classification. Even if you don’t have extensive experience, basic knowledge of remote sensing terminology is sufficient.