The reason for this blog post is to share a bit on a particular hard problem that I've encountered during my Master's thesis with a broader audience. I will try my best to write it in plain English, but as the problem is complex expect this to be a lengthy post with domain specific terminology.
Remote land use detection is a complex problem, regardless if your approach is a type of supervised or unsupervised classification. The intention of this article is to share my exploration with Google Earth Engine with the aim of educating you in case you are dealing with the same problem and my learnings turn out to be somewhat useful 🙂. For this short exploration, I have limited my scope to the detection of urban and suburban land use, i.e. developed land that is or was in use by humans within the Caribbean geographic region of small islands as defined by the United Nations Department of Economic and Social Affairs . In the below widget you can preview a subset of small Caribbean islands and visualise results of time series detections of accumulating objects (the red dots) from satellite imagery. These red dots represent for the most part manmade objects. Note however that these do not necessarily represent accumulating land usage changes, but mostly represent objects that alre