I’ve previously posted on this blog about a machine-learning model we built to detect irrigation globally.
I’m happy to report that our work is now published as a paper in the journal Advances in Water Resources.
[Read More]I’ve previously posted on this blog about a machine-learning model we built to detect irrigation globally.
I’m happy to report that our work is now published as a paper in the journal Advances in Water Resources.
[Read More]A couple posts ago, I described the machine learning model that we developed to predict the extent of cropland irrigation worldwide. This post is a collection of all the things I learned about Google Earth Engine that went into running a global-scale model successfully.
[Read More]For our capstone project at UC Berkeley, we worked with the Department of Environmental Studies. We developed a machine learning model that we continued to improve even after the course term, and I’m happy to report that it is now under discussion to be a published paper – a first for the program itself, according to our lecturer.
Update Aug/5/2020: New blog post: a behind the scenes look on how we built the model.
[Read More]