Workshop on Wet Area Mapping with Machine Learning
The 6-8th of November, the workshop on Wet Area Mapping with Machine Learning was held in Umeå, Sweden.
Anneli Ågren, Swedish University of Agricultural Sciences, is responsible for the activity Wet Area Maps in WAMBAF Tool Box.
− In the first part of the workshop, we taught how to write python-script to automate GIS calculations of digital terrain indices for large areas (entire countries) through iterations, says Anneli Ågren.
The main focus was on generating DTW-maps. In the second part, the focus was the use of machine learning in R to generate Wet Area Maps using DTW maps and other digital terrain indices as input.
Now the participants are working on generating Wet Area Maps for their countries. DTW-maps will be generated for Poland, Finland and Latvia while a Machine Learned Wet Area Map will be generated for Sweden. Due to the long processing times, this is expected to take a couple of months.