🔗Classifying High Resolution Aerial Imagery - Part 2
I have been attempting to use random forests to classify high resolution aerial imagery. Part one of this post series was my first attempt. The aerial imagery dataset that I am working on is made up of many ortho tiles that I need to classify into vegetation categories. The first attempt was to classify vegetation on one tile. This note documents classifying vegetation across tiles.
🔗Colorado Avalanches By The Numbers in R
A look at avalanches in Colorado. Please not I'm not an avalanche expert, so please take these interpretations with a healthy dose of skepticism.
🔗Data Science Resources
A collection of resources on data science and machine learning primarily in R.
🔗Classifying High Resolution Aerial Imagery - Part 1
The following note documents a proof of concept for classifying vegetation with 4 band 0.1m aerial imagery. We used sagebrush, bare ground, grass, and PJ for classes. approximately 300 training polygons were used as a training data.
🔗Making a Chloropleth Map in R
Load the libraries.
🔗D3:Basic Line Chart