Uploaded March 2020 | Updated September 2026, 3 weeks ago
Use geopandas to split a shapefile into training and test datasets to be used for random forests classification. Eventually, this playlist will result in development of a random forests classifier to create land cover classifications for NAIP imagery. Land cover classifications will be applied to image segments (object-oriented image analysis). Code for tutorials in this playlist can be accessed from the web pages linked below.
Visit opensourceoptions.com for more content and courses
Code for this video is available here: opensourceoptions.com/blog/python-geographic-object-based-image-analysis-geobia-part-2-image-classification
Blog post for Part 1: opensourceoptions.com/blog/python-geographic-object-based-image-analysis-geobia
Use geopandas to split a shapefile into training and test datasets to be used for random forests classification. Eventually, this playlist will result in development of a random forests classifier to create land cover classifications for NAIP imagery. Land cover classifications will be applied to image segments (object-oriented image analysis). Code for tutorials in this playlist can be accessed from the web pages linked below.
Visit opensourceoptions.com for more content and courses
Code for this video is available here: opensourceoptions.com/blog/python-geographic-object-based-image-analysis-geobia-part-2-image-classification
Blog post for Part 1: opensourceoptions.com/blog/python-geographic-object-based-image-analysis-geobia
