The goal of this lab was to learn how to classify vegetation in LiDAR data. The vegetation would be classified by low, medium, and high vegetation. High noise would also be classified in this process. QA/QC will be necessary to minimize error.
METHODS
LP360 was used for this data processing. A height filter was used to classify data into either low, medium, or high vegetation. If the points were above the high vegetation threshold, they would be classified as high noise. Only unclassified points were chosen, since vegetation is the last to be classified.
RESULTS
The study area after classification is shown below. The newly classified vegetation is shown as green.
Below are a few examples of closer views of classification within the study area. First is a building that was shown in the previous posts, now with classified vegetation.
Below is a view of some residential housing in the study area. The algorithms had some trouble differentiating between houses and vegetation at some points, especially when it involved overlap. Manual cleanup was used after the algorithm.
SOURCES
Data obtained from Cyril Wilson for use in 358 LiDAR course.
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