Canadian Journal of Remote Sensing 34(2):338-350.

The influence of conifer forest canopy cover on the accuracy of two individual tree measurement algorithms using lidar data. Methods wise, perhaps start with:įalkowski, M.J., A.M.S. There is a considerable body of literature on individual crown detection in spectral and lidar data. Manual direct measurements of a subset of the trees in the area.Visual imagery (like the sample image shown, but covering a much wider area).Full las data, and a tiff raster generated from it.The problem is that this method merges near by trees into a single polygon.Įdit: I probably should have included some more detail about what I have. The closest I have to what I want is the results of passing the output of the isocluster classification through the Raster to Polygon feature in Arcmap. I can obtain a reasonable classification of the vegetation types (and information about the overall percent cover) in the area by using the Iso Cluster classification in Arcmap, but this provides little information on individual trees. This question Single Tree detection in ArcMap? seems to be the same issue, but there does not seem to be a good answer there.

A sample of the type of aerial imagery I have is at the end of this post. Both the visual data and the lidar come from a Pima County, Arizona dataset. The lidar resolution is approximately 1 x 1 feet.

The resolution of the aerial imagery is 0.5 feet by 0.5 feet. The location in question is a desert area, so the tree cover isn't as dense as a forest area. I have both visual wavelength areal imagery, and lidar data from the area. I am looking for a method to process a remote sensing image and extract the crown areas of the individual trees from the image.

Ortho genes extract software