Dataset. The Actuele Hoogtekaart Nederland (AHN) is a so-called point-cloud, consisting of 3D points measured using LIDAR technology. LIDAR stands for Light Detection and Ranging - a remote sensing method that uses light in the form of a pulsed laser to measure ranges to the Earth, in the case of AHN taken from an airplane. We got 2.5TB of point cloud data for you to analyze.

C6: Forests of Trees. Train a deep learning model using the point-cloud dataset that detects trees. A basic goal would be to count trees in The Netherlands, and summarize them by size. Another goal could be to visualize forest areas, and display how many trees are iun them. An absolute stretch goal though would be to detect the tree species as well. This could be done on both the ANH2 and ANH3 datasets, and the dynamics of trees and forsts in The Netherlands could be visualized (how does this change over time).

Summary. This group used the YoloV3 model Forest 3D to detect trees in the AHN2 and AHN3 point-cloud datasets. Though this model is not perfectly suited for the task, as it is trained on point-cloud data other than AHN, the results seem to allow estimating tree quantity, and interestingly, compare AHN and AHN3 to see if where the amount of trees in The Netherlands is changing over time.

Data Curiosity: ***
Paper Writing: **
Technical difficulties mastered: ***
Visualization coolness: ****