AUTOMATIC TUMULI DETECTION IN LIDAR BASED DIGITAL ELEVATION MAPS
In this study, we aim to identify Iron Age tumuli with a probabilistic method, in digital terrain models extracted from airborne LiDAR measurements. Our task was particularly challenging due to the strong and uneven elevation of the ground where tumuli are located. In addition, the area is densely covered by vegetation, mainly by forests, which makes it difficult to create a surface model. The difficulty was exacerbated by the fact that the height and width of tumuli is very diverse but incomparably smaller than the extension of the area. In contrast to the various visualization techniques (openness, local relief model) used since decades for identifying tumuli, our method recognises these features automatically. Our approach is based on a Marked Point Process Model (MPP), which due to its inverse methodology, allows us to detect tumuli with high precision, especially in comparison with bottom-up methods. We quantitatively evaluated the method on six test data sets and we demonstrated its advantages compared to a traditional Hough transform-based method.