期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2013
卷号：XL-1/W1
页码：311-316
DOI：10.5194/isprsarchives-XL-1-W1-311-2013
出版社：Copernicus Publications
摘要：Coastal areas are characterized by high spatial and temporal variability. In order to detect undesired changes at early stages, enabling rapid countermeasures to mitigate or minimize potential harm or hazard, a recurrent monitoring becomes necessary. In this paper, we focus on two monitoring task: the analysis of morphological changes and the classification and mapping of habitats. Our concepts are solely based on airborne lidar data which provide substantial information in coastal areas. For the first task, we generate a digital terrain model (DTM) from the lidar point cloud and analyse the dynamic of an island by comparing the DTMs of different epochs with a time difference of six years. For the deeper understanding of the habitat composition in coastal areas, we classify the lidar point cloud by a supervised approach based on Conditional Random Fields. From the classified point cloud, water-land-boundaries as well as mussel bed objects are derived afterwards. We evaluate our approaches on two datasets of the German Wadden Sea
关键词：Lidar; digital terrain model; classification; conditional random fields; coast
