Modeling and analyzing massive terrain data sets
With recent advances in terrain-mapping technologies such as Laser altimetry (LIDAR) and ground based laser scanning, millions of georeferenced points can be acquired within short periods of time. However, while acquiring and georeferencing the data has become extremely efficient, transforming the resulting massive amounts of heterogeneous data to useful information for different types of users and applications is lagging behind, in large part because of the scarcity of robust, efficient algorithms for terrain modeling and analysis that can handle massive data sets acquired by different technologies and that can rapidly detect and predict changes in the model as the new data is acquired. This talk will review our on-going work on developing efficient algorithms for terrain modeling and analysis that work with massive data sets. It will focus on algorithms for constructing digital elevation models of terrains, handling noise in elevation models, and for computing watershed regions and stream-networks. The talk will also discuss some of the challenges that we face in this area. © Springer-Verlag Berlin Heidelberg 2007.
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