Andrew Danner

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We consider the problem of extracting a river network and a watershed hierarchy from a terrain given as a set of irregularly spaced points. We describe TERRASTREAM, a "pipelined" solution that consists of four main stages: construction of a digital elevation model (DEM), hydrological conditioning, extraction of river networks, and construction of a(More)
We develop cache-oblivious data structures for orthogonal range searching, the problem of finding all <i>T</i> points in a set of <i>N</i> points in <i>IR<sup>d</sup></i> lying in a query hyper-rectangle. Cache-oblivious data structures are designed to be efficient in arbitrary memory hierarchies.We describe a dynamic linear-size data structure that answers(More)
Given a set S of points in R sampled from an elevation function H : R → R, we present a scalable algorithm for constructing a grid digital elevation model (DEM). Our algorithm consists of three stages: First, we construct a quad tree on S to partition the point set into a set of non-overlapping segments. Next, for each segment q, we compute the set of(More)
In line with institutions across the United States, the Computer Science Department at Swarthmore College has faced the challenge of maintaining a demographic composition of students that matches the student body as a whole. To combat this trend, our department has made a concerted effort to revamp our introductory course sequence to both attract and retain(More)
Recent progress in remote sensing has made massive amounts of high resolution terrain data readily available. Often the data is distributed as regular grid terrain models where each grid cell is associated with a height. When terrain analysis applications process such massive terrain models, data movement between main memory and slow disk (I/O), rather than(More)
We present changes to our undergraduate computer science curriculum for a small liberal arts college. The changes are designed to incorporate parallel and distributed computing topics into all levels of our curriculum, with the goal of ensuring that all graduating CS majors have exposure to, and experience with, parallel and distributed computing. Our(More)
The proliferation of lidar technology in remote sensing has resulted in extremely large, high resolution point clouds covering a wide variety of terrain. Constructing a grid digital elevation model (DEM) from these large data sets requires extensive computational resources and ample disk space. We propose a framework for leveraging modern computing(More)