Visualizing Change: Using Cartographic Animation to Explore Remotely-Sensed Data

Mark Harrower


This research describes a geovisualization tool that is designed to facilitate exploration of satellite time-series data. Current change-detection techniques are insufficient for the task of representing the complex behaviors and motions of geographic processes because they emphasize the outcomes of change rather than depict the process of change itself. Cartographic animation of satellite data is proposed as a means of visually summarizing the complex behaviors of geographic entities. Animation provides a means for better understanding the complexity of geographic change because it can represent both the state of a geographic system at a given time (i.e. its space-time structure) and the behavior of that system over time (i.e. trends). However, a simple animation of satellite time-series data is often insufficient for this task because it overwhelms the viewer with irrelevant detail or presents data at an inappropriate temporal and spatial resolution. To solve this problem, dynamic temporal and spatial aggregation tools are implemented with the geovisualization system to allow analysts to change the resolution of their data on the fly. These tools provide (1) a means of detecting structures or trends that may be exhibited only at certain scales and (2) a method for smoothing or filtering unwanted noise from the satellite data. This research is grounded in a delineation of the nature of change, and proposes a framework of four kinds of geographic change: location, size/extent, attribute and existence. Each of these kinds of change may be continuous (a process) or discrete (an event).


cartographic animation; change-detection; temporal and spatial resolution; data filtering; time series analysis; remote sensing; NDVI

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