Virtual-memory tiling for spatial data handling in GIS

Virtual-memory tiling enables applications efficiently to handle much larger arrays of raster spatial data more efficiently than is otherwise possible, without requiring specialist computing resources. It has particular application to geographical information systems (GIS) given the wide availability of large sets of digital raster spatial data from remote sensing and other sources. The size of these data sets often greatly exceeds the capabilities of most applications on standard computer platforms. In this paper, a virtual memory tiling approach is developed and implemented in C++. A tiled array class with a similar syntax and usage to standard arrays is constructed, which is readily integrated With existing algorithms and applications. A framework is developed for classifying operations on spatial data in terms of small and large regions. These two categories are representative of a broad range of operations on spatial data in GIS. Experimental results on a standard desktop platform are presented for an application (river catchment hydrology) using a 297-Mb array (10,800 x 9600 cells) of USGS digital elevation data. (C) 1997 Elsevier Science Ltd.