Data for "Complexity-based matching between image resolution and map scale for multi-scale image-map generation"

An image-map is a compromise of an image
and a map. The quality of such maps is
affected by a number of factors, such as (a) the matching between the features
on images and the graphic symbols from maps, (b) the
complexity of background images, and (c) the representation of graphic and text
symbols on the images. This project
deals with the first issue. The current solution is
that the accuracy of images should satisfy the accuracy standard of maps. However, images with
different resolutions can satisfy the standard for a specific map scale. This may lead to such a situation that the levels
of detail (LoD) in images may not match the complexity of map features although
the planimetric accuracy is matched. To solve
this problem, we developed a complexity-based matching between the image
resolution and map scale. More
precisely, the matching is based on the complexity of line features. Experimental evaluations were conducted in
fifteen representative areas in Hong Kong, by using maps at seven scales and
eight image resolutions. Results show
that this complexity-based method is capable of obtaining good matching between
image resolution and map scale, in terms of both accuracy and users'
preference.