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

Authors: Qian Peng*,
Topics: Geographic Information Science and Systems, Cartography
Keywords: image resolution, map scale, line network complexity, line complexity
Session Type: Paper
Day: 4/6/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: 8217, Park Tower Suites, Marriott, Lobby Level
Presentation File: No File Uploaded

Image-map is a compromise of image and map. In such maps, satellite images work as background and selective map symbols are then overlaid. The quality of such maps has been criticized. And the quality is influenced by the matching between image and map. The current solution is that the accuracy of images should satisfy the accuracy standard of maps. Images with a range of resolutions can satisfy the standard for specific map scale after different image collecting and preprocessing procedures. But the different levels of details (LoD) in images and maps may influence the matching results. This study develops a complexity-based (indicator of LoD) method to match between image resolution and map scale. The matching is based on the complexity of line features (line network and individual line). The indicators for complexity adopted in this study are length, density, area and fractal dimension. Experimental evaluations have been conducted with three areas (urban, rural and mixed) from 7 scales of vector maps and 8 resolutions of images in Hong Kong. In the experiments, the matching between image resolution and map scale is based on the analysis of the indicators for complexity of line network and individual line features from the three areas at different resolutions and scales. It is concluded that the proposed complexity-based matching method improves the matching between image resolution and map scale.

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