Custodians of Geographic Information Systems (GIS) databases currently provide timely and high quality spatial products to users, maintaining multiple databases at different scales for different uses. These custodians are also committed to maintaining and updating the currency of cartographic data sets. Maintaining multiple databases is resource-intensive, time consuming and cumbersome. Cartographic generalisation has primarily been used to derive smaller scale map products from these databases. The practice is based on a cartographer s skill and incurs a high cost. Thus, new approaches for automating the generalisation of spatial data to produce highly varied sets of versatile, multipurpose map products need to be developed. This paper presents a generalisation methodology to derive multiscale spatial data through an evaluation of standardised mapping software that was used as a testbed based on the principles of generalisation. It focuses on integration and utilisation of generalisation operators in order to generalise a road network database, in order to produce small scale maps at 1:500,000 and 1:1,000,000 from 1:250,000 national topographic data that led to the development of a framework for derivative mapping concepts.
|Number of pages||14|
|Journal||International Journal of Geoinformatics|
|Publication status||Published - 2013|
KAZEMI, S., Forghani, A., CHO, G., & MCQUEEN, K. (2013). Integrated Cartographic and Algorithmic Approach for Road Network Database Generalisation. International Journal of Geoinformatics, 9(4), 63-76.