A genetic algorithm approach to cartographic map generalisation Export

@article{citeulike:3844691, abstract = {Rendering map data at scales smaller than their source can give rise to map displays exhibiting graphic conflict, such that objects are either too small to be seen or too close to each other to be distinguishable. Furthermore, scale reduction will often require important features to be exaggerated in size, sometimes leading to overlapping features. Cartographic map generalisation is the process by which any graphic conflict that arises during scaling is resolved. In this paper, we show how a Genetic Algorithm (GA) approach was used to resolve spatial conflict between objects after scaling, achieving near optimal solutions within practical time constraints.}, address = {Amsterdam, The Netherlands, The Netherlands}, author = {Wilson, Ian D. and Ware, Mark J. and Ware, Andrew J.}, citeulike-article-id = {3844691}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=963785.963792}, citeulike-linkout-1 = {http://dx.doi.org/10.1016/S0166-3615(03)00132-5}, doi = {10.1016/S0166-3615(03)00132-5}, issn = {0166-3615}, journal = {Comput. Ind.}, keywords = {generalisation, genetic}, number = {3}, pages = {291--304}, posted-at = {2009-01-03 15:15:14}, priority = {2}, publisher = {Elsevier Science Publishers B. V.}, title = {A genetic algorithm approach to cartographic map generalisation}, url = {http://dx.doi.org/10.1016/S0166-3615(03)00132-5}, volume = {52}, year = {2003} }

TY - JOUR ID - citeulike:3844691 L3 - citeulike-article-id:3844691 N2 - Rendering map data at scales smaller than their source can give rise to map displays exhibiting graphic conflict, such that objects are either too small to be seen or too close to each other to be distinguishable. Furthermore, scale reduction will often require important features to be exaggerated in size, sometimes leading to overlapping features. Cartographic map generalisation is the process by which any graphic conflict that arises during scaling is resolved. In this paper, we show how a Genetic Algorithm (GA) approach was used to resolve spatial conflict between objects after scaling, achieving near optimal solutions within practical time constraints. IS - 3 JF - Comput. Ind. SN - 0166-3615 AD - Amsterdam, The Netherlands, The Netherlands EP - 304 TI - A genetic algorithm approach to cartographic map generalisation PB - Elsevier Science Publishers B. V. VL - 52 SP - 291 KW - generalisation KW - genetic AU - Wilson, Ian AU - Ware, Mark AU - Ware, Andrew PY - 2003/// UR - http://dx.doi.org/10.1016/S0166-3615(03)00132-5 ER -