A quantitative scale-setting approach for building multi-scale spatial databases Export

@article{citeulike:5220767, abstract = {Finding a balance between data redundancy and manipulation efficiency can sometimes be problematic when building multi-scale spatial databases ( MSDB s). In order to render MSDB s real-timely, coarser representations with fewer vertices should be invoked once the response time exceeds the tolerable limitation. Of course, this would result in faster response speeds. With the vertex histogram making it possible to simulate the change in the number of vertices queried ( NVQ ) for the most complex area when the display scale shrinks, a NVQ based approach is set forward to fix the representations by comparing the NVQ of the most complex area with the tolerable NVQ . This causes the number of levels and definite scales to be determined not only by the dataset itself but also by the generalization method. As a result, the arbitrary appointment of levels or scales when building multi-scale spatial datasets is avoided. It is argued that this approach facilitates the use of fewer representation levels to build a multi-scale database with a reasonable scale-setting scheme. Furthermore, the response time is restricted within the limit set in advance. A case study with a real spatial dataset verifies the effect of the proposed approach.}, author = {Cheng, Changxiu and Lu, Feng and Cai, Jun}, citeulike-article-id = {5220767}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.cageo.2009.04.003}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S0098300409001605}, day = {11}, doi = {10.1016/j.cageo.2009.04.003}, issn = {00983004}, journal = {Computers \& Geosciences}, keywords = {data, database, multilevel, multiscale, scale}, month = {June}, posted-at = {2009-07-21 22:30:34}, priority = {2}, title = {A quantitative scale-setting approach for building multi-scale spatial databases}, url = {http://dx.doi.org/10.1016/j.cageo.2009.04.003}, year = {2009} }

TY - JOUR ID - citeulike:5220767 L3 - citeulike-article-id:5220767 N2 - Finding a balance between data redundancy and manipulation efficiency can sometimes be problematic when building multi-scale spatial databases ( MSDB s). In order to render MSDB s real-timely, coarser representations with fewer vertices should be invoked once the response time exceeds the tolerable limitation. Of course, this would result in faster response speeds. With the vertex histogram making it possible to simulate the change in the number of vertices queried ( NVQ ) for the most complex area when the display scale shrinks, a NVQ based approach is set forward to fix the representations by comparing the NVQ of the most complex area with the tolerable NVQ . This causes the number of levels and definite scales to be determined not only by the dataset itself but also by the generalization method. As a result, the arbitrary appointment of levels or scales when building multi-scale spatial datasets is avoided. It is argued that this approach facilitates the use of fewer representation levels to build a multi-scale database with a reasonable scale-setting scheme. Furthermore, the response time is restricted within the limit set in advance. A case study with a real spatial dataset verifies the effect of the proposed approach. JF - Computers & Geosciences SN - 00983004 TI - A quantitative scale-setting approach for building multi-scale spatial databases KW - data KW - database KW - multilevel KW - multiscale KW - scale AU - Cheng, Changxiu AU - Lu, Feng AU - Cai, Jun PY - 2009/06/11/ UR - http://dx.doi.org/10.1016/j.cageo.2009.04.003 ER -