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Sun X.,State Key Laboratory of Information Engineering in Surveying | Sun X.,Changzhou Surveying and Mapping Institute | Li F.,State Key Laboratory of Information Engineering in Surveying | Yan J.,State Key Laboratory of Information Engineering in Surveying
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | Year: 2015

Based on a detailed analysis of the Slepian function, the advantages and disadvantages of the application of the Slepian function in computing lunar local gravity model, local power spectrum combined with the CEGM02 model and local admittance and correlation based on CEGM02, SGM150j, LP150Q and GRAIL660 were analyzed in this paper. It turns out that the local orthogonal Slepian function shows obvious advantages in modeling lunar local gravity field. In the application of power spectrum, the method of Slepian model shows a much wider, credible and reliable bandwidth but brings greater uncertainty in high degrees with the abnormal signal on the cap edge. On the contrary, the local power spectrum curve of Slepian window reflects the relationship between local gravity and the whole moon, but the spectral curve shows a narrow reliable bandwidth and significant errors in low degrees. Local admittance and correlation of four gravity models shows small difference in low orders but obvious difference as the orders get higher. ©, 2015, SinoMaps Press. All right reserved. Source

Liu Q.,Wuhan University | Liu Q.,Changzhou Surveying and Mapping Institute | Deng F.,Wuhan University | Li L.,Changzhou Surveying and Mapping Institute | Ran H.,Changzhou Surveying and Mapping Institute
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | Year: 2015

Considering the demands for precise spatial relationships and effective 3D visualization in 3D planning approval, two solutions of rapid and mass building roof texture generation is presented in this paper. In the first solution, the correspondence of object space and image space is built based on the collinearity equation of perspective projection, then, the best roof texture for texture mapping can be selected considering the optical axis direction, occlusion relation and image resolution. In the second solution, the roof texture database is built and used to synthesize roof texture with the smart matching technology. The experimental results with the 3D city models of Changzhou demonstrate that two sets of solutions for roof texture generation can meet the requirements of rapidly reconstructing texture of building. Source

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