Abstract
Visual analysis is to effectively integrate geographic information data and guide users to comprehensively and carefully analyze the multi-dimensional, spatio-temporal, dynamic, correlation and other characteristics with the help of interactive technology. Firstly, from the perspective of multi-scene transformation, a smooth transformation method based on transparency rendering is proposed, which can eliminate the visual impact caused by scene transformation. Secondly, for the organization and rendering algorithm of geospatial data, the design process of multi-threaded data access, fusion and rendering is proposed. Using a multi-channel data-fusion strategy based on Quadtree, the imagery and vector data corresponding to the node location of the Quadtree are quickly fused to form a new logical data-tile. Through multi-threaded data transmission technology and combined with texture sharing mechanism in OpenGL, the fused data-tile is transmitted to the GPU for rendering. With the help of GPU parallel-computing ability, the rendering efficiency of multi-scene roaming is effectively improved. Compared with the traditional mode of independent rendering of each channel data, this design process has obvious advantages in terms of visual observation.
Supported by Aerospace Information Research Institute, CAS.
Y. Li and K. Fu—Contribute equally to this work.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Xia, J., Huang, S., Zhang, S., et al.: DAPR-tree: a distributed spatial data indexing scheme with data access patterns to support digital earth initiatives. Int. J. Digit. Earth (IJDE) 3(12), 1656–1671 (2020)
Sherlock, M.J., Hasan, M., Samavati, F.F.: Interactive data styling and multifocal visualization for a multigrid web-based digital earth. Int. J. Digit. Earth (IJDE) 14(3), 288–310 (2021)
Friederichs, F., Eisemann, E., Eisemann, E.: Layered weighted blended order-independent transparency. In: Graphics Interface, vol. 2021 (2020)
Everitt, C.: Interactive order-independent transparency. Nvidia OpenGL Appl. Eng. 7(7–8), 491–503 (2001)
Fu, H., Yang, H., Chen, C.: Large-scale terrain-adaptive LOD control based on GPU tessellation. Alex. Eng. J. 60(3), 2865–2874 (2021)
Zhan, J., Mei, L., Zhenming, S., et al.: Research on key techniques of smoothing transition of LOD texture blending and antialiasing based on Shader. Beijing Da Xue Xue Bao 58(1), 113–122 (2022)
Zhou, C., Chen, Z., Pian, Y., et al.: A parallel scheme for large-scale polygon rasterization on CUDA-enabled GPUs. Trans. GIS 21(3), 608–631 (2017)
Xu, W., Pattnaik, A., Yuan, G., et al.: ScaleDNN: data movement aware DNN training on multi-GPU. In: 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD), pp. 1–9. IEEE (2021)
Lins, L., Klosowski, J.T., Scheidegger, C.: Nanocubes for real-time exploration of spatiotemporal datasets. IEEE Trans. Visual Comput. Graphics 19(12), 2456–2465 (2013)
Xiangkun, G., Hu, L., Jishen, L., et al.: Real-time rendering algorithm of three-dimensional terrain based on CPU-GPU cooperative computation. J. Chin. Mini-Micro Comput. Syst. 39(4), 825–829 (2018)
Wang, W.B., Hong, Y., Xie, W.B., et al.: Real-time terrain tessellation on GPU using tessellation Shaders. Comput. Technol. Dev. (2015)
De Boer, W.H.: Fast terrain rendering using geometrical mipmapping (2000). http://www.flipcode.com/articles/article geomipmaps.pdf
Losasso, F., Hoppe, H.: Geometry clipmaps: terrain rendering using nested regular grids. ACM Trans. Graph. 23(3), 769–776 (2004)
Yu, C.M., Wang, C.M.: An effective framework for cloud modeling, rendering, and morphing. J. Inf. Sci. Eng. 27(3), 891–913 (2011)
De Carvalho Jr, P.R., et al.: An improved view frustum culling method using octrees for 3D real-time rendering. Int. J. Image Graph. 13(03), 1350009 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Li, Y. et al. (2022). Fusion and Visualization in GIS Multi-scenario Transformation Mode. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2022. Lecture Notes in Computer Science, vol 13492. Springer, Cham. https://doi.org/10.1007/978-3-031-16538-2_6
Download citation
DOI: https://doi.org/10.1007/978-3-031-16538-2_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-16537-5
Online ISBN: 978-3-031-16538-2
eBook Packages: Computer ScienceComputer Science (R0)