Hui Lin, Jun Zhu, Bingli Xu

1. A study on the particle system method for dynamic modeling in virtual geographic environments (VGE) Hui Lin, Jun Zhu, Bingli Xu Institute of Space and Earth information science The Chinese University of Hong Kong February 27, 2008

2. Contents • Introduction • The particle system based dynamic modeling • Prototype system and experiments • Conclusions and future work

3. 1 Introduction Virtual geographic environments • A Virtual Geographic Environment (VGE) is a virtual representation of the natural world. It aims to offer more intuitive and efficient interactive visualization environments for the visual exploration of large amounts of complicated spatio-temporal information. • The multidimensional and dynamic analysis methods become the fundamental approaches for exploring spatial problems from all dimensions. • There are many successful VGE scenes such as virtual terrain, virtual city and so on.

4. Original Functions of GIS GeoDatabase Visualization Spatial Analysis

5. Expanded framework of GIS Modelbase GeoDatabase Virtual Environments SA + Data Mining Simulation Network supported environments (GRID Computation)

6. 1 Introduction

7. Animation of Crustal* Movement for a Year(Exaggerated by 400,000 times) *: Ground Surface

8. IKONOS Perspective Image of Phangnga Coastal Laem Krang Yai – Ban Bang La On : IKONOS_29 Dec 2004 Submerged shoreline . Narrow coast 2-3 m.msl . Irregular with many bays/inlets Khao Bang Khrok Laem Krang Yai 2 Ban Khuk Khak 1 2 2 1 Ban Bang Niang 2 Khao Lak Andaman Sea 2 Ban Bang La On 1 = Tin placer deposites 2 = Inlets

9. Animation of 2004 Indian Ocean Tsunamis

10. 1 Introduction Fuzzy objects Pollutants, clouds, water flows, and winds can be classified as dynamic and fuzzy boundary volume objects, which have unique properties of multidimensional structural and dynamic change. They are very important for studying geographic phenomena and solving environment problems.

11. 1 Introduction There are some shortcomings in many existing modeling methods for fuzzy objects: • Conventional models (e.g. point, line and surface) can not effectively represent fuzzy objects. • The static modeling environment cannot display the dynamic processes. • Many existing research is not related with geo-referenced environment. Our research will use the particle system to simulate dynamic fuzzy geographic phenomena and implement efficiency optimization in the VGE scene.

12. 2 The particle system based dynamic modeling 2.1 What’s the particle system?(1) The term particle system refers to a computer graphics technique to simulate certain fuzzy phenomena, which are otherwise very hard to reproduce with conventional rendering techniques. Examples of such phenomena include fire, explosions, smoke, flowing water, sparks, clouds, fog, snow, dust, etc.

13. 2 The particle system based dynamic modeling 2.1 What’s the particle system?(2) A particle system is a collection of many minute particles that together represent a fuzzy object. Each particle has many attributes including position, shape, size, color, speed, direction, and lifetime and so on. Over a period of time, particles are generated into a system, move and changewithin the system, and die from the system.

14. 2 The particle system based dynamic modeling 2.2 Flowchart of dynamic modeling(1)

15. 2 The particle system based dynamic modeling 2.2 Flowchart of dynamic modeling(2) Step 1, a simplified math model for simulation representation. Step 2, initializing individual particle attributes including position, appearance, movement, and lifetime and so on. Step 3, In its lifetime, the particle can be generated into the system, move and change form within the system, and die from the system. Step4, Stochastic processes are used to generate and control many particles within a particle system. Step5, some methods including hierarchy model and Visibility culling are used to control the number of particles and to improve rendering efficiency. Step6, these remaining particles are rendered in a geo-referenced environment.

16. 2 The particle system based dynamic modeling 2.3 Visibility culling and hierarchy models(1) Visibility culling including view-frustum culling and occlusion culling canidentify such non-visible particles (e.g. red objects) and discard them before they are sent to the rendering pipeline .

17. 2 The particle system based dynamic modeling 2.3 Visibility culling and hierarchy models(2) If a particle system object is in the distance, then it can be modeled to low detail (few particles), but if it is close to the camera, then it can be modeled in high detail (many particles). It can be easily controlled by the projection pixel error.

18. 3 Prototype system and experiments • Our case study area is Pearl River Delta (PRD) Region with a total area of 42824 km2, which includes 11 cities such as HongKong. Using Visual Studio 2005 .NET, OpenGL and OpenSceneGraph, a prototype system was developed to construct a virtual PRD geographic environment. • It can support the real-time walkthrough for large scale terrain and real-time simulation for dynamic fuzzy objects (e.g., air pollution, rain, snow, cloud, smoke, etc.) in desktop computers.

19. Rapid Urbanization and Living Environment Studies From traditional agricultural dike-pond wetland to urban landscape 1980 1990 2000 Population in Shenzhen increased from 20,000 to 12,000,000 within 30 years

20. 3 Prototype system and experiments Virtual PRD region with DEM data of 100m resolution and ETM images of 30m resolution

21. 3 Prototype system and experiments Virtual Hong Kong region with DEM data of 10m resolution and RS images of 10m resolution

22. 3 Prototype system and experiments Virtual Chinese University campus with DEM data of 1m resolution and aerial photography photo of 1m resolution

23. 3 Prototype system and experiments Several particle effects in virtual PRD environment

24. 3 Prototype system and experiments A simulation of air pollution dispersion is showed on a imaginary site. Attributes of the smoke, such as the direction, the density and so on, can be changed dynamically.

25. Joint Programs with Top National Teams • Chinese Academy of Sciences • China National Space Agency

26. 4 Conclusions and future works • Conclusions： • The particle system based dynamic modeling method is effective to represent fuzzy geographic phenomena. Several kinds of particle effects were integrated into the virtual geographic environment. • Some simplification methods (e.g., view culling and level of detail model) were used to improve mutual operation efficiency. • Future works： • Further optimizing simulation effect and rendering efficiency. • New application study such assimulating air pollution transportation and dispersion in PRD region．

27. Thanks！