Proc. of Monitoring, Prediction and Mitigation of Water-Related Disasters (MPMD2005), pp. 53-58, 2005.

GIS-based Simulation of Soft Geo-objects
Dayong Shen1, Kaoru Takara1, Yasuto Tachikawa1
1

Disaster Prevention Research Institute, Kyoto University, Uji, Kyoto 611-0011, Japan

ABSTRACT: To simulate dynamic soft geo-objects and reflect geoscientific laws, the authors discuss thecharacteristics, mathematical expression, parameter representation and rendering of GIS Flow Element (FE) andGIS Soft Voxel (SV). The simulation and rendering algorithms of GIS FE and GIS SV are based on particle
system and metaball technology in computer graphics. The main differences are that GIS FE and GIS SV havedefinite geoscientific meaning and they are simulated based on geoscientific models so they can well represent
geoscientific characteristics of simulated objects. Compared to traditional GIS modeling approaches such as TIN,grid, tetrahedron, octree and others, this approach is more convenient, realistic and efficient in simulating
dynamic soft geo-objects. This paper selects the simulation of soil erosion process on hillslopes as a case study,and proves that the approaches of GIS FE and GIS SV can enrich the capability of GIS. Therefore, they have thepotential for widely practical use.
1INTRODUCTION

Objectively geo-objects are divided into rigid geo-objects and soft geo-objects. The critical characteristic of asoft geo-object is that the object will change shape when influenced by forces or collisions. There are manykinds of soft geo-objects such as flood, landslides, mudflow, lava flow, wind, cloud, smoke, fire and others in thereal world. However, how to appropriately represent soft geo-objects in GIS is still a challenge even thoughtraditional GIS modeling approaches (Wu and Shi 2003) such as TIN, grid, tetrahedron and octree can well
represent rigid geo-objects.
In this paper, we mainly test GIS-based simulation of soft geo-objects using the approach of GIS FE andGIS SV.
2GIS FE AND GIS SV

A GIS FE is an object with position, velocity and direction and other parameters that change over time. But it
neglects volume. A GIS SV is an object with position, velocity, direction and volume and covered by anisosurface. When several GIS SVs meet together, one smooth surface will be formed. Both GIS FE and GIS SV
are basic simulation units to simulate dynamic soft geo-objects and built based on pixels from remotely sensed
imagery and scientific computation of geoscientific models (as shown in Table 1).
2.1 Structure● A GIS FE has coordinates of starting point and end point, velocity, direction and geoscientific models forcomputing V and D as shown in Figure 1.
● A GIS SV has two basic components: a critical point (or point skeleton) and an implicit surface (sometimesinclude constraints). The critical point is a point-shaped GIS FE and parameters of the implicit surface are shownin Figure 2, where strength and threshold have the same meaning as that in computer graphics (Geiss 2000). As
we draw GIS SVs using marching cube algorithm, the depth of division will affect both rendering speed andcontents pageaccuracy. Considering faults simulation is very important in geology, and it may cut many imagery pixels intopieces, we use constraint functions to control the shape and volume of a GIS SV. Index identity number is usedin template-based rendering algorithms, which will be discussed in the following context.
Table 1.

GIS FE and GIS SV

Description

GIS FEGIS SVKey geometricStarting point and end point

A critical point and an isosurface

Computing, simulating and analyzing theComputing, simulating and analyzing thevelocity and direction of soft geo-objects

volume and deformation of soft geo-objects

based on geoscientific models

based on geoscientific models

Considering existing accuracy of data

Considering

acquisition, it is simulated based on

acquisition, it is simulated based on pixels ofpixels of remotely sensed imagery

remotely sensed imagery

Geoscientific

Reflecting dynamic change of velocity

Reflecting the dynamic change of volume

meaningand direction of soft objects in a pixel

and shape of soft geo-objects in a pixel

CriticalReflecting dynamics and stochastics ofSimulating

characteristic

soft geo-objects realisticallygeo-objects naturallycomponents
Aims

Scale

existing

theaccuracy

deformationofofFigure 1. Structure of a GIS FE

Figure 2. Structure of the implicit surface Figure 3. Field function graph of a GIS SV54datasoft

2.2 Mathematical expression● Velocity of a GIS FE is computed using geoscientific models as seen in Eq. (1), where M 1 is geoscientificmodel, p1, p2 , K, p j are affecting factors of V .

V = M1( p1, p2 , K , p j )(1)

Considering that V is in direct proportion to L , which is the length of a GIS FE, we get:V = λL(2)

where λ is a proportional coefficient and λ > 0 .
● Implicit surface of a GIS SV is created by a field function as seen in Eq. (3):⎞⎛g (r ) = ⎜⎜ r − 2d 2 + h 2 2 ⎟⎟
⎠
⎝

2(3)

where d is the length of a pixel, h is the average thickness of soft objects, ( x, y, z ) are 3-D coordinates of the critical point of⎛

⎞

⎝

⎠

2222a GIS SV, r = x + y + z . Note that g (0 ) = ⎛⎜ 2d 2 + h 2 ⎞⎟ 4 and g ⎜⎜ 2d 2 + h 2 2 ⎟⎟ = 0 . Between r = 0 and⎝⎠r = 2d 2 + h 2 2 , values of g (r ) decrease smoothly from ⎛⎜ 2d 2 + h 2 ⎞⎟ 4 to 0 (as seen in Figure 3).
⎝⎠Note that volume of a GIS SV Vol is computed based on its inscribed cuboid, as seen in Eq. (4):Vol = d 2 h

2.3 Parameter representation (as shown in Table 2 and Table 3)
Table 2. Representation of a GIS FE
Parameters

Representation

Shape

A point, line, surface, or volume

Color

Depends on the color of the geo-object

Opaqueness

Depends on the opaqueness of the geo-object

Initial Position

The center point of current pixel

Velocity

Computed using geoscientific models

Direction

8-neibourhood tracing algorithm

Lifetime

When a GIS FE moves out of the simulated control boundary, its life will beended and not rendered any more55(4)Table 3. Representation of a GIS SV
Parameters

Representation

ShapeA voxel covered by an isosurface

Color

Depends on the color of the geo-object

Opaqueness

Depends on the opaqueness of the geo-object

Initial Position

the perpendicular projection of the center point of a GIS SV in a pixel planeis the center of the center point of current pixel

Velocity

Computed using geoscientific models

Direction

8-neibourhood tracing algorithm

Deformation

Computed based on separation and fusion algorithms; constraints will be
added if necessary

VolumeComputed based on its inscribed cuboid; volume control will be consideredwhen deformation occurs

Lifetime

When a GIS FE moves out of the simulated control boundary, its life will be
ended and not rendered any more

2.4 Rendering● Basic methods for rendering GIS FEs take each GIS FE as a point (or linear if motion blur is considered) lightsource. Each GIS FE has a constant color, without difference in luminance and hue, and no obstacles. Thenaccumulate the contribution made by all GIS FEs and integrate it into normally rendered scenarios. Advancedmethods include setting light and shadow and processing GIS FEs in hidden surfaces. Note that theoretically theshape of a GIS FE can be rendered as arbitrary point, line, surface or volume. However, the perpendicular
projection of a GIS FE in a pixel plane should be completely within the pixel considering that it is created basedon the pixel.
● To render GIS SVs, basic methods include tracing isosurface, controlling shape and setting light, texture andshadow (Geiss 2000); advanced methods contain special algorithms for separation and fusion (Desbrun andGascuel 1994) and template-based algorithms, which are used to create GIS SV template data and their index
identity numbers to raise rendering speed.
3CASE STUDY

3.1 Simulate water flow based on GIS FEs● data structure: struct WaterFlow{
C3DfPoint bPoint;//coordinates of the starting point (center of the base circle)

C3DfPoint ePoint;//coordinates of the end point (center of the top circle)

float radius;//radius of the basefloat velocity;//velocity of motion

float angle;//direction of motion

COLORFLT color;//r(0.0 – 1.0); g(0.0 – 1.0); b(0.0 – 1.0)

float transparency;//0.0 – 1.0};56

● geoscientific models: velocity model of overland flow is as seen in Eq. (5):V = a 0 (q / h )a1 Sa2(5)where V is velocity of overland flow (m s-1); q is discharge per unit width (m-3m-1s-1); h is depth of runoff (m); S
is slope angle (º) and a 0 , a1 , a 2 are coefficients and indices of geography.
●rendering: Figure 4 shows the technical routes for rendering overland flow. Figure 6 shows rendering effects ofdynamic overland flow.
read DEM dataread DEM data

trace flow direction

read the template data for GIS SVs

compute slope length

read the index data of the template data for GIS SVs
read graded data of the intensity of water erosion

compute unit dischargecolor GIS SVs based on graded erosion intensities
compute the depth of runoff

trace the movement direction for GIS SVs
compute the velocity of overland flow
define the structure of a GIS FE

compute the velocity of GIS VSs
preset the movement route for GIS SVs

preset the route of overland flow

render DEM

render DEM

render the dynamic process of hillslopes soil erosion

render dynamic overland flow
Figure 4. Flow chart of rendering overland flow

Figure 5. Flow chart of rendering the process of soil

erosion on hillslopes

3.2 Simulate soil erosion based on GIS SVs●erosion model:
Esl = a0 (I − I 0 I )a1 hsl (φ )a2 (sin 2α )a3 exp(− a4 Svc )(6)

where Esl (mm a-1) is the intensity of soil erosion on hillslopes; I is the intensity of rainfall (mm a-1);

I 0 is the-1

threshold value of the intensity of rainfall causing erosion; hsl (mm a ) is the intensity of runoff on hillslopes;
φ (%) is preponderant percentage of soil particle size; α is the gradient (radian); Svc (%) is vegetation coverage;

a 0 , a1 , a 2 , a 3 , a 4 are geographical coefficient and indices (Shen et al 2003).

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● rendering: Figure 5 shows the technical routes for rendering soil erosion scenarios. We collect data sourcesfrom a sub-watershed in China Loess Plateau region and simulate one rainfall process in that region. In Figure 6,the texture is based on a 1:10,000 color infrared aerial photograph. In Figure 7, DEM is digitized from a 1:5,000
relief map. The deeper color of a GIS SV, the greater erosion intensity of the pixel in which the GIS SV islocated.

Figure 6.

Simulate overland flow based on

Figure 7.

GIS FEs

by water on hillslopes based on

45

Simulate the process of soil erosion
GIS FEs and GIS SVs

CONCLUSION AND DISCUSSION

This paper discusses theory and methods of GIS FE and GIS SV, and proves that the methods are quite efficientthrough a case study in China Loess Plateau region. Considering existing accuracy of data acquisition, both GIS
FE and GIS are simulated based on remotely sensed imagery pixels. Therefore, they can be used as basic units
for simulating soft geo-objects and have the potential for widely practical use such as flood disaster modelingand simulation (Takara et al 1998). As the approaches of GIS FE and GIS SV are in progress, it is necessary toenhance their functions in geoscientific analysis to more conveniently show the strong capability of GIS.
ACKNOWLEDGMENTS This work is supported by JSPS (Japan Society for the Promotion of Science)
Fellowship. We are grateful to Lin, H., Ma, A.N., Mao, S.J., Jin, Z.P., Bao, H.J. and Li, P.J. for their help andadvice.
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Desbrun, M., Gascuel, M.P. (1994). “Highly deformable material for animation and collision processing”. In 5th
Eurographics Workshop on Animation and Simulation. Oslo, Norway.
Geiss, R. (2000). “Metaballs”. http://www.geisswerks.com/ryan/BLOBS/blobs.html.
Shen, D.Y., Ma, A.N., Lin, H. et al. (2003). “A new approach for simulating water erosion on hillslopes”.
International Journal of Remote Sensing. 24(14): 2819-2835.
Takara, K., K. Notsumata, R. Usaka. (1998). “A distributed model for flood runoff and sediment yield based onremote sensing and GIS”. Proc. of Symposium on Japan-Indonesia IDNDR Project---Volcanology, Techtonics,Flood and Sediment Hazards. Bandung, pp. 373-384.
Wu, L.X., Shi, W.Z. (2003). Principles and algorithms of GIS. Beijing: Science Press. (in Chinese)

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