+ All Categories
Home > Documents > Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van...

Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van...

Date post: 13-Jan-2016
Category:
Upload: amelia-sullivan
View: 215 times
Download: 2 times
Share this document with a friend
Popular Tags:
38
Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink
Transcript
Page 1: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Flow Simulation in TINs

Drainage Queries in TINs: from local to global and back again

S. Yu, M. van Kreveld, and J. Snoeylink

Page 2: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Motivation

• Provide important information on water resources, flood areas, erosion and other natural processes

• Natural resource management

• Road building, logging, or other activities have potential to affect defining stream

• Manual quantification of terrain drainage is time consuming

Page 3: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

TINs

• Piecewise-planar approximation to a terrain where each facet of the approximation is a triangle

Page 4: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Assumptions

• At any point, water follows the steepest descent

• Watercourses can merge, forming trees

• Watercourses end only at local minimum

• At any point there is a unique direction of steepest descent (no flat faces)

Page 5: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

General Definitions

trickle path(p):

path beginning at point p, following steepest descent and ending at local minimum

watershed(p):

set of points which drain to p

watercourse network:

all points that form watersheds

Page 6: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Observations

• steepest descents in a triangle lie on parallel lines (planar object)

• edge become channels when flow comes from both adjacent triangles

• trickle paths cannot cross

• drain objects:

faces edges vertices faces

faces edges

Page 7: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.
Page 8: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Definitions

Page 9: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Definitions

• peak – local maximum (vertex)

• pit – local minimum (vertex)

• basin – watershed of a pit

Method

• Approximate steepest descent by passing flow triangle to triangle in direction of steepest descent

Page 10: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Observations

• point p collects flow from region bounded by steepest ascent in adjacent triangles

• trickle paths from local channels determine the watershed network

Lemma:

Watercourse network is a collection of disjoint trees rooted at pits whose leaves are local channels

Page 11: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Watercourse Definitions

• junction – point of the network that has at least two separate incoming parts

• segment – maximal part that doesn’t contain junctions

• catchment area – the part of the terrain that drains directly into the segment

Page 12: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Processing a TIN Queries/Operations

• What is the area of the watershed of point q?

• What is the flow rate through q if water falls at uniform rate r?

• Construct the watershed of point q

• What points have watershed area of size A?

Page 13: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Idea

• Partition a TIN surface into pieces, for which simple functions summarize drainage behavior

Page 14: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Partitioning a TINTailored Definitions

• drain(p) – the point where trickle path(p) meets the network

• catchment area(s) – all points that drain(p) is on s

• set of basins (one per pit) – form a (coarse) partition

• set of catchment areas (per segment) – form a finer partition

Page 15: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

• base segments – for every vertex v define a node drain(v) which cut segments into base segments (further refinement)

• right/left strips – set of points p such that drain(p) lies on s and trickle path(p) comes from the right/left

Lemma:

A strip is a region bounded by a base segment from a local channel, a segment of a local ridge, and two steepest descent paths.

Page 16: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Corollary:Basins, watersheds, and catchment areas

are bounded by local ridges and steepest descents

Proof: all are composed of left/right strips of segments

Corollary:Watershed area, projected area, or steady-

state flow rate can be summarized by piecewise quadratic functions on base segments

Page 17: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Proof: For a query point q,

base segment s determines left and right strips that are partially inside the watershed of q

Every other strip is either entirely outside or inside and contributes a constant amount

contribution(s) – at^2 + bt + ct is a parameter indicating the position of q

on s

Page 18: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Computation of Flow Network

For each triangle t,

Calculate the center point p,

Call t.trickle path(p)

Locate tree in network (forest)

Add (sub)path as branch to tree

Page 19: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Query:Given a discrete set of points P each with a

corresponding mm/hour rain value, and a point q, approximate the flow at q according to time.

Init:T = find flow tree containing query point qFor each triangle t containing p in P,set inflow, slope, flow speed, out capacity

Flow Simulation

Page 20: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

run():For each time frame,Start with any leaf triangle t in T,t.flow = t.inflowt.outflow = min(t.flow, t.outcapacity) t.flow -= t.outflowUntil t is a pit, t.flow += t.inflow + t.sources.outflowt.outflow = min(t.flow, t.capacity) t.flow -= t.outflowContinue up the tree merging sub-trees and

summing input flow

Page 21: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Results

Page 22: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.
Page 23: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.
Page 24: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.
Page 25: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.
Page 26: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Demonstrating trickle path

Page 27: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Working with grid elevation map (PGM)

Page 28: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

TIN created from 237606 grid points containing 79998 triangles

Page 29: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

14820 trickle paths longer than 5

Page 30: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

31248 Triangle TIN created from 92256 grid

Page 31: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

19998 Triangle TIN created from 58806 grid

Page 32: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

8710 Triangle TIN created from 25350 grid points

Page 33: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

TIN created from 372006 grid points containing 124998 triangles

Page 34: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

5561 trickle paths longer than 10

Page 35: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

TIN created from 496008 grid points containing 166498 triangles

Page 36: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

TIN created from 537840 grid points containing 180484 triangles

Page 37: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Extensions and Future Research

• Absorption of water by different ground types

• Account water volume (spilling, pruning)

• Horizontal triangles, stream bifurcation

Page 38: Flow Simulation in TINs Drainage Queries in TINs: from local to global and back again S. Yu, M. van Kreveld, and J. Snoeylink.

Conclusions

• TINs can provide a good, efficient approximation of drainage networks

• Large maps require significant optimizations/approximations


Recommended