A Web-based Visualization and Analysis System for Watershed Management Yufeng Kou, Chang-Tien Lu...

A Web-based Visualization and Analysis System

for Watershed ManagementYufeng Kou, Chang-Tien LuDept. of Computer ScienceVirginia Tech

Thomas Grizzard, Adil Godrej, Harold PostDept. of Civil EngineeringVirginia Tech

Outline

Introduction System Architecture System

Demonstration Future Work Summarization

Introduction:Objective of the system

Build a comprehensive database of water information in the Occoquan Basin Surface water, Ground water, Water quality

Report impact of extreme weather incidents on Occoquan water system Flooding, draught, storm

Data

Department ofEnvironmental

Quality

Game and FishCommission

Weather and ClimateResearch Institute

Natural ResourcesConservation

Service

Fish and WildlifeService

Objective of the system

Water quality surveillance and evaluation Chemical pollutant density

High efficiency data operation and dissemination Real time data collection Internet-based online information publication

Outline

Introduction System Architecture System

Demonstration Future Work Summarization

Hardware Architecture

Real-time Data collecting System Connect monitoring stations to central database via telephone line Data collecting: every 15 minutes

Web-based Information Publication Maintain duplicate databases:

Master database: collect data from monitoring stations Slave database: A copy of master database

Web server

Software Architecture

Standard 3-tier System Thin client

All the computation and maintenance are on server side High performance

Efficient for data centric tasks

Software Architecture

Automatic Data Synchronization Master database Slave database By a FTP client programmed with Java Transfer action is triggered

periodically by “Scheduled Task” in Windows 2003

Only the increment of data is transmitted

Set firewall to ensure security

Software Architecture

Database system Visual Foxpro 7.0

Water data database: flow, stage, … Station database: location, description, … User database: name, password, contact

information, …

Development Tools ASP, HTML, Javascript Java Applet, Java Servlet, Javascript

Outline

Introduction System Architecture System

Demonstration Future Work Summarization

System Demonstration:GUI

System Demonstration:Data comparison between

stations ST60:

Located upstream of Bull Run Peak flow detected at 7AM, Jan

14, 2004

ST45: Located downstream of Bull Run Peak flow detected at 5AM, Jan

14, 2004

9 Hour gap Useful for flood prediction

System Demonstration:Linear scale vs Log scale

Linear Scale: Suitable for data with small

variance Details lost when plotting data

with large variance

Log Scale: Suitable for data with large

variance Details retained for the value

between the maximum and the minimum

Not good for data with small variance

System Demonstration:Statistics from historical data

50 year flow data

Minimum flow Maximum flow Average flow

Help find interesting patterns

1980 is a dry year 1973 is a rainy

year

System Demonstration:Data Cube

Data Cube Generate the union of a set of alpha-numeric summary tables corresponding to a given hierarchy

Provide an aggregation view for different dimensions

Usually aggregate temporal property to different granularities

Or aggregate temporal dimension with spatial dimension

Data Cube:Stations vs Day of Month

Water flow data for 7 stations in April, May, and June 2004 Show the flow fluctuation of multiple stations in a single

figure High flow values are identified, for example

By ST01 on April 13th ,14th; By ST01 and ST10 on May 8th and 9th

By ST01 and ST10 on June 18th and 19th

Data Cube:Time of Day vs Day of Month

Water flow data for ST70 in April, May, and June 2004 Clearly show the flow fluctuation at a specific time on a

specific day High flow values are identified

20PM-24PM, on April 12th; 0-3AM and 19-24PM, on April 13th 0AM-12AM, on April 14

Data Cube:Years vs Day of Year

Water 53 year flow data for ST70 High flow values are identified

Near the 150th day of year

Outline

Introduction System Architecture System

Demonstration Future Work Summarization

Future Work

More visualization methods 3-D representation

Both spatial attribute and non-spatial attributes

Animation Graphic tools for data comparison

Histogram, bar chart, pie chart, 2-D and 3-D colormap

Apply Data Mining Techniques Frequent Pattern Detection

Discover the area flooded frequently in the past 30 years

Abnormal Pattern Detection Find a week in which flow changes dramatically compared

with flow in the immediate adjacent weeks

Future Work

Apply Data Mining Techniques Similarity Search

Find two similar pollutant leak accidents according to their impacts on the Occoquan water quality

Association Rule Formulation Explore the relationship among temperature,

humidity, and stage fluctuation

Build a decision support system Combine GIS, Meteorological, Transportation,

Economics, and Water monitoring data Generate a comprehensive model

Rule-based system, Neural network, or Decision Tree

Predict damage of the incoming calamity and provide corresponding decision support

Summarization

Propose a web-based visualization and analysis system Has been successfully used for watershed

management Based on a 3-tier client/server architecture Near real-time data collection and

dissemination Support multiple visualization methods

Table, figure, and data cube Support download data as text file, PDF, or JPEG

Future direction Add more visualization methods Add data mining functionalities

Thank you !

Any comment is appreciated.

ykou@cs.vt.edu