a web-based visualization and analysis system for watershed management yufeng kou, chang-tien lu...
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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
