inundation risk information system (iris)...
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Inundation Risk Information System (IRIS) ViewerA Convergence of Big Spatial Data and Cloud Computing for Flood Mitigation
Mengyang (Iris) Guo1, Jie Gong1, Jennifer Whytlaw2, and Henry Mayer2
1Department of Civil and Environmental Engineering, Rutgers University2Edward J. Bloustetin School of Planning and Public Policy, Rutgers University
Introduction
Data Sources
A Cloud-based Platform & Use Cases
Use Case 1: Building Structural Elevation Data Extraction
Spatial Data Acquisition
Use Case 4: Fusion with Crowd-Sourced Photos for Flood Monitoring
It is very much in every homeowner's financial and survival interests to know exactly
the elevation of their home and to understand exposure to flooding vulnerability.
Modern big spatial data acquisition and processing technologies such as laser
scanning are increasingly used for floodplain management applications, generating
massive point cloud data sets. Although these spatial data immediately enable
applications such as geographical visualization with rich three-dimensional
information, their true value cannot be realized until accessing, visualizing, and
processing of these data can be conveniently done on the emerging computing
platforms such as tablets, smart phones, and wearable computers.
In this poster, we present a lightweight web-based 3D data exploration framework
that provide capabilities to visualize, analyze, and interact with city-scale 3D data on
a variety of computing devices. We demonstrate the use of this system to support
real-time flood risk visualization and to support real-time flood monitoring.
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User Interface
Real-time Tide Gauge Data
A Light-Weight Web-based Exploration Platform for Managing and Analyzing Massive
Point Cloud Data Sets and Other Geo-Tagged Information
Use Case 2: Flood Scenario Visualization
N.J. Coastal Line
Ground Elevation:5.75 feet
Front Door Elevation:8.75 feet
3 ft4.5 ft
17 ft
Use Case 3: Integration with Real-time Tide Gauge Data
Measured Water Surface
Elevation ~13 feetThis function give users the ability
to project photo onto the point
cloud model for detailed flood
elevation measurement during
flooding events.
Machine learning algorithms are
provided at the server-side to
detect the road/water surface.
This function fetches real-time tide
gauge data and overlays onto point
cloud data.
The following structural
elevation data can be
extracted for residential
homes:
• Front door elevation
• Ground elevation
• C2a
• C2b
• Building diagram
Toms River
Mobile LiDAR
Airborne LiDAR
A FEMA Rebuilding for
Greater Resiliency Study
BFE – 100 Year
Flooding
Acknowledgement
This research project was sponsored by Federal Emergency Management Agency through New
Jersey Department of Environmental Protection, award HMGP-DR-02NJ-4070-0004. The funding
and support from these agencies is appreciated.
Disclaimer
The views, opinions, findings and conclusions reflected in this presentation are the responsibility of
the authors only and do not represent the official policy or position of the FEMA and NJDEP, or any
State or other entity.