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.