aegis: wildfire prevention and management information...

AEGIS: Wildfire Prevention and

Management Information SystemProf. Kostas D. Kalabokidis, Principal Investigator

University of the Aegean, Mytilene, Greece

• Large wildfires (mega-fires) in North & South America, Australia, Russia and the Mediterranean burned vast areas in the 21st century

• Climate change, overpopulation, overconsumption, "non-sustainable development"

Wildfires are ravaging our World!

• Greek firefighting strategy does not integrate a holistic system of geospatial and decision support tools

• Large number of systems exist; few of them can be considered fully integrated solutions

• EFFIS in EU, WFDSS in the US, CFFDRS in Canada

Wildfire Decision Support Systems

Challenge: Instant access to

functionalities

conduct fire analysis based on need, without thenecessity to install complicated software

Challenge: Intuitive solutions

TimeMAY OCT

Inactive period

JAN DEC

Fire Season

Inactive period

Computations

Challenge: Users demand vs.

requirements for maintenance

1,636 km2

14,068 km2

millions of km2

Challenge: Scalability

Auto-Hazard Pro (2002) Virtual Fire (2009)

• Spatial estimation of wildfire ignition risk for Lesvos Island

• Desktop installation required

• Complex Graphical User Interface (GUI)

• Dependence on external libraries (DLL’s)

• Automated spatial estimation of wildfire ignition risk & 3-day weather forecasts for Lesvos Island

• Easy-to-use Web-GIS GUI

• Computation based on High Performance Computing (HPC) nodes

Evolution

VENUS-C Fire (2010) AEGIS (2012-2015)

• Automated spatial estimation of wildfire ignition risk and fire propagations with the H-fire algorithm for Lesvos Island

• Computations based on Cloud

• High computing power, availability of resources and storage space, expandable, flexible

• Automated spatial estimation of wildfire danger (ignition + burned area + fire intensity)

•7 study areas of Greece

•Fire propagation based on Minimum Travel Time Algorithm

• Computations based on a hybrid Cloud (Microsoft Azure + HPC)

Evolution

The AEGIS System

• AEGIS: integrated approach to wildfire decision support, designed for use by the civil protection authorities of Greece

• End users interact with AEGIS through a Web-GIS platform and a Windows Phone application

Services provided by AEGIS

– Fire analysis (fire danger & behavior)

– Historical fire data

– Topographic & satellite maps

– Weather measurements

– Weather prediction maps

– Land use / land cover types

– Road network and fire management data

– Fire management tools (e.g. elevation profile, shortest routes to closest firefighting facilities, real-time images of high-risk areas through web cameras)

7 different study locations around the country of Greece (i.e. 10% of the total Greek territory) with high-hazard, high-value and high-use forest and other multi-purpose areas

Study areas

• Local and network-based Geographical Databases (GDB) to store, retrieve and

manage the necessary data and inputs of AEGIS

• Need for field sampling and inventory of vegetation and fuels on each of the 7

study areas (fuel models, canopy cover, stand height, CBH)

Geographical Databases &

Field Data Collection

The AEGIS System

The AEGIS System - Layout

Fire behavior analysis

(single fire simulation)

Fire behavior analysis – waiting for

the simulation outputs

Fire behavior analysis

simulation outputs

Major travel paths

Travel paths

Fire behavior analysis

simulation outputs

Arrival time

Rate of spread

Fire line intensity

Visualization of travel paths from a wildfire simulation through the AEGIS platform, over Google Earth

Fire behavior analysis

simulation outputs

Fire behavior analysis

(burn probability outputs)

Fire danger analysis

Fire danger analysis

Historical fire data

Historical fire data

Weather measurements

Data are retrieved at regular

intervals from a wide network of

Remote Automatic Weather

Stations scattered around the 7

study areas

Weather Forecast Data

Hourly weather

forecast maps for

the next 5 days (cell

size 5 km) based on

SKIRON/Eta (RAMS)

for:

• Air Temperature

• Relative Humidity

• Precipitation

• Cloud Cover

• Wind Speed

• Wind Direction

• Barometric Pressure

Wind speed and Wind direction

Air Temperature

Relative Humidity

Cloud coverage

Precipitation

Historical Weather data

Background maps

•Bing Maps

•OpenStreetMaps

•Land cover types

•Annotations

Types:

Fire management data• Pumping stations

• Fire hydrants

• Water tanks

• Road network

Locations of:

Fire management data

• Fire watch

outlooks

• Fire vehicles on-

duty

Locations of: • Cultural monuments

• Helipads

• Evacuation sites

• Gas stations

• Landfills

Measure polygon area &

polygon perimeter

AEGIS tools

Identify tool

Web cameras

AEGIS tools

Active Fires from

MODIS satellite

Shortest routes to the 3 closest

firefighting facilities

Drive times

AEGIS tools

Routing directions

Printing

Elevation profile

Fire management tools

Drive times

Fire management tools

Export to KML

Import KML

Active fires from AEGIS App

Fire management tools

Optical camera surveillance combined with visualization of the road network, the pumping stations, the cover types and real-time weather records from the closest RAWS

Combining fire management tools

• Parallel computing techniques (High Performance Computing –HPC, and Cloud Computing) to ensure both computational power and speed.

• On demand fire behavior simulations are conducted in an HPC cluster inside a Datacenter on-premises (Aegean University Campus).

• Seasonal burn probability outputs are first conducted in the Cloud infrastructure of Microsoft Azure and then finalized in the HPC cluster.

Computation scheme

Execution in the HPC cluster

Seasonal execution

Virtual

Machines in

Microsoft Azure

Data storage

ArcGIS Server

Burn Probabilities Conditional Flame Length

Visualization

Execution in the Cloud

Parallel computing scheme

• By taking advantage of the Cloud's ability to increase/decrease the number of available VMs on demand, end users are charged only for their consumed processing time and only during the actual wildfire confrontation period.

• On demand fire simulations are better suited to run on premises than in the Cloud. This is because of the significant amount of time overhead (approximately 15 min) required to allocate new VMs in Microsoft Azure.

• On demand fire behavior simulations need to be conducted instantly and thus, time overheads should be minimized to achieve a timely and effective response when a wildfire breaks out.

Architectural components of AEGIS

platform

Fire danger forecast Fire behavior

prediction

Fire management

tools & data

Fire database Active fire

detection

Damage

assessment

Virtual Fire

daily creation of fire

risk mapsX √ X

covered by

optical camera

surveillance

X

VENUS-C hourly fire risk maps

for the next 112

hours

√ X X X X

EFFIS Canadian FWI X X √ √ √

WFDSS

√ √ X √

by reports

from

individual

users

√

CFFDRS√ √

by using external

components√ √ X

AEGIS √ √ √ √

covered by

optical camera

surveillance

X

AEGIS vs. other related systems

A: West Attica, 13/6/2015; B: Chalkidiki, 16/6/2015; C: Rhodes Island, 23/7/2015; D: Rhodes Island, 31/7/2015; E: Rhodes Island, 23/8/2015; F: Lesvos Island, 30/8/2015

Spatial fire danger

results

A: West Attica, 13/6/2015; B: Chalkidiki, 16/6/2015; C: Rhodes Island, 23/7/2015; D: Rhodes Island, 31/7/2015; E: Rhodes Island, 23/8/2015;F: Lesvos Island, 30/8/2015

black polygons delimit the actually burned areas, while colored areas and lines map times of arrival and major travel paths in AEGIS

Simulation results

Second simulation run of Lesvos Island 2015 wildfire from the site where the first simulation ended

Simulation results

• Mobile application for wildfire information management that operates on Windows Phone devices

• Acts as a complementary tool to the web-based version of the AEGIS platform

• Digital assistant for artificial intelligence “Cortana” (developed by Microsoft for Windows Phone devices) allows information utilization through voice commands

The AEGIS App(lication)

EFFIS App

Forest Fire Danger Meter

Wildland Fire Behavior App

Mobile Apps in wildfire management

• Fire Data: access to fire management data• Position: re-calculates the current position

of the end user and re-centers the background map

• Weather: access to current weather conditions

• Directions: enables the calculation of the shortest route between the current location and a different location specified by the user

• Change Basemap: switch the base map scheme between Bing Maps and Open Street Maps

• Login: allows authenticated users to publish a new wildfire event in the web-based platform of AEGIS

Functionalities

(A) Basic screen of

AEGIS App;

(B) calculation of the

areas that the user can

access by driving a

regular firefighting truck

in 3 minutes, 5 minutes

and 10 minutes; and

(C) accessing fire

management data

through the AEGIS App

Functionalities

• Cortana is a highly advanced artificial intelligence system for the Windows Phone platform. It allows end users to execute the desired functions via their mobile phone, simply by using corresponding voice commands.

• The voice commands are executed in an automatic and transparent to the user way and the result is visualized on the screen of the mobile phone without any further user intervention.

Cortana

Cortana

(b) (c)

AEGIS App & AEGIS web-

based system

• The AEGIS system can potentially contribute towards a more sophisticated knowledge transfer among the various entities involved in wildfire suppression activities including operation centers and firefighting units in the field.

• Resources can be more easily shared among fire agencies, thus reducing costs and enabling efficiency for suppression operations.

• The system is designed for wide-scale deployment for the different geographical areas of Greece or regional countries with minimal effort and resources, providing the development of the required input databases and services.

Conclusions

AEGIS Video

Research Team

(~ 20 people & many agencies, incl. US Missoula Fire Sciences Lab and Microsoft Research)

• Kalabokidis K., Vasilakos C., Athanasis N., Palaiologou P., Vaitis M., Tsekouras G., Ager A., Finney M. 2015. AEGIS: Wildfire Web Geographic Information System. In Proceedings of 2nd International Conference SafeChania 2015: The Knowledge Triangle in the Civil Protection Service, 10-12 June 2015, Chania, Greece. 6 p.

• Athanasis N., Karagiannis F., Palaiologou P., Vasilakos C., Kalabokidis K. 2015. AEGIS App: Wildfire Information Management for Windows Phone Devices. Procedia Computer Science 56:544-549.

Website: http://aegis.aegean.gr

Platform: http://aegis.aegean.gr/aegisplatform

THANK YOU!

Questions & Answers