1.
How to Use Spatial Data to
Create a Wildfire Risk Index
Follow @CARTO on Twitter

2.
CARTO — Unlock the power of spatial analysis
Introductions
Lucía García-Duarte
Data Scientist at CARTO
Mark Gibbas
CEO at Weather Source

3.
CARTO — Unlock the power of spatial analysis
Last year, more
than 8,000
wildfires burned
almost 2.6 million
acres in the state of
California alone.

4.
CARTO — Unlock the power of spatial analysis
Wildfire Risk is Only Increasing

5.
CARTO — Unlock the power of spatial analysis
Organizations need spatial data and
analysis to answer pressing questions
Government
Agencies
Insurance
Businesses
Power &
Utilities
How should I develop
wildfire suppression
plans, direct resources,
and aid in emitting
wildfire alerts when
needed?
Landscape
Managers
How can I design
contingency plans that
guarantee energy supply
during disaster recovery to
critical facilities and
vulnerable neighbors?
How can I prioritize and
allocate investments to
treat wildland fuels and
identify areas with a high
estimated loss?
How can I provide affordable
coverage, mitigate risks, and
manage losses, while staying
competitive by offering
wildfire insurance while
others choose not to?

6.
CARTO — Unlock the power of spatial analysis
POLL 1
Are you currently using weather data and/or spatial analysis
when analyzing wildfire risk?
Yes, I use it almost every day
Somewhat, I use it occasionally
No, I have never used location data or spatial analysis
before

7.
Key Ingredients For Wildfires
Vegetation Fuel Persistent Heat & Drought Wind
Spark Wildfires

8.
Climate Crisis Increased Wildfire Risk
Warming Planet:
More Atmospheric Energy
Stronger Atmospheric Dynamics
More Weather Extremes
More Drought
Stronger Winds
More Wildfires
NOAA

9.
Weather Source Data & Solutions
OnPoint Weather
OnPoint Climatology
ECMWF Forecast
Historical GFS Forecast
Historical ECMWF Forecast
GFS and ECMWF Ensembles
HRRR Forecast
WRF Forecast & Modeling
Dynamic Weather Alerting System (DWAS)
OnPoint Geospatial
The Weather Insights Platform (WIP)
Weather Impact Indices
Condition-Based Ad Triggering (C-BAT)
Much of this is available
via CARTO !

10.
CARTO — Unlock the power of spatial analysis
Building the
Wildfire Risk
Index with
Weather Data &
Spatial Analysis
+

11.
CARTO — Unlock the power of spatial analysis
Area under study: California

12.
CARTO — Unlock the power of spatial analysis
Area under study: California

13.
CARTO — Unlock the power of spatial analysis
Data Sources
● Wildfires data (2001-2020): perimeters of
different fires (Weather Source)
● Geographical Data:
○ Land cover type (Microsoft Planetary
Computer): physical coverage of the
Earth’s surface (i.e.: crops, trees, water…)
○ Köpper-Geiger climate classification:
assigns a different climate group based
on seasonal patterns.
○ Population and elevation (CARTO Spatial
features)
○ Kilometers of roads and distance to
the closest road (Roads North America -
Global - Natural Earth, from CARTO DO)

14.
CARTO — Unlock the power of spatial analysis
Data Sources
● Meteorological data (Weather Source):
○ SPEI - standardized precipitation
evapotranspiration index (2001 - 2020):
drought index, measured at different
time scales
○ SM - soil moisture (2014 - 2020): the
water content of the soil, measured at
different depths
● Sociodemographics data:
○ Median income (Sociodemographics -
American Community Survey dataset
from CARTO DO)

15.
CARTO — Unlock the power of spatial analysis
Building the WRI
1. Cluster the data → built a different index for each cluster
2. Fire precursors selection → find those variables related with burned area
3. Index definition → built a WRI combining selected variables

16.
CARTO — Unlock the power of spatial analysis
Building the WRI
1. Cluster the data → built a different index for each cluster
Building the WRI

17.
CARTO — Unlock the power of spatial analysis
Building the WRI
1. T
2. Fire precursors selection → find those variables
related with burned area

18.
CARTO — Unlock the power of spatial analysis
1. Cluster the data → built a different index for each cluster
2. Fire precursors selection → find those variables related with burned area
3. Index definition → built a WRI combining selected variables
Building the WRI
● Annual index

19.
CARTO — Unlock the power of spatial analysis
1. Cluster the data → built a different index for each cluster
2. Fire precursors selection → find those variables related with burned area
Building the WRI
● Seasonal index

20.
CARTO — Unlock the power of spatial analysis
Building the WRI
Annual Seasonal

21.
CARTO — Unlock the power of spatial analysis
Building the WRI
Annual Seasonal

22.
CARTO — Unlock the power of spatial analysis
Building the WRI
Annual Seasonal
https://gcp-us-east1.app.carto.com/map/2f397711-4bb3-41fa-9040-55990c237327 https://gcp-us-east1.app.carto.com/map/32fae6c5-dd8b-4805-ae59-f93ff9c29c29

23.
CARTO — Unlock the power of spatial analysis
Provides competitive advantage in assessing
wildfire risk:
● Defining coverage costs
● Adjust coverages
● Design specific plans to ensure resource
and personnel assistance
Can be used to design targeted marketing
campaigns
Use Case:
Using the WRI to
improve home insurance

24.
CARTO — Unlock the power of spatial analysis
Weather Source in the Spatial Data Catalog

25.
Thanks for listening!
Any questions?
Request a demo at CARTO.COM
Mark Gibbas
CEO at Weather Source // mark.gibbas@weathersource.com
Lucía García-Duarte
Data Scientist at CARTO // lgarciaduarte@cartodb.com