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Flood Factors: Map the flood risk of America’s 142 million properties with Mapbox


By: Marena Brinkhurst

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By making flood risk data free to everyone through FloodFactor.com, the nonprofit organization First Street Foundation equips individuals and communities across the United States to better understand and prepare for flooding and environmental change.

Uncovering underreported flood risks in San Francisco

Flooding is the costliest type of natural disaster in the United States, with losses of more than $1 trillion in inflation-adjusted dollars since 1980. Although institutional real estate investors and insurance companies have had access to detailed property flood risk data for years, the majority of Americans have access to years of detailed property flood risk data. relying on Federal Emergency Management Agency (FEMA) maps. However, FEMA maps are not created to model flooding at the individual property level, leaving millions of households and property owners unaware of the true risk.

The Flood Factor was created to address this knowledge gap. For example, I can quickly search Hoboken, New Jersey to see the areas most at risk.

Or I could search for zip code 20002 in the District of Columbia — and see that there is an “increased risk” and an estimated 2,385 properties will be at risk of flooding in just 30 years.

Our goal is to make the most up-to-date flood data freely accessible to everyone, using a simple 1–10 score that provides an easy way for property owners to understand the flood risk to their largest and most valuable financial asset: their home. .
— Matthew Eby, Executive Director, First Street Foundation

Make complex data private

The most important element of Flood Factor is its simplicity. Behind the scenes, the team at First Street Foundation has created a unique methodology that adapts to the reality of climate change and its impact on future flood risk, accounts for local adaptation, and combines all four. The main contributors to flooding: tides, rain, river flows and storm surges are all at the level of detail required to calculate the flood risk for individual properties. Although the modeling is complex, the user experience is accessible and engaging.

Flood Factor model location and depth of floods for different probabilities in a given year.

Flood Factor’s ‘Score Map’ feature allows users to visualize changes in the nature of risk and makes data more relevant. By breaking down scores as users zoom in and out, this interactive map allows them to understand Flood Risk relative to other properties in a simple and visually appealing way.

Partnering with Mapbox was instrumental in giving us an innovative way to integrate location into Flood Factor and improve the user experience. Our Score Map is one of our most popular site components.
— Colleen Ensor, Product Manager, First Street Foundation

An address search on the Flood Factor homepage, powered by the Mapbox Geocoding API, takes users directly to content that is relevant to them and their community. For optimal user experience, maps across the site use Mapbox GL JS for dynamic maps and static ‘snapshot’ maps to help orient users.

Static maps help find and confirm property addresses
Dynamic maps allow users to explore flood data in more detail and in relation to the surrounding area

To calculate flood risk scores at the individual property level, First Street Foundation uses building footprint data (from Mapbox, Microsoft, and OpenStreetMap) combined with parcel data from LightBox. The resulting flood risk data set was processed into vector plots and laid out in Mapbox Studio. The finished map features a variety of data-driven styling techniques and zoom-based styling techniques — explore how to replicate these in Mapbox Studio, directly in GL JS code using Expressions, or by editing paint properties.

Data to the public

Since its launch in June, Flood Factor has sparked new conversations around floods and flood preparedness, both in the scientific community, the media and the general public. Through a partnership with Realtor.com, Flood Factor now also reaches millions of current and future homeowners to help them understand a property’s risk of flooding due to environmental changes over the life of a 30-year mortgage.

Our goal is to democratize information that has long been inaccessible due to its complexity and cost. We’ve heard from people across the country who have used Flood Factors to help make important decisions about whether to purchase flood insurance, and other investments to protect their homes..
— Matthew Eby, Founder and Executive Director, First Street Foundation

First Street Foundation also shares its data with others working in the field of flood risk. Nonprofits, academia, and the public sector can access combined flood risk summary statistics for public and non-commercial use through AWS public datasets — and others can purchase access through APIs. Leading academic and industry researchers collaborate as part of the First Street Foundation Flood Lab to gain new insights and further understanding of flood risk, its consequences, and possible solutions. Other projects such as Neighborhoods at Risk are already using Flood Factor data to help communities prioritize stormwater system improvements and other climate adaptation efforts.

Understanding and communicating risks effectively is the first step towards adaptation and mitigation. Innovators like the First Street Foundation are leading the way. If you use location tools to change the world for the better, contact our Community team.

If you work with large data sets, give it a try Map Box Tile Services to process custom vector tiles. Combine your data with all available layers Studio accounts, including boundaries, terrain, elevation, and high-resolution land cover and land use data.

Marena Brinkhurst – Community Team Program Manager – Mapbox | LinkedIn

Map feature data from map box And OpenStreetMap and their data partners.


Flood Factor: Mapping the flood risk of America’s 142 million properties with Mapbox was originally published in maps for developers on Medium, where people continued the conversation by highlighting and responding to this story.



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