Impervious Surface Analysis for Climate Resilience Equity

Climate equity is a complex topic becoming increasingly significant in society. As climate events are more frequent and intense, communities must mitigate associated natural hazard risk and adapt to these changing conditions in order to be resilient. However, many communities lack the resources to develop climate resilience strategies, resulting in equity gaps that leave underserved populations more vulnerable to hazard risk.

Gaps in climate equity can be closed by understanding where vulnerable populations live, what their local landscape looks like, and how climate events will impact their area. With this information, policymakers and government agencies can derive actionable insights for improving resilience in the communities that need it most. It’s important to note, though, that reliable data is required in order to gain this level of understanding for such a complex and highly localized issue.

Comprehensive, accurate, and up-to-date land cover data is a game-changer for public sector organizations seeking these insights into climate equity and resilience. Vector features classified to represent distinct land cover types can be used to visualize and analyze the areas within a community most susceptible to climate risks like flooding and extreme heat, particularly when it comes to the amount of impervious surface or tree canopy. Weather data can then be used to model how likely an extreme event is to occur there, and demographic data can be factored in to reveal how climate events are likely to impact the local population.

Fortunately, the National Oceanic and Atmospheric Administration (NOAA)’s Office for Coastal Management produces publicly available land cover data to fuel this type of critical analysis. Ecopia AI (Ecopia)’s artificial intelligence (AI)-based mapping systems support NOAA’s Coastal Change Analysis Program (C-CAP) dataset, making it possible to provide communities with 1 meter resolution data. Although traditional C-CAP data (with a resolution of 10-30 meters) has been instrumental in climate resilience analysis, this enhanced granularity will power even deeper geospatial analytics across American coastal communities. 

Analyzing climate resilience equity with impervious surface data

To showcase just how informative NOAA’s high-precision land cover data is for US communities, Ecopia recently conducted an analysis of impervious surfaces and median household income in some of the most populous coastal cities across the country. These are important factors for understanding climate equity, as impervious surfaces lead to a higher risk of flooding and extreme heat events, and income can be an indicator of resilience.

The results are staggering - on average, lower-income communities of these cities have 13% more impervious surface cover than higher-income communities. While each community is different, these stats highlight how essential it is to create and maintain a land cover database that accurately reflects our dynamically changing landscape.

Check out the full analysis below:

This infographic just scratches the surface when it comes to visualizing and analyzing climate resilience equity, but highlights the significance of layering geospatial datasets together to derive actionable insights. 

Ecopia took this analysis one step further for the Houston metro area, adding in historical weather data to provide even more context for understanding climate risk and equity. Here’s a quick snapshot of our results, which echoed our nationwide analysis.

Our detailed analysis of the Houston metro area shows many lower income communities are more likely to have higher levels of impervious surface and experience more precipitation, making them less resilient socioeconomically and environmentally to extreme climate events like flooding.

Explore our Houston metro area analysis here in more detail.

Access C-CAP data from NOAA and Ecopia AI for climate resilience analysis

With the insights provided by such analyses, states, municipalities, nonprofits, and private companies alike can identify pockets of climate inequity and develop strategies to enhance resilience. By addressing both the environmental and socioeconomic factors that impact climate resilience, organizations can help communities adapt to a changing climate and mitigate risks. 

“Ecopia is proud to partner with NOAA to create informative datasets that empower coastal communities to enhance climate resilience and equity,” said Brandon Palin, Senior Director of Public Sector and International Development at Ecopia. “Communities need access to high-precision data in order to allocate resources effectively, and the increased resolution of NOAA’s freely available C-CAP data is powering critical analysis to drive real change.”

“Our partnership with Ecopia has enabled us to develop more granular data and empower coastal communities with the information they need to build resilience to increasing climate risks,” said Nate Herold, a Physical Scientist with NOAA's Office for Coastal Management. “High-resolution land cover data is an integral part of understanding the relationship between the population and our planet, and provides an essential foundation to a wide range of geospatial analytics for climate resilience, sustainability, and other key initiatives.”

In addition to providing open access to the 1 meter resolution C-CAP raster data, NOAA will continue to leverage the foundational Ecopia land cover data to fuel deeper geospatial analytics across US coastal communities. Organizations interested in incorporating the full vector dataset can get in touch with our team of experts here.

NOAA’s updated C-CAP data is now available for anyone to download from the Digital Coast website. To learn more about Ecopia’s work with NOAA, click here.

Analysis data sources:
Land cover data provided by Ecopia AI as part of ongoing work with NOAA*

Population and income data sourced from US Census Bureau (2021)

*Baltimore, Washington DC, Wilmington (DE), & Virginia Beach land cover data sourced from Chesapeake Conservancy; Philadelphia land cover data sourced from City of Philadelphia via PASDA