How Coastal States Are Using GIS for Climate Resilience

Climate challenges facing coastal states

According to the National Oceanic and Atmospheric Administration (NOAA), floods are the most frequent natural disaster in the United States, causing billions of dollars in damages annually. Coastal states are particularly vulnerable to flooding due to rising sea levels and powerful storm surges. Severe storms, such as hurricanes, also increase the risk of flooding and can cause extensive wind damage and land erosion in coastal areas. Not only do these climate challenges cause billions of dollars in property and infrastructure damage for coastal states each year, but they pose significant risks to human health and safety.

According to the Environmental Protection Agency (EPA), more than 25 million people live in an area vulnerable to coastal flooding, and the risk of flooding is likely to increase significantly across the United States as global temperatures continue to rise. Climate change is leading to more frequent and intense storms, including hurricanes. On top of that, higher sea levels make storm surges and hurricanes more damaging - even a relatively small increase in sea level rise of a few inches can allow a hurricane or storm surge to push more water onto land and increase destruction. 

Investing in climate resilience

To deal with the increasing threats posed by coastal hazards, communities are heavily investing in planning and analysis to enhance climate resilience. Among the many ways coastal states are boosting resilience are flood mapping and hydrological modeling, analyses that help to predict flood events and understand the movement and distribution of water in the environment. These analytics produce important insights that not only keep people safe, but also guide infrastructure-related decision-making.

Hazard mitigation and emergency response planning

Understanding coastal land cover is a critical function for emergency response planning. By analyzing various infrastructure elements, such as road and bridge networks, in conjunction with variables like elevation, rainfall, and water runoff, states can effectively anticipate which roads or bridges might be prone to flooding in a storm scenario. This insight can help ensure the safe evacuation of residents. Similarly, knowing which areas are most susceptible to coastal flooding can help states make informed decisions to mitigate climate risks and protect communities and the environment. For example, states can leverage geospatial data and mapping to inform land use planning and guide zoning decisions that consider community safety and environmental conservation.

Stormwater management and flood modeling

Coastal communities also engage in stormwater mapping to deal with the management of stormwater runoff, which is excess rainwater or melted snow that flows off surfaces. Stormwater carries pollutants such as chemicals and debris as it flows through drainage systems. When stormwater systems are overwhelmed, like during a heavy rainfall event, contaminated runoff can spill into water bodies, causing environmental degradation and potential human health impacts. Coastal flooding from storm surges can also overwhelm stormwater systems and cause saltwater to contaminate freshwater supplies. Stormwater mapping can help inform stormwater utility fees (SUFs), which provide funding for managing and mitigating the impacts of stormwater runoff.

The need for geospatial data

As important as these analysis and modeling activities are to reduce the risks associated with climate events, they require comprehensive, up-to-date, and accurate geospatial data, which can be difficult to obtain. For example, GIS teams and hydrologists need land cover data with detailed impervious and pervious surface data to power flood mapping, hydrological modeling, and stormwater mapping. Impervious surfaces, such as pavement and buildings, contribute to stormwater runoff as they are unable to absorb water. Pervious surfaces, which absorb some level of water, can include grass, trees, and other natural features that are found in the environment. GIS teams analyze both impervious and pervious layers to quantify runoff coefficients and predict how water will interact with a community, ultimately informing their climate resilience and planning strategies.

Challenges in obtaining land cover data

Historically, both local and state governments have faced challenges in obtaining the precise land cover data they need for climate resilience planning. A community will likely maintain first-party data about underground stormwater infrastructure for stormwater mapping, like sewer networks. However, when it comes to collecting land cover data, GIS teams and hydrologists have a few options, whether for stormwater mapping, flood modeling, or hydrological analysis.

Land surveys

Land cover data can be collected manually through land surveys. While this allows for a high degree of control over feature collection, it often requires significant time and financial resources. Due to the time-consuming nature of the process, the data can become outdated by the time it is ready to use, and fail to reflect real-world changes that have occurred.

Manual digitization from geospatial imagery

Land cover data can also be collected digitally without conducting land use surveys. Municipalities may capture or purchase geospatial imagery to digitize features into classified vector layers. However, to extract vector features from imagery with the level of detail needed for analysis, GIS analysts must spend a huge amount of time on manual digitization. With cities taking as long as 12-18 months to complete these efforts, scaling the manual digitization of features across an entire state can take years.

The reality is that many GIS teams cannot easily devote the time and resources necessary to create and update the detailed map features needed for analysis, especially on a large scale. As with data collected during land surveys, data manually digitized from geospatial imagery can quickly become stale because of how time-consuming manual digitization is. 

AI-powered impervious surface and land cover mapping

Fortunately, advancements in technology have made it easier than ever before to get the high-precision geospatial data needed for analysis. At Ecopia AI (Ecopia) we’ve partnered with federal, state, and local governments to provide a source of truth for the land cover features, including highly detailed classifications of impervious and pervious surfaces. Ecopia’s AI-powered mapping systems extract detailed land cover features from up-to-date geospatial imagery with the accuracy of a trained GIS professional. This eliminates the need for manual digitization, producing high-precision geospatial data across an entire municipality in just a matter of weeks, at just a fraction of the cost of manual digitization.

Check out the following real-world examples to learn more about how Ecopia’s AI-powered mapping is transforming climate resilience in coastal US states:

Powering stormwater mapping and planning in Florida

As a coastal city located on the Atlantic shoreline of northeastern Florida, the City of Jacksonville requires highly detailed information on how stormwater will interact with infrastructure and the environment. The city was looking for detailed geospatial data to improve the cost and efficiency of stormwater mapping in Duval County, without compromising quality. After comparing multiple geospatial data providers, Jacksonville decided to partner with Ecopia due to the quality, speed, and scalability of the data. Ecopia produced detailed land cover data at a price per parcel that was over 80% lower than other vendors and delivered the data in just four weeks. 

Providing detailed land cover data to Washington State 

In 2023, Ecopia was also selected by the State of Washington to provide high-resolution land cover data state-wide for hydrological modeling, flood mapping, and other key climate resilience and sustainability applications. Ecopia’s AI-based mapping technology leveraged high-resolution aerial imagery to provide Washington with comprehensive land cover data across the state’s 70,000+ square mile area in just 4 weeks. The data fueled geospatial analysis workflows for both State agencies and third-party organizations developing climate resilience and sustainability solutions.

Delivering high-resolution land cover data to states with NOAA

Ecopia’s AI-based mapping technology also powers NOAA’s Coastal Change and Analysis Program (C-CAP). This program delivers free 1-meter resolution data to help coastal states analyze land cover features with an unprecedented level of detail, fueling more precise models and stronger decision-making to support climate resilience initiatives. This land cover mapping data is publicly available to use through NOAA’s Digital Coast website and covers 1.5M square miles of land cover across US coastal communities. 

Leveraging Ecopia data to enhance climate resilience

The impacts of climate change, including rising sea levels and shifting storm patterns, are transforming coastal landscapes. In response, coastal communities and states are leveraging AI-powered geospatial data to bolster resilience against these challenges. If you’re looking for comprehensive, up-to-date, and accurate geospatial data to enhance climate resilience, Ecopia is here to help. Get in touch to learn more.