There is enormous location data available that can help decision-makers during an impending crisis decide who to evacuate, when, and from where, says Ryan Lanclos, Director of Public Safety Solutions, Esri. Lanclos is responsible for strategic initiatives across public safety and national security. He serves as Esri’s subject matter expert on GIS for emergency management and humanitarian response. He also leads Esri’s Disaster Response Program (DRP) that provides 24×7 GIS support to organizations during disasters.
What is the role and importance of Location Intelligence in emergency response and management?
Knowing the “where” during unsettling events — a global health pandemic, an active shooter situation, a raging wildfire — to mention a few are essential. How else would one know the location a virus is spreading to next, where rescue can be staged, or the places flames can escape to? But this kind of intelligence goes far beyond emergency response. When harnessed for preparedness and mitigation efforts, knowing where a community faces the greatest risk, where residents are most vulnerable, and where critical infrastructure is located allows planners to design risk-informed projects that can reduce risk and help mitigate the impacts of these hazards. Putting it all together, Location Intelligence (LI) means a better understanding of systemic risk and the ability to anticipate and more effective response at the moment.
What is the unique value proposition of Esri for emergency response?
Esri has been assisting in disaster response efforts globally for more than 27 years. In that time, we have been engaged helping organizations respond to threats and hazards of all types and sizes — and we have learned a lot through those efforts. When we look back over the years, there are three broad areas where Esri software has and continues to help. The first is to fuse disparate, real-time data using a map to provide situational awareness that supports quick, informed decision-making. The second is the ability to understanding potential impacts from an approaching storm or an incident that just occurred. Who and what has been impacted, what does that mean for resource needs, and where can they have the greatest impact? This happens in emergency operation centers and the field using mobile devices for efforts like structural damage assessments — again, where the element of location is critical. The third is the ability to collaborate and share information securely in real-time with partners and publicly with residents using maps to provide the critical context that is often missing.
Can you point out a few of your success stories in crime, accidents, fires, health emergencies, and natural disasters?
If you think about it, the last year, alone, had every one of those grim events, keeping emergency managers busy and looking at how to anticipate what might be coming next.
The Covid pandemic led to countless lives lost and dominated the efforts of so many in the emergency management field. It’s difficult to consider anything during such an upending time as a success. Still, it was LI that Johns Hopkins University and other authorities seized on to track cases worldwide in easy to navigate dashboard to show where the virus was taking hold each step of the way, hopefully helping those regions and governments decide how to react. Later, LI was the backbone of numerous local vaccination deployments. In Maricopa County, Ariz., the municipality surveyed residents on their likelihood of getting a vaccine to dedicate resources where they were needed most. When officials noticed a zip code had fallen behind in inoculations relative to the rest of the county, they opened a vaccination clinic in its geographic center, bringing the rate up in a neighborhood that may have had difficulty accessing the other clinic sites.
In Southern California, where drought conditions have fueled ever-more-ferocious wildfires, utilities instituted power shut-offs when the environment appeared ripe to catch fire. While the aim is to certainly prevent the kind of sprawling devastation we have seen in recent years, the ancillary effect of those shut-offs is that residents in dire need of a power source — those that might be on ventilators — may be at risk. The Inland Empire Health Plan, the most extensive nonprofit Medicare-Medicaid plan in the country that serves millions in Riverside and San Bernardino Counties, has layered data on top of data to find those plan participants at risk and relocate them in such circumstances. The group looks at information from the local utilities, emergency response providers, and patient records to find people who might be caught in or near a power shut-off perimeter, to help.
The 2020 Atlantic hurricane season saw the most named storms in history, and the ferocity of the storms making landfall has undoubtedly changed. There is so much more location-based data available about weather patterns and forecasts that can help decision-makers during an impending crisis decide who to evacuate, when, and from where. It can help them consider the cascading impacts, too, including the loss of power for those who may not have even been close to the hurricane itself but instead suffer in the oppressive heat. A map with information about the location of assisted living residents at risk of losing power during such events could help emergency workers to respond proactively before it’s too late, ensuring the most vulnerable among us are taken care of.
Another cascading consequence of hurricanes can be severe flooding that leaves homes vacant until they can be fixed. Houston Police, analyzing an online map pinpointing burglaries after Hurricane Harvey in 2017, noticed a rash of them happening inside vacant homes among flooded neighborhoods. The department was able to respond by focusing on the most recent areas to be burglarized, sending several undercover officers to watch for the next attempt. In less than a week, the burglars were caught, and what they had stolen was returned to residents.
How are new technologies, such as AI, ML, Digital Twin, and IoT, making location data more actionable to improve the emergency services?
The best emergency response starts with robust data at its core. And with an ever-increasing amount of real-time data and a growing number of IoT sensors around us that can monitor everything from floods, seismic events, and air quality to the status of equipment in real-time, the ability to monitor, analyze, and take action based on this data is where we have great potential with location intelligence. Couple that data with a ‘Digital Twin’ representation of a location, be it a transportation network, facility, or an entire city, and we can speed response times with everyone involved on the same page about where key alerts are happening, where access points are located, and an immediate understanding of where a system may have gone awry. Using Artificial Intelligence (AI) or Machine Learning (ML) to automate this is to reach efficiencies and scales that make this truly real-time. When something does happen, ML and AI tools can comb aerial imagery of a disaster site over a large geographic area — imagine the entire island of Puerto Rick all at once — to determine what property damage may have occurred, which roads became inaccessible, and model which hard-to-reach sites may have succumbed to the elements if traditional communication networks are down.
How can we ensure the optimal use of LI and analytics to improve the services provided to citizens and customers? What are the challenges in this?
LI needs to begin with a foundation of accurate, precise data, including reliable base maps. Without it, any strategy will be hobbled from the start, and there are too many places around the world not on the map yet. Esri’s base maps combine rich, credible data sets from our partners and authoritative organizations with data from the community — like the Humanitarian OpenStreetMap Team (HOT) — to give those who need the information assurance that they are getting a full picture of a situation. The second aspect is taking a user-centric design approach when building solutions. Building any tool without a fundamental understanding of who it will help and what they need to succeed can lead to failure. Optimal Location Intelligence means combing the correct data with the right tools to deliver practical operational solutions. The best time to develop a geospatial strategy is now — before the next emergency happens. However, don’t underestimate the innovation and digital transformation that can often occur in the middle of an emergency response. Look at how quickly our world was transformed due to COVID-19 and moving to work from home globally.
What future do you see for LI and analytics in emergency response and management?
If the pandemic has taught us anything, it’s that we can’t simply rely on a good defense anymore. The days of merely reacting to the latest malady or only trusting our experience from a previous response to guide the next one are over. Emergency response teams should lean into preparedness and resilience efforts, using Location Intelligence as a foundation to understand where the next crisis may arise and how to prevent best or mitigate dire consequences for residents and customers — especially those most vulnerable in the community and those that are disproportionally impacted when an incident occurs. We can’t continue on the path we are today of respond, recover, repeat. That isn’t sustainable financially, and it isn’t sustainable for families who experience hardship again and again. Using historical data is all well and good. Still, if the last year has shown us anything, we need new ways to look at the increasingly systemic and interconnected risk in our world if we are going to change the outcomes for a more sustainable future. Just as our world is advancing quickly, so is the field of location intelligence — I think Covid advanced the world’s collective geographic knowledge more than any event in recent history. People now expect the same level of geographic insights and location intelligence we saw for COVID-19 every single day. I see this as the key to finding our way forward for a sustainable and resilient future.
