Disaster Management with GIS & AI – Be Disaster Ready

post disaster assessment

Disasters like earthquakes, floods, tornadoes, fires and hurricanes are events that have affected humankind significantly since the beginning. However, advancements in technology have helped humans to understand these disasters and mitigate the damage thus caused. Such technology not only gives us the foresight to avoid some of these disasters but also to manage the risks associated with the inevitable ones.  Of these technologies, Geographic Information Systems or GIS is extremely useful and has helped immensely in disaster management in recent times.

property and car on fire post disaster assessment
Disasters, both man-made and natural have plagued humanity since the beginning. Image Credits- Dawn Armfield on Unsplash

The role of GIS in disaster management

Disasters are intricately related to the land and geography of a place. Naturally, GIS becomes an indispensable tool in dealing with them. Moreover, the infusion of AI into the various GIS processes creates a very sensitive response framework as well as a highly insightful dataset about climatic and geographical parameters that dictate disasters. This combination of GIS and AI, called Geo-AI, provides indispensable relief and decision making abilities during all the stages of disaster management- pre, during, and post. The complex, large-scale operations that need to be carried out by governments and relief services during these stages are optimized, efficiently delegated and catalyzed with the use of Geo-AI. Let us look into the details of these processes.

Before the Disaster 

As they say,  ‘Prevention is better than cure’. In many cases, GIS can help us to prevent disasters, especially those originating from artificial causes. Since some disasters by their very nature are unavoidable, GIS provides a workflow to brace ourselves for the impact when such calamities finally strike. Using geographical, engineering, meteorological and demographic insights generated through various GIS tools, precautionary measures can be taken to improve the preparedness on an individual as well as the governmental level. In such cases, the foresight that GIS affords us helps us to save numerous lives and limit the damage to the minimum. Thus, before the disaster strikes, mitigation and preparedness become critical.

Mitigation

The focus during this phase is to propose long-term measures that can reduce or eliminate risks. The foundation of any successful mitigation or response plan is a detailed risk and hazard analysis. There is an extensive amount of data in various formats clubbed to form a comprehensive emergency management program. These programs are used to delegate resources and execute processes that mitigate or minimize the causes of the disaster.

Preparedness

ERPs or Emergency response plans, containing engineering as well as administrative controls are framed and publicized to ensure preparedness in case of an unfortunate occurrence of a disaster.  GIS helps governments, NGOs and relief services to prepare and execute these ERPs.

Mitigation, Awareness and Preparedness – Cyclone Amphan

The forecasts for cyclones is done by Indian Meteorological Department (IMD). IMD monitors and gives warnings regarding tropical cyclones. During the monitoring phase, satellite-based observation, a routine application of GIS, is extensively utilized. Cyclone Amphan was a powerful and deadly tropical cyclone that wreaked widespread havoc in Eastern India and Bangladesh in May 2020. Due to the timely forecast, numerous administrative and engineering controls were put in place which helped to minimize the destructive effects of cyclone Amphan.

Cyclone Amphan near peak intensity over the Bay of Bengal on May 18. Image Credit- NASA

After the Disaster

Once a disaster strikes at a specific location, relief services and emergency response teams come into action. Apart from the loss in lives and properties, the disaster also brings in a looming panic. Also, the amount of situational and on-ground information coming from the affected zones is huge. The panic coupled with the large non-systematic information can make all relief operations less effective or even futile. This is where GIS comes in handy. The various parameters of the situation are monitored geospatially so as to identify the affected zones with clarity. In such cases, heat maps, damage scores and other GIS insights allow us to understand the severity and thus provide indispensable crutches for decision making to enable response and recovery.

Response

The response activities include mobilization of emergency relief services and resources so that the first responders can execute their tasks effectively. Obtaining, managing, and maintaining the resources is important for the execution of a seamless response to a disaster.  All of these are intertwined with locational insights and thus GIS provides the most effective execution framework.

Recovery

After the initial shock of the disaster is managed, there is always a need to restore the infrastructure in the affected areas to their original state. The short-term recovery measures include the restoration of essential services which are guided by the geospatial insights. .Moreover, long-term recoveries, which include re-establishing major infrastructures and basic lifestyle amenities, utilize GIS to prioritize the recovery projects. 

Response, Delegation and Recovery – Hurricane Maria

The 2017 Hurricane Maria in Puerto Rico led to complete darkness across the island. Months passed by as residents did not have a power supply, and a scarcity of food and water began emerging. This led a small group of volunteers and developers, working under the umbrella of CrowdSourceHQ, to create a map of Puerto Rico. It helped the locals to communicate their requirements to the government and relief services. Emergency responders and volunteers would then get this information that enabled them to get into the action mode and provide the necessary support.

Hurricane Maria satellite image post disaster assessment
Hurricane Maria near peak intensity, moving north towards Puerto Rico, on September 19, 2017. Image Credit- The Naval Research Laboratory/ NOAA

Case study- Use of GIS and AI in the Insurance industry for disaster management and risk assessment

To understand how GIS and AI  create a unique solution that provides actionable insights and data pertaining to disasters, hazards and risks, let’s take a look at the insurance industry. The insurance industry deals with risks, disasters and accidents routinely and thus it must use the most efficient tools to predict, measure and mitigate risks and hazards.  

Preparing for the worst

The worth of an insurance company comes not only from how well it can predict, manage and mitigate risks and hazards but also from how well it can analyze and understand post-disaster situations. The revenue of insurers around the world are intertwined with these measurements. As a result, insurers use numerous Geo-AI tools and techniques as follows to be on top of the situation.

Risk Assessment

One of the most important preventive and risk-awareness methods is risk assessment. Risk assessment is the overall process or method wherein hazards and risk factors that have the potential to cause harm are identified. The probability and severity of the risks are calculated to define risk scores or matrices. 

P & C Insurance companies use risk assessments to understand risk factors that might be consequential for a property which helps them in policy underwriting. Risk assessment of properties can be easily carried out using remote sensing data and AI. Property insights are generated by performing feature extraction on aerial imageries which are then fed into risk modeling algorithms and calculators. 

property insights for insurance
Insurers use GIS to gather property insights using remote property surveys

Risk Engineering and Management

Risk management is the systematic identification, assessment and prioritization of various risks, followed by efforts to minimize or control the probability of occurrence of such hazards.

Before a disaster hits, GIS is used to calculate risks and understand the various hazards in a given geographical area. These are visualized using data derived from feature extraction and the insights can be used to perform risk mitigation. This is different from risk assessment as it is more detailed in its scope and also comprises an actionable plan to eliminate risks and prevent any disasters. 

Change Detection

Change detection is the comparison of two geographical datasets of the same location so as to determine the quality and measure of various factors that have changed with time.  Mapping and analysis of a region before and after a disaster, a classic application of change detection, can help insurers to quantify the damage that was done and measure the losses involved. With the help of change detection, the extent and type of damage, the geographical situation of it can be easily found out.

Benefits of using GIS for disaster management and mitigation in Insurance 

There are various benefits that GIS solutions provide to insurance companies in understanding and managing disasters. The major benefits are as follows

  • Improved risk insights using updated aerial imagery
  • Risk scores of individual properties can be accessed easily
  • Eliminating in-person inspections of disaster-hit sites
  • Use of latest geographical and meteorological data models for analysis
  • Low turnaround time for policy underwriting and claim-evaluations

Making disasters less disastrous by disaster management

Disasters are born out of the earth and its innumerable eco-systems. Hence, we need something that understands our planet and its components, to deal with these disasters. GIS is thus the natural weapon of choice in this fight. GIS when conjoined with AI can prevent numerous disasters with its enhanced ability to simulate future occurrences. Moreover, actionable insights, available on a real-time basis, enable response teams to handle disaster responses better. Thus GIS and AI lead to a preventative understanding, more collaborative response effort and lesser impact on the human population and infrastructure of disasters. Contact us to know how you can leverage GIS and AI to be better prepared in dealing with disasters.

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3 Responses

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