How rapidly evolving technologies can help governments, communities and relief organizations prepare for and respond more quickly to natural catastrophes
Mikel Maron is head of community at Mapbox and a board member at the OpenStreetMap Foundation. The views expressed here are those of Maron and do not necessarily reflect the opinions of FreightWaves.
Hurricane Katrina was a catastrophe of unprecedented proportions during the record-breaking 2005 Atlantic hurricane season, but it also served as an early example of how useful crowd-sourcing and satellite imagery can be in disaster response.
What were then fortuitous lightning-bulb moments in using data-driven images and analytics in emergency situations are now considered landmark moments in terms of how individuals, enterprises, government institutions and relief organizations can dramatically hasten reaction times in life- and property-threatening situations.
In fact, the world’s top retailer established an early standard for the logistics industry in how to use mapping, predictive modeling and data processing to deliver supplies to victims in the storm’s aftermath. No less than the Wall Street Journal praised Walmart in the wake of the disaster, and the Weatherhead School of Management at Case Western Reserve University in Cleveland detailed the chain’s critical activities in a case study, including these points:
● Used point-of-purchase data culled from other hurricanes to determine what supplies its victims would need.
● Monitored weather reports to redirect goods originally planned to be shipped to Florida to the Mississippi/Louisiana Gulf Coast when the storm’s course shifted.
● Consistently reached relief workers and citizens in need faster than FEMA.
Setting new standards
Walmart was not alone in leveraging nascent technologies during Katrina. Crowdsourcing efforts analyzed satellite map images to track storm damage, with many of the images coming from the Remote Sensing Division of the National Oceanic and Atmospheric Administration (NOAA). The standard NOAA and other organizations helped set highlighted the importance of having historic and post-event data at hand for analysis, flexible operations based on that data for everyday activities and strong connections to impacted communities and relief workers.
A decade and a half later, climate change has dramatically increased the ferocity, pace and volume of natural disasters such as storms, floods and fires – creating greater strain on logistics-based relief efforts. Fortunately, mapping technologies, predictive data analytics and communications capabilities have evolved at a relatively similar pace. Entrenched GPS navigation software apps are already helping people maneuver around crowded thoroughfares.
Today, the transportation and logistics (T&L) industry finds itself in a pivotal position to play a substantial role in aiding crisis efforts – and mitigating the effects on communities and their citizens – more than ever before.
Specifically, T&L enterprises – in conjunction with government agencies, non-governmental organizations and volunteer organizations – are now at the forefront of creating virtual collaborative communities that can better assist relief efforts during natural disasters by:
● Shipping supplies to precisely targeted areas before an event occurs.
● Ensuring the goods are distributed in a timely matter to citizens and relief organizations during a crisis.
● Helping recovery efforts after disaster strikes.
To be sure, it’s impossible to predict some natural events such as earthquakes and wildfires, frustrating urgent relief efforts and timely distribution of warehoused critical supplies. Northern California retailers, for example, quickly ran out of air purifiers and breathing masks within two days of the mid-November 2018 Camp Fire that wiped out the town of Paradise, and rendered the usually fresh San Francisco Bay area air practically unbreathable for more than a week.
But mapping, location and communications tools can be extremely helpful in logistical efforts to mitigate delays and promote quicker disaster response. That’s especially true if these efforts are coordinated among different sectors and groups – such as governments, universities, nonprofits, etc. – in an open and public way.
Cloud-based mapping is already the go-to tool to assist first responders and citizens during disasters. As one of many examples, both Houston and Miami embraced the power of data-driven solutions and mapping to mitigate the threats against public health and safety in hurricanes Harvey and Irma. Unmanned aerial vehicle (UAV) mapping was also deployed in these and other disasters, not only to process images of damaged areas but also to facilitate faster claims processes for insurance purposes.
Meanwhile, teams from NASA and Development Seed have developed Cumulus, a cloud-based platform that leverages open observation data and artificial intelligence (AI) to estimate a storm’s destructive potential six times faster than traditional processes – a huge help in preparing and planning for relief and rescue efforts.
The Open Data for Resilience Initiative (OpenDRI) is a World Bank initiative that has established prototypes for the type of collaborative, data-driven disaster risk management initiatives we’re advocating. In addition to creating a checklist of 10 guiding principles for the effective use of risk data, the World Bank is leveraging the global open data movement to manage disaster risk, including:
● Partnering with the United Nations, the Red Cross, Google, Amazon and Microsoft to use data about floods, droughts and migrations to prevent famine across the globe and mitigate its effects.
● Using information and communication technologies (ICTs) to map the future of humanitarian aid.
● Organizing community-based mapping events that, for example, recently created geospatial data to help the city of Accra, Ghana, prepare for and respond to flooding.
Smarter, efficient logistics
In the United States, we’re continuing to learn from the lead of the World Bank and the developing countries it is helping, especially when it comes to leveraging mapping data, weather data, telemetry data, data modeling and predictive analytics to bolster logistical efforts during disasters. For example:
● Transportation networks can be programmed to identify shelters and locations of key services.
● Government and public-service agency networks can pinpoint vulnerable populations, locate where people might be trapped, identify their evacuation routes and predict where they will gather based on such elements as topography and vulnerabilities of critical infrastructures. The Catholic Charities USA Disaster Operations map is a good example of this, as was this post-Hurricane Maria map of Puerto Rico.
● Maps can be updated in near real-time and with vivid detail to reflect changes in roads and pathways that disasters have altered, and which evacuation/escape routes are most crowded.
● Emergency response teams can better understand where they can and can’t move, where food and goods are most needed and how to get them on the ground.
The unfortunate reality is that the frequency and severity of many types of natural disasters are only increasing. The fortunate news is that data-driven mapping, open communities, telemetry and analytics technologies will continue to evolve and enable streamlined logistical planning and more efficient disaster response.