Big data is a powerful tool for tackling climate change – humanity’s greatest challenge in the 21st century. Geospatial data is a form of Big Data that is drastically improving mitigation/adaptation strategies for climate change and increasing the likelihood that we collectively accomplish the Sustainable Development Goals. By giving businesses and governments a firm understanding of evolving mobility patterns and spatial relationships, geospatial intelligence can decrease resource consumption, lower pollution and carbon emissions, enhance our resilience to climate-induced natural disasters, and more.
Researchers, businesses, and government agencies leverage mobile location and Point-of-Interest (POI) data to advance sustainability. Let's look at some of these use cases.
Sustainable cities
Cities generate 70% of global carbon emissions and the lion’s share of air pollutants. Lowering the carbon intensity and broader environmental impact of urban settlements cannot be achieved without drastically reducing people’s reliance on private transportation. To that end, establishing far-reaching and accessible public transportation networks is vital in the fight against climate change and environmental degradation.
Through location intelligence, we can enhance our understanding of urban spaces and harness these insights to create accessible public transit systems.
Transportation agencies can use location data to identify popular travel routes, evaluate gaps between transit supply and demand, and isolate low-density routes that would be better served by resource-efficient and environmentally friendly microtransit solutions. This is exactly what transit consultancies like Innovate Mobility are doing. Using Quadrant’s high-quality location data, Innovate mobility derived actionable intelligence for the City of Fairfield California (public transport department). This analysis help the city secure $1 Million in funding to build more accessible, resilient, and sustainable public transit systems.
Traffic monitoring systems can also leverage location data to identify high-congestion routes. These insights can be used to formulate strategies that improve traffic management in a way that meets people's demands while minimizing environmental impact. 
The image above highlights high-activity areas in Manhattan. Visual, location-based insights like this can enable transport authorities to decrease congestion levels and increase the use of existing infrastructure.
Enhancing resilience to natural disasters
According to the UN, climate change has caused a five-fold increase in the frequency of natural disasters and extreme weather events over the past 50 years. Geospatial data can play a huge role in enhancing our preparedness to deal with natural disasters and inform response and rehabilitation strategies.
Researchers from the Asian Development Bank (ADB) used Quadrant’s location data to study the aftermath of a 6.5 magnitude earthquake that struck Maluku Island (Indonesia) in 2019. Their mobility-based studies proved that location intelligence can inform highly effective disaster management and response strategies – thereby reducing the socio-economic and environmental impacts of similar events in the future. 
The figure above is an activity heat map (generated via location data) for Ambon for an average 24-hr period in Sep 2019. It has been color coded to reflect activity (yellow areas have the greatest number of people).
Geospatial data can help governments reduce the risk associated with a natural disaster or extreme weather events. Most recently, researchers from leading universities have used Quadrant’s location data to study the aftermath of Hurricane Ian. Studies like these can help improve preparedness, identify vulnerable populations, and reduce property damage.
Reducing the environmental footprint of supply chains operations
Around 80% of carbon emissions from Consumer Packaged Goods (CPG) companies come from supply chain operations.
Geospatial data can be used to enhance supply chain efficiency in several ways.
The carbon footprint of logistics and last-mile services is quite high because these industries expend a lot of fuel. By taking shorter, more fuel-efficient routes, businesses in these spaces can lower operational costs and enhance workforce productivity while decreasing their carbon-intensity.
High-quality and regularly refreshed POI (Point-of-Interest) datasets can act as the building blocks of well-optimized navigation systems. When drivers know how to get from point A to point B via the shortest route possible, their vehicles emit less carbon because they are spending less time on the roads. This applies not only to retail logistics but last-mile delivery as a whole.
To gauge the efficiency of their supply chain networks, firms can use POI data alongside the historical mobility data of their customers and suppliers. Insights from such analyses allow businesses to move or expand distribution centers and other supply chain nodes to areas with higher demand, greater proximity to raw materials, and shorter routes. As a result, companies can significantly decrease fuel consumption and slash the carbon footprint of their operations.
Facilitating the adoption of EVs
Road transport accounts for a whopping 15% of global carbon emissions. Electric Vehicles (EVs) are a promising solution to reign in emissions from road transport; however, for EVs to become practical for personal and commercial use, there must be an extensive network of charging stations that can fulfill escalating demand.
Governments and EV manufacturers can execute mobility-based studies to identify locations with the greatest need for charging facilities. This demand-based approach will allow them to optimize resource allocation and gradually expand coverage over large geographies.
The locations of charging stations must be mapped and updated regularly so that EV owners have access to reliable information. During a pilot project for a leading mapping company, we collected and verified the locations of 5000 EV charging stations across Amsterdam – in person. In doing so, we discovered that >14% of locations within the city’s database were inaccurate, while 11% of data from a popular mapping app was outdated.
Providing individuals and businesses with accurate, up-to-date, and contextual charging station data will go a long way in fast-tracking EV adoption.
The scope of geospatial data, as it pertains to advancing sustainability initiatives, is quite vast. With time, businesses and governments will be subjected to even greater pressure from consumers and citizens to achieve carbon neutrality. To respond to these demands, they must leverage geospatial intelligence to decrease the resource intensity and environmental impact of their services and operations. By doing so, they will make meaningful strides in containing climate change, preserving non-renewable resources, and reversing environmental degradation.
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