Data Driven: GIS Guiding the Future

Troy Lambert

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The visualization of data is the power of GIS and mapping systems. Presenting a CEO or CMO with another flat spreadsheet or database filled with numbers might be effective, but it may also induce sleep. Clients of nearly any business need to see what you can do and what all those numbers mean.

Maps are often one of the easiest ways to do this. It is one thing to say “we have remote employees in 23 countries.” It is another to map those employees, dramatically illustrating a company’s reach. There are dramatic ways maps are guiding the future of nearly every business around the world.

 

Mega-Mapping

Despite the recent trend toward nationalism, we still exist in a global economy and deal with global issues such as climate change, population growth, terrorism, cyber security, and poverty. The more data we have about these things, and the more precise we can be with location data, the easier it is to visualize and come up with solutions to these issues.


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The Globally Remote Workforce

In the global economy, more companies are outsourcing work to freelancers. With the growth of technology in connectivity, the issues of managing remote workers have become simpler to deal with. A big part of this is data driven. We can use analytics to deal with issues from global payroll to monitoring productivity and the return on investment (ROI) from expanding operations into global markets.

This can be achieved using a couple of mapping methods, including mapping social media and marketing reach. Comparative data and mapping can be used to determine which of these efforts are the most effective, and where marketing reach needs to be improved.

Climate Change

Mapping climate change globally is nothing new, but as we add more data and more high resolution imagery, we get a better picture of the effect of local efforts on the overall global issue. We also begin to see new weather patterns so we can be more responsive both globally and locally.

This color-coded map displays global temperature anomaly data from 2014. Credits: NASA's Goddard Space Flight Center
This color-coded map displays global temperature anomaly data from 2014.
Credits: NASA’s Goddard Space Flight Center

Proper data driven mapping allows us to be proactive rather than reactive to changing weather phenomena and other environmental issues, including light pollution and industrial impacts, preventing negative outcomes rather than engaging in cleanup efforts after the fact.

Aerial Image of the GTA, showing light pollution hotspots in white light. Major streets and Highways can clearly be identified.
Aerial Image of the GTA, showing light pollution hotspots in white light. Major streets and Highways can clearly be identified.

Cybersecurity and Terrorism

Hacking has always been a global issue, but the recent release of the Vault 7 documents shows that cybersecurity is a global issue in need of attention from individuals, businesses, and governments.

Mapping is useful here as well. We can map targets, the source of hacking or terrorist efforts, and make correlations between countries, organizations, and individual targets. This data allows decision makers to establish virtual data back-up plans, institute new security measures, and ensure employees and decision makers are following them.

It also allows us to see correlations. Where have attacks come from and where have they targeted with some frequency or regularity? Those patterns are likely to repeat themselves, and we can issue warnings and establish threat levels that are data based.

The more data we have, the more proactive we can be about protecting assets, data, and citizens from malicious efforts of many types.

Poverty

Where are humanitarian efforts most needed? Where should we locate resources so they have the largest impact? These are all questions that can be answered most effectively by data-driven maps. Facebook has helped create one of the most comprehensive population maps for reasons of their own, but it also effectively mapped economic status, and enabled us to add information to an already immense dataset.

Despite the recent vilification of poverty in the United States, it continues to be a global humanitarian issue. Allocating resources so they are most efficient is all about location, and situating them to have the most impact per dollar requires rich income data as well.

Estimates of per capita consumption in four African countries. Stanford researchers used machine learning to extract information from high-resolution satellite imagery to identify impoverished regions in Africa. (Image credit: Neal Jean et al.)
Estimates of per capita consumption in four African countries. Stanford researchers used machine learning to extract information from high-resolution satellite imagery to identify impoverished regions in Africa. (Image credit: Neal Jean et al.)

Micro-Mapping

With the rise of autonomous vehicles, the need for high-resolution micro-mapping is on the rise. But this is by far not the only application for this precise technology. Construction site mapping, environmental rehabilitation and research, and even pre-screening and geolocating historic maps for archeology sites require this kind of data.

LiDAR reveals the underlying history of a landscape.  Image from Kate Johnson.
LiDAR reveals the underlying history of a landscape. Image from Kate Johnson.

Sub-Meter Mapping

So how are we getting sub-meter mapping? There are a couple of ways we are gathering and utilizing this imagery.

Small Satellites: Many companies are launching small and inexpensive satellites that, among other things, take real-time, high-resolution imagery of the Earth in various areas. This footage, besides being insanely detailed, also allows data to be more current, able to be updated as often as every seven days or in some cases even less.

Drone Imagery: Nearly every type of camera or imaging device can be attached to a drone, and used at low elevation with the proper filming angle or angles, an area can be mapped precisely with just a few strategic flights and overlaying the raster files.

An aerial image of Nepal earthquake zone, from volunteered drone user (UAViators)
An aerial image of Nepal earthquake zone, from volunteered drone user (UAViators)

Using one of these two types of imagery or a combination of both, vital information can be created and utilized in a number of scenarios.

As to autonomous vehicles, in large part, navigation will be sensor based as much as it is informed by background mapping. The data gathered by the car sensors can then be transmitted to improve the accuracy of mapping. In other words, precise mapping informs autonomous vehicles, and the vehicles also inform the map, making the trip for the next vehicle even easier.

There are many more applications of micro-mapping: automated drone delivery, crime prevention and security, disaster relief, damage assessments and more.

The beauty of micro-mapping and mega-mapping is that they inform each other: mega-mapping gives us an overall global picture in which to place micro-data, and micro-mapping data makes mega-mapping more accurate.

Mapping has always been data driven, and the more data we gather, the more important practical visualization of that data becomes. Mapping is a vital part of that visualization process.

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About the author
Troy Lambert
Troy Lambert is an author and editor who began using GIS for historical research at a museum He prides himself on thinking of new ways GIS can be used to tackle issues or approach them in a different way. He lives and works in Boise, Idaho with his fiance, 13 year old son, and two very bright dogs.