A New Perspective on the World: Geospatial Data
The expansion of artificial intelligence into all areas of life has reached near ubiquity in the modern era. Namely, advances in machine learning within the field of data science has revolutionized our ability to process and analyze the endless heaps of data we now have at our disposal. For humans, analyzing a massive amount of data hinders our ability to draw connections and derive insights from its entirety; however, AI is able to easily identify obscure trends and patterns present in large amounts of data that would be imperceptible to human eyes.
Additionally, a large dataset seems cumbersome to sort through for a human analyst, but is a boon for training neural networks. One such source of data comes from our ever increasing accumulation of satellite imagery.
A substantial decline in satellite launch costs coupled with the emergence of new technologies such as inexpensive nanosatellites and synthetic aperture radar (SAR) has resulted in a deluge of geospatial data, or data with an associated geographical component. Previously, geospatial data was both difficult and costly to obtain, used primarily by the military or intelligence agencies. However, the development of new deep learning techniques and our exponentially increasing computing power has allowed us to process this mass of data, driving what is now being called, “The Geospatial AI Revolution.”
Since the democratization of geospatial data, corporations, institutions, and governments have all come to realize its immense potential in guiding their decisions. For example, it is common knowledge that data drives the retail industry. Companies such as Amazon or Target are able to make personalized recommendations to consumers based on their past searches and purchases. Relying on buying habits alone, Target was infamously able to deduce a teenage girl’s pregnancy before her own father.
Additionally, many firms have developed algorithms that monitor social media and search trends to predict future demand for certain products. However, unbeknownst to most, geospatial data is now being added to many companies’ arsenals of data. The growing usage of geospatial data is allowing retailers to peer further into our personal lives and how they might subtly coerce us to purchase their products.
Specifically, geospatial data provides firms with socioeconomic data such as average annual income, housing prices, local business performance, population, and age, as well as information like foot traffic or future construction plans. Utilizing these statistics, retailers will be better able to target specific regions and groups of individuals through store and advertisement placement or product choice.
Another advantageous usage of geospatial data occurs in the realm of healthcare, more specifically, in the study of spatial epidemiology. Knowing the location of clean sources of water, environmental hazards, or disease breeding grounds has proven to be invaluable information in predicting where the greatest healthcare needs will be, but more importantly, it allows epidemiologists to focus on disease prevention rather than treatment. For example, geospatial technology is being used in Africa to detect and locate piles of scrap tires, a known breeding ground for disease-ridden mosquitoes.
Additionally, this data has been instrumental in capturing the location and potential health risks of nomadic pastoralists, one of the world’s most elusive and least served populations. Due to their migratory nature, they often lack proper access to medication and vaccinations, resulting in many preventable deaths. The application of geospatial technology allows health workers to better track the migratory patterns of these nomadic tribes and deliver appropriate medical treatment and vaccinations to them.
Returning to the more mundane, geospatial data also assists healthcare providers by informing them about changing environmental influences or the locations of high-risk areas, allowing them to better decide where to deploy their limited amount of resources in order to provide the greatest benefit. Using just retail and healthcare as two prime examples, geospatial data can be universally serviceable to all fields.
The ability to visualize and organize the world both spatially and temporally has allowed us to discover complex trends between people and places across the globe. Geospatial analytics has transformed our ever increasing mound of data into a bird’s eye view of the world around us, opening our eyes to an entirely new perspective of the world and augmenting the awareness of governments and corporations alike.
Written by Kevin Ma & Edited by Alexander Fleiss
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