GeoSTEM in CONTEXT
CLICK HERE to view an abbreviated Chronosequence in GeoSTEM

So many STEM fields converge around geospatial science and technology that we have come to refer to this simply as the GeoSTEM convergence.  Everything on or around our planet, by definition, exists in space and time.  As such, it should come as no surprise that Geography and Geospatial Science and Technology stand at the center of many STEM fields that either underpin Geography, grew out of Geography, were fueled by advances in geospatial technologies, or exist because of the fusion of geospatial technologies with other fields of science and technology.

 

This paper seeks to put all of these GeoSTEM related fields in context, through a short historical survey of how and why each of these STEM fields began, and how they built on each other.  Context matters, and even if one doesn’t have the scientific, technical, engineering, or mathematical background to understand the details of how each works, all of us are capable of understanding how they relate to our complex, ever changing world.  As we collectively make investments in the next generation STEM workforce, understanding the central role that Geography has played in anchoring STEM learning in our real-world lived experience is critical.

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ANCIENT ROOTS OF GeoSTEM

 

People often forget that the creation of the first map was itself an innovation, introducing a fundamentally new technology to humanity.  The first maps, just as modern maps today, did two things - they communicated information and they coordinated action.  

 

The oldest surviving map, the Nippur Map Tablet, a clay tablet from around 1500 BCE, is a hyper-local map of an area near the Babylonian city of Nippur, Iraq.  No doubt it was not the first map created by a human, given that a Sumerian building floor plan from circa 3000 BCE has been discovered on a clay tablet.  Few other tablets have been found that are older than that.  Communicating information and coordinating action are essential human traits.  Organizing a hunt, planning a migration trek, protecting a settlement against invaders, tax assessment, and the planning of agricultural production – the group with reliable and detailed maps no doubt enjoyed certain benefits.  

 

There is actually good science suggesting that humans were creating maps as far back as the Upper Paleolithic, more than 10,000 years ago, before cities and urban civilization.  Scientists have uncovered engravings and paintings in the Abauntz Cave (in Navarra, Spain) from the Late Magdelinian era, from perhaps 13,000 years ago.  The Magdalenian map depicts a landscape including mountains, rivers, and ponds, with possible routes or avenues to different parts of the Geography.  These early humans communicated spatial information geographically leveraging the power of maps.

 

From these cave engravings and paintings to the clay tablets of Mesopotamia, the coordination of increasingly complex human activity required organizing and communicating knowledge using location as a central principle.

 

Of course, as civilizations became interconnected, the geographic extent of maps expanded, for similar reasons.  The oldest surviving world map, the Imago Mundi world map, also known as the Babylonian Map of the World, dates back only to around 600 BCE.  

 

Maps are a fundamental human technology with ancient roots.  Just like the formation of language (e.g., verbal communication, alphabets, etc), the increasing capacity to make maps represents an ongoing competitive advantage for human advancement and is similarly so ingrained in the essence of being human that it is now impossible to separate from our core DNA.  The value of these early maps inspired millenia of continuous improvement, spawning all manner of GeoSTEM innovations, which we will address below.

 

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Census Taking

A census is a complete count of a population, including its size, location, and characteristics. The word "census" comes from the Latin word cēnsus, which is derived from cēnsēre, meaning "to assess, appraise, or give an opinion".  It is not a surprise that one of humanity’s early geographic activities was census taking, which provided a rigorous accounting of how the ever changing number of people within a country was distributed across geographic space for administrative purposes.  The history of census taking can be traced back thousands of years, with the first known census being taken by the Babylonian Empire around 3800 BCE. The Romans conducted censuses every five years, starting in the 6th century BC, as they annexed new lands, and grew organically. The census was used to determine taxes and keep track of the population.  The Han Dynasty (202 BC – 9 AD, 25–220 AD) recorded the oldest surviving census data, which showed a population of 57.7 million people in 12.4 million households.  Today, a regularly conducted decadal census is a leading indicator of a country’s development and governmental stability.  The lack of a regular census is often due to conflict within a society, where the powers that be do not see an accurate census count to be useful to their particular aims.  While censuses have historically been conducted by door to door census takers, and the filling out of census forms sent to a fixed address, increasingly advanced geospatial technologies are being used to characterize our ever changing global population regardless of the status or quality of an individual country’s census organization.

 

Cadastre Surveying

It makes sense that practical techniques and technologies for mapping began at the local level, providing the origins of simple cadastral surveying systems used to establish boundaries for arable land plots in Egypt around 3000 BCE.  After the annual flooding of the Nile, this system was required for farmers and authorities to recover the boundaries between plots.  As part of this process, the Egyptians also created the first surveying instruments, including the plumb board, A-Level, T-Level, and plumb square, around 2600 BCE.

 

Astronomy

Humans’ ability to reliably geolocate our position on earth, and therefore our ability to navigate, was originally based on astronomical calculations.  The Babylonians in ancient Mesopotamia recorded astronomical observations as early as 1600 BCE, including the positions of planets and times of eclipses.  There is even evidence of primitive star drawings by prehistoric people in Siberia between 8,000 and 12,000 years ago.  Over time, multiple cultures around the world seemingly independently built reliable astronomical calendars that enabled precise temporal stellar observations that served as a foundation of geo-enablement.  To this day, star trackers offer reliably precise position information, on the ground, at sea, in the air, and even for satellites in space. 

 

Geometry  

The centrality of geometric calculations to Geography goes all the way back to Eratosthenes (of Cyrene), before 200 BCE.  His calculation of the Earth’s circumference was remarkably accurate, and he was the first to calculate the Earth’s axial tilt.  He also utilized the same geometric tools to create the first global projection of the world, incorporating parallels and meridians.

 

Trigonometry

While Eratosthenes harnessed the power of Geometry to characterize our planet as a sphere, along with its orientation in space, the same metes and chains that he used to measure the distance between towns served as the foundation for future generations engaging in trigonometric analysis of the Earth’s terrain.  Whether for land surveying, building and infrastructure construction, or determining distances for meteorological observations, or projectile trajectories, ever more sophisticated trigonometric azimuth tools were required.  For centuries, many rudimentary instruments (e.g., groma, geometric square, dioptra, various graduated circles/circumferentor, and semicircles/graphometer) were used to obtain vertical or horizontal angle measurements.  Over time, the functions of these instruments were combined into a single instrument (called a theodolite as early as 1571 AD) that could measure both angles simultaneously.

 

Design in 3D Euclidean Space

These tools allowed for surveying our planet in ever more precise terms, helping us better understand Earth’s sphere as an ellipsoid.  They also allowed for designing structures in 3D Euclidean space, and situating them within the larger landscape such that infrastructure such as roads, walls and aqueducts joined precisely and accurately.

ISLAMIC GOLDEN AGE INNOVATIONS

 

Europe lost much of its classical knowledge from the ancient world after the fall of the Roman Empire in the fifth century, in what became known as the Middle Ages, or Dark Ages.  This includes classical knowledge about Geography and its related fields of astronomy and mathematics.  However, during this period, much of this knowledge was not only preserved within Islamic cultural centers.  It was actually reimagined and advanced during the Islamic Golden Age.  The work of major Islamic thinkers during this period is illustrative. 

 

Muhammad ibn Musa al-Khwarizmi (c. 780 – c. 850 CE) was a Persian polymath whose contributions to mathematics, Geography, astronomy, and cartography established the basis for innovation in algebra and trigonometry. His systematic approach to solving linear and quadratic equations led to algebra, a word derived from the title of his book on the subject, Al-Jabr.  He also made important contributions to trigonometry, producing accurate sine and cosine tables and the first table of tangents.  The term ”algorithm” comes from the Latin translation of his name - Algoritmi for al-Khwārizmī.  Al-Khwarizmi produced a set of astronomical tables and wrote about calendric works, as well as writing about the astrolabe and the sundial.  (Astrolabes were crucial in fomenting the Age of Exploration, hundreds of years in the future. Astrolabes could not only show the positions of stars and planets, but also tell the latitude, local time zones, and angles of the stars.  This allowed explorers to determine where they were during their voyages.)  Al-Khwārizmī systematized and corrected Ptolemy's data for Africa and the Middle East. Another major book was Kitab surat al-ard ("The Image of the Earth"; translated as Geography), presenting the coordinates of places based on those in the Geography of Ptolemy, but with improved values for the Mediterranean Sea, Asia, and Africa.  Al-Khwārizmī assisted a project to determine the circumference of the Earth and in making a world map for al-Ma'mun, the caliph, overseeing 70 geographers.

 

Islamic Golden Age astronomical insights continued.In 994 CE, Abu Mahmud Hamid ibn Khidr al-Khujandi, a Muslim Transoxanian mathematician and astronomer, built a massive mural sextant of his own invention near Ray, Iran, intended to determine the Earth’s axial tilt (“obliquity of the ecliptic”) with much more accurate calculation - and was off by just two minutes - a level of accuracy that had never before been attained.

 

The Moroccan scholar Muhammad Al-Idrisi (c.1100-c. 1165 CE) was one of the great Arab Muslim geographers and cartographers. Escaping conflict and instability in Al-Andalus, al-Idrisi joined contemporaries such as Abu al-Salt in Sicily, where the Normans had overthrown Arabs formerly loyal to the Fatimid Caliphate, serving in the court of King Roger II at Palermo, Sicily.   Sicily then was a cultural melting pot for the Muslim-Arab and West Europe.  There he created the Tabula Rogeriana in 1154 CE, after 18 years at court, one of the most advanced medieval world maps, incorporating knowledge of Africa, the Indian Ocean and the Far East gathered by Islamic merchants and explorers and recorded on Islamic maps with the information brought by the Norman voyagers to create the most accurate map of the world in pre-modern times,  

 

Both al-Khwarizmi and al-Idrisi (and others) built on Ptolemy’s ancient work (85-165 CE), but benefited from cartographic tools and techniques such as stenographic projection, and innovations in the field of navigation (like the astrolabe, above) developed in the intervening centuries, enabling them to achieve a far higher level of precision and accuracy.  The Islamic Golden Age went far beyond merely preserving ancient geographic knowledge, and advanced all the related GeoSTEM fields in powerful ways, which in turn reinvigorated European geographic traditions, enabling the Age of Exploration from the 15th to the 17th century.

 

Perhaps a less obvious contribution of the Islamic Golden Age to future incarnations of the field of Geography is the field of optics.  The field of optics has its foundation in the primitive lenses of the ancient Egyptians and Mesopotamians, logical concepts of Ancient Greek philosophers and simple geometrical optics of figures from the ancient world such as Euclid, Ptolemy, and Hero of Alexandria.  

 

In the future, telescopes became essential for the advance of the field of Geography, whether to look up at the stars, off into great distances, or down from airplanes and satellites with more precision and accuracy.  For telescopes to continuously improve in their quality and their ability to convey distant features without distortion, the field of optics was required.  The mathematics underpinning the field of optics included vector algebra, analytic geometry, differential and integral calculus, real analysis, complex analysis, differential equations, partial differential equations, tensors, and differential operators such as gradient, divergence, and curl.  Over time, this allowed for any given lens to be characterized very precisely and accurately, which in turn allowed for observations from optical devices to be more reliable and at greater distances.  All of this was by the Islamic Golden Age, which gave us revolutionary ideas in the field of optics from luminaries such as Abu Ali al-Hassan Ibn al-Haytham, whose Book of Optics laid the foundations for the modern understanding of optics and continues to influence optical theory and design today.

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18th AND 19th CENTURY INNOVATIONS

 

Telescopes

While there is evidence that the principles of telescopes were known in the late 16th century, the first telescopes were created in the Netherlands in 1608 when spectacle makers Hans Lippershey & Zacharias Janssen and Jacob Metius independently created telescopes.  After John Sisson first combined the telescope with the other components of a modern theodolite in 1725, such trigonometric survey devices vastly improved the geographic rigor underpinning our maps and navigation.

 

Marine Chronometer

In response to the prizes established through an Act of the British Parliament (the Longitude Act) in 1714 (administered by the Board of Longitude), Englishman John Harrison's 1730 marine chronometer solution revolutionized navigation and greatly increased the safety of long-distance sea travel.  The many inventors who responded to this prize represent the first wave in a long line of inventors who helped create the precise timekeeping at the core of what we now call Position, Navigation, and Timing (PNT), and which today we all simply assume as a given, with GPS built into our phones.

 

Geology and Paleontology

Precise surveying instruments (like theodolites) gave birth to geological insights that quickly launched an entirely distinct academic field of inquiry.  As told in Simon Winchester’s book “The Map That Changed the World,” William Smith’s work as a surveyor supporting the engineering of canals and mines led him to observe that the deeper – and therefore older – the strata were, the more the fossilized species within them differed from living organisms.  In 1799, Smith produced the first large-scale geological map by adapting agricultural mapping techniques for displaying layers of rocks horizontally, as strata.  Smith released the first geological map of most of Great Britain by 1815, stirring some controversy and intrigue within the Geological Society of London that had only been founded in 1807.  His work gave critical context for the emerging field of paleontology (a field that lies at the border of biology and geology, and a term created in 1822), and gave great support and impetus to the hypothesis of biological evolution that Charles Darwin posited in his 1859 book, the Origin of Species.

 

Biology

It would be glib to say that modern Biology was further dependent on Geography and geospatial technologies, due to the pioneering work of Alexander von Humboldt, the German polymath, geographer, naturalist, explorer and philosopher work at the dawn of the 19th century - as he invented the idea of “nature” and rooted it in his establishment of the field of bioGeography.  The truth is a bit more complex, and worth exploring.

 

The study of the diversity of life can be traced to Aristotle (384-322 BCE), and the Islamic Golden Age saw scholars contribute greatly to botany, anatomy, and physiology.  But, biology as a field has more modern roots.  The field of microbiology began to quickly develop with the invention of the microscope sometime prior to 1668 by Anton van Leeuwenhoek, a great contributor to the Golden Age of Dutch science and technology.  

 

But, the biology of how all living things in the natural world relate to each other has other roots.  Carl Linnaeus published a basic taxonomy of the natural world in 1735, showing how all species were related and connected, and introduced scientific names for species in the 1750s.  George-Louis Leclerc (later Comte de Buffon) suggested the possibility of common descent amongst these species, though was later forced to recant his view by the Church.  This is where the world of Alexander von Humboldt came in, as he helped us understand how all such species were connected in nature.  As told in Andrea Wulf’s book “The Invention of Nature,” von Humboldt’s pioneering scientific drawings and writings, and his quantitative work on botanical Geography, from his first explorations (1799-1804) laid the foundation for the field of bioGeography.  These scholars also gave great support and impetus to the hypothesis of biological evolution that Charles Darwin posited in his 1859 book, the Origin of Species.  It was not until Gregor Mendel’s work in 1865 that the basis for modern genetics began, as he outlined the principles of biological inheritance.  But one can see how even his work was enabled by this geographic grounding of biological understanding.

 

Public Health/Epidemiology/Medical Geography

Precise and accurate urban maps made it possible for Dr. John Snow, in 1854, to achieve scientific insights on the spread of cholera, by simply plotting instances of cholera, and determining that each drank water from the same water well.  This episode was key to establishing the “Germ Theory of Disease” which upended millennia of superstition and misguided science on how illnesses spread.  A century later, it was a decade-long study on the occurrence and spread of diseases by the American Geographical Society that led to the establishment of the modern Geographic Information System (GIS) vector data model.

 

Oceanography

Quite explicitly, the field of Oceanography was an outgrowth of the field of Geography, when AGS Councilor Matthew Fontaine Maury first published the book “The Physical Geography of the Sea” (1855).  By this point, mariners (both inland, and at sea) had been drawing nautical maps for thousands of years, often with very poor geolocation.  These had included not only detailed shorelines, but also depth estimations to ensure that the next ship to travel that Geography did not run aground.  Hydrography - or the mapping of bodies of water - came to include Bathymetry - or the precise mapping of the underwater terrain.  During the Age of Exploration, nation states funded maritime explorers to travel at great risk to new places, map them, lay claim, exploit their resources, and to return safely.  Maps were essential to this process, as land claims began in specific places where they disembarked from their sea voyages.  The wars that emerged between these great nations were over the legal claims staked and documented in these maps.  With the growing sophistication of these maps, the Age of Exploration gave way to regular lines of seafaring and commerce - so much so that the first insurer, Lloyds of London - insured these ships and their cargo.  Ocean maps were table-stakes in this growing business.  In the 20th century, oceanography went far beyond a physical cartographic process, placing the ever changing biological, chemical and physical flows and processes on what is now understood to be a continuously changing dynamic map of the ocean.

 

Space-Time Relativity

In the early 19th century, sophisticated surveying capabilities supercharged the spread of railroad lines across vast geographies creating very practical problems.  Due to the lack of any practical means for understanding varying times of day across vast geographies, there was no practical way to synchronize train schedules across lines of longitude (e.g., East/West lines of demarcation), leaving a train starting in one location to often hit a train starting in another location, leading to the loss of lives and money.  For time zones to be created in 1883, there first had to be a means for understanding time (say noon, or midnight) in different locations.  A young Albert Einstein in Germany experimented with measuring time using telegraph networks and with the coordination of clocks at train stations.  At the same time, the renowned French mathematician Henri Poincaré, president of the French Bureau of Longitude, mapped time coordinates across continents, and worked to build a global network of astronomical observatories capable of determining their precise and accurate location, and precise and accurate time at their locations.  When connected via a global Telegraph network capable of instantaneous communication, humanity finally had a rigorous infrastructure for solving such practical problems.  In order to understand this newly global world, they realized we had to determine whether there existed a pure time in which simultaneity was absolute or whether time was relative.

 

Meteorology

The earliest information about Meteorology dates back to 340 BC when Aristotle, the famous Greek scientist, wrote Meteorologica, a book that gave a summary of meteorology. The scientists who followed didn't do much on the study until about the 17th to 18th century when the thermometer and the barometer were invented.  Among other things, the barometer helped determine altitude - which is the z axis in the “x, y, z” taught in Geography.  Much of meteorology was based on such in situ measurements, even when they were taken aloft, such as with the first weather balloons launched by Léon Teisserenc de Bort, the French meteorologist in 1896, discovering the tropopause and the stratosphere.

 

While the airplanes of the early 20th century helped locate weather observations, it was the first weather remote sensing satellite, NASA’s Television Infrared Observation Satellite (TIROS-1), launched on April 1, 1960 that imaged weather over large portions of the Earth, allowing scientists and forecasters to directly observe the planet's weather systems for the first time. Since then, the combination of in situ, space based, and terrestrial Doppler radar have led to unprecedented meteorological insights.  It is important to note also that meteorology is essential to understanding and predicting atmospheric conditions impacting remote sensing signals.

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THE DIGITAL AGE

 

Photogrammetry

The dawn of photography and the dawn of flight were required before such geometric and optical methods could be applied to observations from above.  The extraction of precise and accurate measurements from overhead imagery in many ways depended on these same bodies of knowledge.  Increasingly accurate altimeters (derived initially from barometers) allowed for more precise calculations where “ground control points” had not already been surveyed.  The fields of military reconnaissance and precision targeting led to amazing innovations in the field of photogrammetry over the first half of the 20th century.  By the middle of the 20th century, these same methods developed for air photos were applied to satellite reconnaissance, and the larger academic discipline and civilian profession of remote sensing came into being.  Outside of classified “spy satellite” technology, this largely remained analog until the dawn of Landsat satellite remote sensing program.  Once digital, the ability to fit a pixel matrix to ground control points required algebraic quadratic equations.

 

Electromagnetic Spectrum

In the early 20th century, experiments with film photography demonstrated the ability to sense and visualize non-visual portions of the electromagnetic spectrum such as infrared and ultraviolet (eg, beyond red, green, blue).  Military investment in multi-spectral imaging for target identification and reconnaissance set the stage for a revolution in remote sensing.  After the first multi-spectral images were created, remote sensing scholars, students and practitioners had to master the science of the electromagnetic spectrum, and the chemical and biological phenomena that could be observed by combinations of different wavelengths.  The sensing of near-infrared, infrared and thermal bands quickly gave way to sensors capable to observing fine grained spectral differences across the whole range of the electromagnetic spectrum.  This led to powerful tools for geologists, agronomists, forestry, atmospheric chemists, oceanographers, environmental scientists, military intelligence professionals, and many others.

 

Sonar, Radar

Mapping ocean floors with sonar came from military investment during World War II.  Mapping the earth at night and in all weather became possible with the advent of radar, which was also an investment of military investment during World War II.  These were active forms of remote sensing, which sent energy into the world (eg sound waves, radio waves) in order to observe the returns (like an echo) and calculating the distance of the returns in ways that allowed for the fine grained characterization of the ocean’s bathymetry or the earth terrestrial surface (e.g., terrain).  Making sense of sonar and radar returns required Digital Signal Processing.  See below.

 

Radio Frequency (RF) Geolocation

During this same WWII era, scientists and engineers figured out various technical strategies for geolocating radio waves of their adversaries, in order to find spies.  As the variety of RF emitting devices has expanded, many new applications for geolocating radio waves have emerged.  These include search and rescue, air traffic control, and emergency response.  In recent years, this has expanded to space-based remote sensing of different kinds of RF emitters.

 

Plate Tectonics

Beginning in the early 1900s, various theorists unsuccessfully attempted to explain the many geographical, geological, and biological continuities and discontinuities between continents. In 1915, the meteorologist Alfred Wegener put forth his arguments for what he called “continental drift,” in his book The Origin of Continents and Oceans.  This idea was debated for decades, and culminated in 1960 in the modern theory of plate tectonics.  This was made possible by the deployment of modern instruments for mapping the ocean floor.  In 1947, a team of scientists led by Maurice Ewing utilizing the Woods Hole Oceanographic Institution's research vessel Atlantis and an array of instruments, confirmed the existence of a rise in the central Atlantic Ocean called the Mid-Atlantic Ridge, and characterized its geological composition.  This precipitated more ocean floor mapping missions of the ocean basins, detecting a system of mid-oceanic ridges, all along the globe that Bruce Heezen described with the concept of the "Great Global Rift," based on his work with the geologist and oceanographic cartographer Marie Tharp, producing the first scientific map of the Atlantic Ocean floor.  It was her cartography that revealed a more detailed topography and multi-dimensional geographical landscape of the ocean bottom, using the data from these modern sensors.

 

LiDAR

The first prototype of LiDAR, or light detection and ranging, was built in 1961 by a team at Hughes Research Laboratory, shortly after the invention of the laser in 1960. It functioned much like sonar and Radar, except using lasers.  The first commercial LiDAR was released in 1962.  The general public became aware of the accuracy and usefulness of lidar systems in 1971 during the Apollo 15 mission, when astronauts used a laser altimeter to map the surface of the Moon.  Decades later, NASA pioneered the airborne use of LiDAR for mapping on Earth, which by the end of the 1990s led to a growing commercial airborne photogrammetric mapping industry using LiDAR to map high resolution terrain. Making sense of LiDAR returns required Digital Signal Processing.  See below.

 

Digital Signal Processing

The reflections of our planet’s electromagnetic spectrum signals generated enormous amounts of non-visual digital data requiring new ways to be processed and interpreted for deeper patterns that could explain the many natural and human-induced phenomena occurring on our ever changing planet.  DSP required the use of trigonometric functions, complex numbers, complex analysis, linear algebra, and statistical methods.

 

Satellite Remote Sensing

Satellite remote sensing has always been a trade off between spatial, temporal, radiometric, and spectral resolutions.  Satellite remote sensing has been accomplished with electro-optical imagery, multi- and hyper-spectral imagery, radar, and even LiDAR (light detection and ranging).  To make sense of satellite imagery, one must understand baseline dynamics of the object/phenomenon under study and build sensor and platform characteristics (optics, physics, spectrum, and engineering) capable that are fit for purpose.  Whether narrow observations of specific places and specific times, or something as broad as the global Land Cover Land Use data provided by Landsat for the last half century, satellite remote sensing has fundamentally changed how humans think about our planet, and our personal relationship with part of our planet that had been inaccessible to human observation for the preceding hundreds of thousands of years of human existence.

 

Orbital Mechanics

Getting the first satellite into orbit required detailed understandings of the physics of gravity, thrust, and orbital mechanics - not to mention the countless fields of engineering - beyond aeronautical/aerospace engineering - required to build a successful rocket and satellite.  There are many orbits that are useful for different kinds of remote sensing satellites, and remote sensing strategies.  Geo-stationary orbits that are far, far from Earth allow very large satellites with huge optics to observe the Earth from a fixed location.  Sun-synchronous orbits allow particular remote sensing satellite constellations to always observe the Earth during daytime.  Thousands of small satellites now orbit in Low Earth Orbit (LEO), offering remote sensing and communications capabilities over the entire planet.  Polar orbits and high inclination orbits of different kinds have specialized value to different kinds of applications, and medium earth orbits are occupied by Global Navigation Satellite Systems (GNSS) like GPS.  When creating a new space application, complex trade-offs have to be made between the size, weight and power of the satellite, its capabilities, and the orbit it would need to be in in order to be effective, and what is required to launch it into that orbit.

 

Global Navigation Satellite Systems (GNSS)

GNSS began with the United States’ Global Positioning System (GPS), launched into orbit in the 1980s by the US military, and made available for civilian use in the 1990s.  These satellites, placed in very specific orbits that were calibrated against celestial observations, broadcast precise and accurate “Position, Navigation and Timing” data such that a GPS receiver on Earth that receives at least 4 of these satellite signals are able to determine their x, y, z, and t within tremendous precision.  GPS was such a success that Europe, Russia, and China decided that it was in their geopolitical self interest to have their own GNSS constellations known as Galileo, GLONASS, and Baidou, respectively.  GPS not only provides us precise and accurate positioning and timing information on the surface of the Earth, but also in the air, and in space itself.  Many satellites gather their positional information from GPS.  Orientation, of course, still must be determined by one or more of several methods, including startrackers.

 

Aeronautical/Aerospace Engineering  

The earliest aviators both demanded and created maps to enable the safety of aeronautical navigation.  These aviators were often eager contributors to airborne imaging, flying while taking photo surveys, which fueled the photogrammatric revolution which in turn generated ever better maps.  Aviators were also early adopters of GPS, which provided them superior understanding of their position and heading, and an ability to share this info with other aviators and air traffic controllers via radio broadcast.  Today’s aviators are voracious consumers of realtime geographic data from their “ownship” data, to air traffic data, to weather/turbulence data, restricted airspace notifications, alongside their aeronautical safety of navigation charts.  The increasingly busy business of space, and aerospace engineering, has a similarly insatiable appetite for geographic information, including that required for search and rescue.

 

Geographic Information Systems (GIS)

The first GIS was invented by Roger Tomlinson in 1963 with funding from the Canadian government, to create a manageable inventory of its natural resources, which, of course, were geographically distributed across the nation of Canada.  This revolution enabled people to encode their observations about the planet and phenomena occurring on/around our planet in points, lines and polygons which together composed digital maps.  Over time, other data types, such as rasters (or gridded coverages) were added to GIS, providing a bridge between remotely sensed data and digitized geometric data.  Countless GIS algorithms have been developed, and when married with remote sensing algorithms, has created a virtuous cycle of insight generation about our planet.   GIS is a powerful data science framework that allows all manner of mathematical operations to be applied to spatio-temporally encoded data.

 

Spatial Databases

With the explosion in digital computing in the 1960s, we saw the invention of databases, first with Charles Bachman’s creation of the Integrated Data Store in 1963 while at General Electric, followed by the Information Management Systems developed by IBM, Rockwell, and Caterpillar starting in 1966 for the Apollo Program.  The beginning of relational databases (RDBMS) was marked by E.F. Code’s 1970 paper “A Relational Model of Data for Large Shared Data Banks”.

 

This led to the creation of INGRES (Interactive Graphics and Retrieval System), a relational database model, by Michael Stonebraker’s team at the University of California, Berkeley, in 1974, which used the QUEL query language.  The System R project - which was the first to use Structured Query Language (SQL) - ran from 1975 to 1979 and was a massive success. Oracle’s first database was created in 1979.  In 1981, IBM announced its first relational database product, SQL/DS.  Informix (INFORMation on unIX) was also released by a company named Relational Database Systems in 1981. In 1983, IBM launched DB2 for mainframes, based on the same foundational developments. Sybase was invented in 1984. Stonebraker’s team later created Postgres (Post INGRES) in 1986, which after being abandoned, became an open source project that is wildly popular to this day. Illustra, with its proprietary fork of Postgres, was founded in 1992 by Stonebraker and current and former students.

 

What followed was a flurry of efforts to create bolt-on products that would take a regular database and make it spatial, but the beginning is hard to pinpoint.  The Oracle RDBMS first incorporated spatial-data capability with a modification to Oracle 4 made by scientists working with the Canadian Hydrographic Service (CHS) sometime after 1984, leading to a re-engineering or the Oracle kernel, resulting in the “Spatial Data Option” (SDO) in Oracle 7 in 1992.  Illustra’s Spatial Data Blade was made possible by Illustra’s extensibility model, with DataBlade modules that defined types and associated index methods, operators, and functions for purposes and data domains that included the management of geospatial information.  This was used on a massive NASA project in 1995, which led Illustra to sell to Informix in 1996.  Esri’s release of ArcSDE in 1995 came after acquiring the Spatial Database Engine (SDBE) from Salamanca Software Pvt Ltd, which took over development that previously started with Geographic Technologies Incorporated (GTI) in Australia. Many followed, including MapInfo’s SpatialWare (circa 1998), LaserScan, Autometric SQS, and notably, the creation of PostGIS (built on PostGres) in 2001, under Canadian government sponsorship.  Spatial databases have continued to evolve and be redefined over the past quarter century, but all have stabilized on using the Open Geospatial Consortium’s Simple Features standards (created in 1997) that specify a common storage and access model of geographic features made of mostly two-dimensional geometries (point, line, polygon, multi-point, multi-line, etc.) used by geographic databases and geographic information systems. 

 

Environmental Science & Justice

With roots back to the mid 1800s, the modern field of environment science developed during the 1960s and 1970s, in response to growing public awareness and concern about environmental issues. It is not a coincidence that one of the largest commercial GIS technology companies, founded in 1969, was named the Environmental Systems Research Institute, Inc. (Esri).  GIS and GIS analytics have not only enabled environmental science, but have made it possible to undertake complex environmental justice inquiries resulting in rigorous scientific data driven answers.

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21st CENTURY INNOVATIONS

 

Commercial Space-based Remote Sensing

The late twentieth century saw some of the first successes in government agencies launching remote sensing satellites and selling the data commercially, as well as commercial companies launching their own remote sensing satellites into space, and developing a business model around selling their observations of earth.  The first, SPOT 1 (Satellite pour l'Observation de la Terre), launched in 1986, was a commercial Earth-imaging satellite from CNES (Centre National D'Etudes Spatiales), the French Space Agency - a public agency selling imagery to the world.  RADARSAT-1 was an Earth-imaging radar satellite put in orbit in 1995 by the Canadian Space Agency, with subsequent RADARSATs launched in partnership with MDA (MacDonald Dettwiler Associates Ltd.), making Radar data available to the world.  Space Imaging in the United States launched IKONOS in 1999, as the first commercial satellite with sub-meter resolution imagery.  In 2001, Digital Globe put QuickBird in orbit, built by Ball Aerospace with marginally better resolution than IKONOS.  GeoEye-1 made orbit in 2008, also providing sub-meter resolution imagery.  Digital Globe built several more in the WorldView series of satellites in 2007, 2009, and 2014.  Collecting everything from panchromatic imagery to multi-spectral imagery (and often both), these satellites were very large “school bus” sized satellites with huge optics that operated in distant orbits.

 

All of this pioneering effort, which involved several failures on the path to success, layed the groundwork for the Low Earth Orbit (LEO) smallsat revolution.  Skybox Imaging put its first high resolution smallsats in orbit in 2013.  Later acquired by Google, then sold to Planet Labs, these high resolution SkySats live on.  At roughly the same time in 2013, Planet Labs put its first “Dove” cube-sats in orbit, providing lower (3-5m) resolution, with the intent of launching hundreds that would serve as a “line scanner for the Earth” that would image the entire earth once a day - a goal which they quickly succeeded at with no financial support from the US government, which had never been done before.  More and more commercial remote sensing companies have since made orbit, providing electro-optical/ imaging (e.g., BlackSky, Satellogic, etc.) and additional phenomenologies like Synthetic Aperture Radar (e.g., Capella Space, UMBRA, ICEYE, etc.) and multi-/hyper-spectral (e.g., RapidEye, Pixxel, Orbital Sidekick, etc.), and Radio Frequency (e.g., Spire, Hawkeye 360, etc.).  And in 2025, Very Low Earth Orbit (VLEO) companies will be demonstrating unprecedented high resolution imagery with unprecedented revisit rates, transforming the value of space based remote imaging yet again.

 

All the while, national space agencies such as NASA, the European Space Agency (ESA), Indian Space Research Organisation (ISRO), Deutsches Zentrum für Luft- und Raumfahrt (DLR), Israeli Space Agency, Japan Aerospace Exploration Agency (JAXA), China Aerospace Science and Technology Corporation (CASC), have also been continually innovating in the remote sensing satellites they put on orbit over this explosive era in commercial remote sensing.

 

Geospatial Web Services

The world of geospatial web services has been defined, by and large, by the history of the Open Geospatial Consortium.  While different companies, university researchers, and governments have advanced geospatial web services since the dawn of the WorldWideWeb (www) in the early 1990s, it has been the OGC that has enabled all of these innovators around the world to collaborate and generate common interoperability standards to have their core geospatial capabilities interoperate over web services.  The OGC’s Web Map Service 1.0 was created in 1999 after two years of collaborative interoperability testbeds amongst various companies and government agencies, allowing a single application to consume digital map layers from different vendors’ and open source implementations over the Web in real-time.  In the early 2000s, the growing global OGC community generated an entire architecture of interoperability standards that enabled interoperability across map layers, geospatial features, gridded coverages (rasters), metadata, sensor observations/tasking, and much more.

 

As information technology standards have evolved, so has the OGC architecture, with a modernized suite of standards based on OpenAPI/REST/JSON replacing the older architecture beginning in 2018.  The OGC architecture now enables the interoperable streaming of high resolution 3D geospatial data, the management of all manner of connected systems (e.g., sensors, things, robots, drones, satellites, devices, and platforms from all domains), and more (see below)

 

Global Gridded Population

The 1990s saw the creation of global gridded population datasets that rigorously tracked the growth and movement of human population across the entire world at relatively high resolutions (say 1km x 1km pixels).  Satellite remote sensing constellations such as LandSat provided consistent global grids that could be processed and interpreted to give a systematic means of tracking change on the Earth’s surface.  The methodologies for generating these global gridded population datasets evolved quickly, to integrate various datasources in pursuit of ever more precise and accurate accountings of population.  The NASA Socioeconomic Data and Applications Center at Columbia University generated a Gridded Population of the World used widely.  WorldPop has been another source of open spatial demographic data.  Perhaps more comprehensive is LandScan, maintained by Oak Ridge National Laboratory, which has tracked change in human populations for a quarter of a century.  Others, such as the European Space Agency, have sought to retrospectively create historical global gridded population datasets that reach back to the dawn of LandSat some 50 years ago.  These datasets have become powerful imputs into AI models that help us understand the grand challenges facing our planet (see GeoAI below)

 

OpenStreetMap

As the largest and most accurate open geospatial database, built with data contributions from millions of users worldwide, OpenStreetMap has created in 2004 as a platform that lets everyone gather observations about our ever changing planet.

 

OSM mapping provides a baseline for the critical element of using the “macroscope” (as AGS President Emeritus Jerry Dobson termed it) that the world of geo provides us all. The ability to observe and quantify patterns from overhead and translate into ground based, and often human scale, issues and phenomena. Imagery interpretation combined with the vector data model provides a mechanism for describing the earth in an abstracted and computable way; effectively bringing the power of spatial relationships to other forms of data analysis. With this baseline knowledge gathered through OSM mapping, larger concepts of temporal change, moving objects, human Geography and semantics for describing life patterns, and spatial modeling become accessible. At this point, the tools of mapping get combined with knowledge across the range of science and social topics…this is the point where baseline math, science, and descriptive Geography evolve into something new…a modular framework for investigating, analyzing, describing, understanding, and communicating our world.  The more complex the phenomenon, the more complex mathematical, engineering, and domain expertise is required…but these are all predicated on an interwoven set of concepts that can be systematically engaged and taught through OSM mapping. 

 

Geospatial SensorWebs

In the mid 1990s, the work of AGS Fellow Dr. Mike Botts for NASA led to the creation of Sensor Model Language (SensorML) for providing a means to have sensors of all kinds (whether in the space, air, land, sea, cyber, or electromagnetic domains) interoperate within a common 4D framework with spatio-temporal precision and accuracy.  SensorML laid the foundation for modern 21st century SensorWebs, as the key to the Open Geospatial Consortium’s Sensor Web Enablement (OGC SWE) architecture (Now the OGC API - Connected Systems Standard).  This now provides a Web standard for allowing interoperability among all of the sensors, things, robots, drones, satellites, devices, control systems, and platforms from all domains that are increasingly connected by the Internet of Everything.

 

3D Geospatial

For decades, the world’s of geospatial/geographic data and 3D modeling/simulation/gaming were strictly divided.  It was not possible to have a geodetically correct world within your video game or modeling and simulation environment.

 

This was frustrating since civil engineers and architects had been creating Computer Aided Design files for the buildings and infrastructure they had designed, and even made strides in bridging these CAD files into GIS environments.  But this marriage was awkward, uneasy, and did not scale to global scale.  Though, 3D models of buildings can be attached to their relevant 2D building features in OSM.

 

In recent years, the 3D Tiles standard of the Open Geospatial Consortium has finally made it possible to stream a geodetically precise and accurate world (or portion of a world) into a gaming/modeling/simulation application, and to merge high resolution 3D insets, that have more recently been observed/designed, into your application.  This has fundamentally changed the way GIS, OSM and other geospatial data can be experienced.

 

Uncrewed Remote Sensing Systems

The 21st century has seen the miniaturization, commoditization and commercialization of various kinds of “drones”.  Airborne drones (sometimes called Unmanned Aerial Systems - UAS, or Unmanned Aerial Vehicles - UAVs, or Remotely Piloted Vehicles - RPVs) had their start in 1917 with the Aerial Target, a British radio-controlled aircraft from the First World I - unless you count the Austrian unmanned incendiary balloon attack on Venice in July 1849.  However the first drone converted by the USArmy for remote sensing was for a battlefield unmanned aerial photo reconnaissance mission, in the mid-1950s, was a version of the MQM-33, designated the RP-71, later re-designated the MQM-57 Falconer.  So, there is a long history of uncrewed remote sensing systems, but not just for the air.  The 21st century has just seen these go mainstream, in the hands of anyone who seeks to harness their power.  Increasingly, the term UxS is used to address the wide variety of such systems operating on the ground, the air, underwater and on the water’s surface.  (Of course, remote sensing satellites are just UxS in space.)  Uncrewed remote sensing systems collect geospatial, and sophisticated spatio-temporal observations of the world around them.  And increasingly, these remote sensing capabilities underpin their function as autonomous systems.

 

Simultaneous Localization and Mapping (SLAM)

SLAM technologies are at the core of the revolution in autonomous navigation and mobile robotics on land, in the air, and at sea.  SLAM brings together maps, sensors, and algorithms to allow autonomous platforms to construct or update a map of an unknown environment while simultaneously keeping track of its location within it.  These SLAM maps can be 2D or 3D in nature.  While seminal work in SLAM on the representation and estimation of spatial uncertainty dates back to 1986, the actual acronym was coined in 1995 in a paper entitled “Localization of Autonomous Guided Vehicles”.  But, practical SLAM technologies exploded onto the scene in the early 2000s in large part because of innovations from DARPA Grand Challenge and DARPA Urban Challenge, bringing SLAM to worldwide attention.  SLAM technologies are now miniaturized and commoditized, bringing the power of geospatial awareness to all manner of platforms that are able to autonomously support human goals.

 

Cyber-Social Geography

At the end of the 20th century, the AGS published a special issue of the Geographical Review, edited by Barney Warf and Paul Adams, dedicated to Cyberspace and Geographical Space (1997). The 21st century has given us the work of AGS Fellow Dr. John Kelly on how humanity’s online behaviors have come to form a kind of cyber-social terrain of enduring social relationships that now shape how our world works, and how we experience our world, constitutes a new dimension to Geography.  This “Cyber-Social Geography” can be characterized quantitatively with rigor at hyper-local, regional, national, and global scales - and all of the world’s online expression across and through this networked terrain can be understood in realtime and retrospectively in terms of change over time.

 

GeoAI

Artificial Intelligence, Machine Learning, and Computer Vision (AI/ML/CV) are changing every field of endeavor.  The world of geospatial is no different.  The growing GeoAI bag of tricks is evolving rapidly, and practitioners in many industries, non-profits, local/state/federal governments - as well as academic researchers - are putting these GeoAI strategies to amazing uses every day. But, GeoAI is only as good as the data that it operates on!  Thus, all of the areas of geospatial innovation discussed above will add fuel to the GeoAI fire.

 

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Geography’s STEM credentials and its centrality to so many STEM fields and innovations these days cannot be denied.  The throughline that Geography offers our understanding of the evolution of STEM fields over human history is compelling.  And, the critical role that Geography has played in providing humanity tools to communicate information and coordinate action in every era and at every scale has inspired STEM exploration across an astonishing array of fields in order to improve our spatial understanding of an ever changing world.

 

After millennia of progressive knowledge creation, Geography now offers a springboard for mastering STEM fields of all kinds, as it ties these STEM fields to real world issues and fields of endeavor, and the way these issues impact real people in real places. Geography is science for society.

 

Again, context matters, and even if one doesn’t have the scientific, technical, engineering, or mathematical background to understand the details of how each works, all of us are capable of understanding how they relate to our complex, ever changing world.  As we collectively make investments in the next generation STEM workforce - a STEM workforce that is representative of our society at large and adaptable for the future - it is critical that all citizens, of every background, understand the central role that Geography has played in anchoring STEM learning in our real-world lived experience.