What Earth Businesses Are Built Entirely on Satellites?

The Invisible Infrastructure

In the modern economy, satellites have become a silent, invisible utility, as foundational as electricity or the internet. While space exploration captures headlines, the most significant economic activity is occurring not in orbit, but on Earth, driven by a new generation of businesses whose operations are 100% dependent on this orbital infrastructure. These companies are not just using space; they are built on it. Their products, services, and entire business models would be impossible, and in many cases inconceivable, without a constant, real-time connection to assets orbiting hundreds or thousands of kilometers above the planet.

This dependency isn’t uniform. It’s built on three distinct services from space, which function as the raw materials for these new terrestrial enterprises. For any business to be 100% dependent, it must rely on at least one of these three pillars.

The first pillar is Global Navigation Satellite Systems (GNSS). This is a generic term for any satellite constellation that provides global positioning, navigation, and timing (PNT) services. While most people use the term “GPS,” that name technically refers to the specific constellation owned by the United States. Other global systems include the European Union’s Galileo, Russia’s GLONASS, and China’s BeiDou. A receiver on Earth, like a smartphone, listens to signals from these satellites to determine its exact location.

The second pillar is Satellite Communications (SATCOM). This is the more intuitive concept of a satellite acting as a relay in the sky. A SATCOM, often an artificial satellite in a high geostationary orbit, receives telecommunication signals from a ground station (an uplink) and re-transmits them (a downlink) over a vast geographical area. This allows communication in places where it’s impossible to build terrestrial infrastructure like cell towers or fiber optic cables.

The third pillar is Earth Observation (EO). This involves the gathering of information about the planet’s physical, chemical, and biological systems. EO satellites use advanced remote-sensing technologies, from high-resolution optical cameras to cloud-penetrating radar, to monitor everything from deforestation and urban growth to soil moisture and atmospheric gases.

While these pillars can be analyzed separately, the most sophisticated modern businesses are built on their convergence. A single autonomous tractor, for example, is 100% dependent on all three: it uses GNSS to know where it is, it uses EO data to know what to spray, and it uses SATCOM to send its status back to the farmer from a remote field. These pillars are not just tools. They are the bedrock of entire industries, supporting hundreds of billions of dollars in global revenue.

Pillar One: Positioning and Timing (GNSS)

The most pervasive and perhaps most misunderstood satellite dependency is GNSS. Its function is neatly summarized by the acronym PNT: Positioning, Navigation, and Timing. The “positioning” (your latitude and longitude) and “navigation” (your route from A to B) are obvious. These are the functions that have made GNSS synonymous with “GPS” and mapping apps.

The system works through a precise and constant celestial broadcast. A constellation of 24 or more satellites continuously orbits the Earth, each one broadcasting a signal that contains its exact orbital location and, most importantly, the exact time the signal was sent. This timekeeping is maintained by incredibly accurate atomic clocks on board the satellites.

A receiver on the ground – whether a dedicated device or a chip in a smartphone – listens for these signals. When it picks up a signal, it notes the tiny discrepancy between the time the signal was sent and the time it was received. Since the signal travels at the speed of light, this time-delay measurement reveals the receiver’s distance from that one satellite.

A signal from a single satellite isn’t enough; it only tells the receiver it is “somewhere” on the surface of a giant, imaginary sphere. By receiving a second signal from a second satellite, the receiver can narrow its location to the intersection of two spheres, which creates a circle. A third signal narrows this circle down to just two possible points. It’s the signal from a fourth satellite that confirms the one true location and, in the process, also determines the receiver’s precise altitude. This mathematical process is known as trilateration.

The “P” and “N” of PNT have created entire markets, but the most economically vital, and most hidden, 100% dependency is on the “T”: Timing. The GNSS system is, in effect, a single, global atomic clock, accessible by anyone with a cheap receiver. The PNT data from these systems is the raw material for a global market projected to reach €580 billion by 2033.

This timing signal is what synchronizes the world’s infrastructure. Modern 5G cellular networks, for instance, are 100% dependent on GNSS timing signals to synchronize their base stations. This allows a phone to move seamlessly between cell zones without dropping a call and ensures data packets are handled in the correct order. High-frequency trading systems on global stock exchanges are 100% dependent on these timing signals to timestamp transactions down to the nanosecond, providing a legally verifiable record of when a trade occurred. Even the electrical grid uses GNSS timing to synchronize power flows. These are multi-trillion-dollar systems that appear entirely terrestrial, yet they would fail instantly without the timing signals from satellites they don’t even own.

The Modern Mobility Engine: Ride-Sharing

The most visible business built on GNSS is the on-demand mobility platform. Companies like Uber, Lyft, Grab, and Didi are pure-play GNSS businesses. Their product – a car that arrives on demand – is a service that simply could not exist, in any recognizable form, without a constant, 100% dependency on positioning satellites. The entire business model is built around a smartphone app that is, at its core, a sophisticated GNSS receiver.

This dependency is absolute across every single function of the business operation. The process of booking a ride is a cascade of GNSS-driven calculations:

• Matching: When a user opens the app, the first thing it does is use GNSS to determine their precise location. Simultaneously, the app is tracking the real-time GNSS location of every available driver. The platform’s core algorithm is a matching engine that uses this location data to find the nearest available driver and dispatch them.
• Tracking and ETAs: Once a ride is booked, the passenger is 100% dependent on GNSS to monitor the driver’s real-time location on a map. This feature is not just for convenience; it’s a core part of the service, reducing uncertainty. This same tracking data allows the platform to calculate a reliable Estimated Time of Arrival (ETA).
• Navigation: The platform provides in-app route mapping for the driver. This entire feature is a GNSS-dependent navigation service, guiding the driver turn-by-turn.
• Pricing: The “dynamic” or “surge” pricing models these companies are famous for are 100% location-driven. The platform uses aggregated GNSS data to identify a geographic zone (a “heatmap”) where rider demand is high and driver supply is low, and automatically adjusts fares in real-time for that specific location.
• Safety: Safety features, such as sharing a trip’s progress with a family member or detecting an unusual stop, are all functions of precise GNSS tracking.

This dependency has evolved. These companies are no longer just passively consuming GNSS signals. They have become active producers of a new, high-value data asset. They harvest the anonymized, historical GPS traces from their millions of daily trips.

This vast trove of data is then used in a powerful feedback loop. By overlaying their drivers’ GPS traces onto existing digital maps, these companies can infer where a map is wrong. If thousands of drivers are consistently cutting a corner, it’s likely a new road exists that the map provider doesn’t know about. This allows the ride-sharing platform to build its own proprietary mapping data, correcting deficiencies in the very maps they rely on. This location data, generated as a byproduct of their 100% dependency on GNSS, is now a core strategic asset, used to improve operational efficiency and to build and perfect the autonomous vehicles that represent their future.

The New Digital Farm: Precision Agriculture

A similar transformation has happened in one of the world’s oldest industries: agriculture. The 100% dependency on satellites has created a new field known as precision agriculture. This is a collection of business models and technologies that move farming from a uniform, “one-size-fits-all” operation to a data-driven, “per-square-meter” practice.

Precision agriculture uses satellite technology – primarily GNSS – to manage variability within a single field. Farmers have always known that some parts of a field are more productive than others. Precision agriculture allows them to quantify this variability and manage it. The entire system is built on GNSS, allowing farmers to plan operations, map fields, and work in low-visibility conditions like rain, dust, fog, or darkness.

This industry is not a single business but a complete, interlocking ecosystem of satellite dependency. It’s a value chain where each link is 100% satellite-dependent, and each sells a product or service to the next.

The first link is The Hardware Business: Autonomous Tractors. The backbone of the modern digital farm is GNSS-guided machinery. Companies like John Deere sell tractors and combines that are 100% dependent on high-precision GNSS receivers. By using their own GNSS signals combined with satellite-based correction signals, these systems can achieve “inch” level accuracy. This allows a tractor to steer itself, following precise paths across a field. The business model is the sale of high-margin equipment. The value proposition for the farmer is a reduction in labor costs, the ability to run operations 24/7, and a sharp reduction in input waste. A human driver will “overlap” rows, spraying fertilizer or planting seeds in an area that has already been covered. A GNSS-guided tractor eliminates this redundancy, saving farmers millions of dollars in fuel, seed, and fertilizer.

The second link is The Service Provider Business (SaaS). These are software-as-a-service companies that sell data, not hardware. Their business model is 100% satellite-dependent and based on a subscription. Their product is an “advisory” or, more commonly, a “prescription map.” These companies, like Farmonaut, use a convergence of satellite technologies. First, they use GNSS-guided tools to create high-resolution maps of a farmer’s field, often guiding automated soil sampling. Second, they ingest multispectral satellite imagery – an Earth Observation (EO) product – to monitor crop health, identify stress, and measure soil moisture. Third, their proprietary AI and machine learning algorithms combine this GNSS data and EO imagery to create a “prescription” that tells the farmer exactly what that field needs, meter by meter.

The third link is The Application Business: Variable-Rate Technology (VRT). This is the business of selling the “smart” implements, such as sprayers, seeders, and irrigators, that use the prescription map created by the SaaS company. This VRT equipment has its own GNSS receiver. It knows exactly where it is in the field at all times. As it moves, it reads the prescription map and automatically adjusts the rate of fertilizer, pesticide, or water it applies to that specific, precise spot. If one part of the field has rich soil and high moisture, the VRT seeder will apply fewer seeds; 20 meters later, where the soil is poor, it will increase the seed rate. This business model cannot exist without GNSS.

These three businesses lock together to form a perfect, self-contained ecosystem of satellite dependency. The hardware company sells a GNSS-guided tractor. The SaaS company sells a prescription map made from GNSS and EO data. The VRT company sells an implement that uses its own GNSS receiver to read that map and execute its instructions. The 100% dependency on satellites isn’t a single point of failure; it is the fundamental, shared utility that enables this entire multi-billion-dollar market to exist.

Pillar Two: Satellite Communications (SATCOM)

The second pillar of dependency is Satellite Communications, or SATCOM. This is the business of selling connectivity. These businesses exist to serve the “85% of the Earth’s surface” that is not covered by terrestrial networks like cell towers and fiber optic cables. Their foundational business model is acting as a relay in the sky. A signal is sent from a ground station (an “uplink”) to a satellite, which is equipped with a device called a transponder. The transponder amplifies the signal and retransmits it on a different frequency (a “downlink”) back to a receiver on Earth.

For these businesses, the location of the satellite dictates the entire business model. The two most important locations are Geostationary Orbit (GEO) and Low Earth Orbit (LEO).

Geostationary Orbit (GEO) is a specific, high-altitude orbit approximately 36,000 kilometers above the equator. In this orbit, a satellite moves at the exact same angular speed as the Earth’s rotation. From the perspective of a person on the ground, a GEO satellite appears to be “stationary,” fixed in one spot in the sky. This is ideal for broadcasting services, because a receiver dish on a house can be pointed at the satellite once and never needs to move. Its great weakness is latency. Because the signal must travel 36,000 km up and 36,000 km back down, there is a noticeable signal delay (or “ping”) of 600 milliseconds or more. This makes GEO unsuitable for real-time applications like video calls or online gaming.

Low Earth Orbit (LEO) is a much lower orbit, from 550 to 2,000 kilometers above the Earth. Because the satellites are so much closer, their latency is dramatically lower – often just 25 to 50 milliseconds, which is comparable to ground-based fiber. This allows for high-speed, real-time internet. The weakness of LEO is that the satellites are not stationary; they are moving very fast. To provide continuous, global coverage, a company must launch a “constellation” of hundreds or even thousands of satellites, and the receiver on the ground must be “smart” enough to hand off the signal from one satellite to the next as they fly overhead.

This distinction between GEO and LEO isn’t just a technical detail; it defines the 100% satellite-dependent business models built on SATCOM.

The classic 100% SATCOM-dependent business is Direct-to-Home (DTH) broadcasting, built entirely on GEO satellites. This category includes DTH satellite television providers like DirecTV and Sky, as well as satellite radio providers like SiriusXM.

The DTH satellite TV business model is designed to provide television programming directly to a small dish at a viewer’s home, completely bypassing the terrestrial cable infrastructure. Its 100% satellite-dependent value proposition has always been coverage. It can deliver hundreds of high-quality channels to rural and remote areas where laying cable would be (or was) prohibitively expensive.

The business model involves a complete, satellite-dependent value chain.

1. Content Aggregation: The DTH operator (e.g., Dish Network) acts as a central hub, creating channel packages by aggregating content from various broadcasters.
2. Uplink: The operator combines, compresses, and encrypts all of this content at a large, secure ground station called a “broadcast center” or “teleport.” From this teleport, the massive, combined signal is uplinked to a GEO satellite.
3. Broadcast: The GEO satellite, fixed in its orbital slot, receives the signal and re-transmits it over a vast “footprint,” which can cover an entire continent.
4. Subscription: A viewer on the ground with a small, fixed dish receives this signal. However, the signal is encrypted. The DTH business model is a “pay-TV” model; the company isn’t selling the signal (which is free to receive), it’s selling the key to unlock it. The viewer pays a monthly subscription fee, and in return, the DTH provider gives them a “set-top box” (STB). This STB is a specialized receiver that gets authorization signals from the satellite, allowing it to decrypt and display the channels the user has paid for.

The satellite radio business model, dominated by SiriusXM, is nearly identical. It’s a “pay-for-service” subscription business 100% dependent on its own fleet of satellites. Its value proposition is content – commercial-free music, exclusive talk shows, and sports – that isn’t subject to the same content regulations as terrestrial AM/FM radio.

While satellite radio can be received anywhere, its business strategy is almost entirely focused on its “core automotive subscriber segment.” Today, 90% of SiriusXM’s subscribers are in-vehicle. This is not by accident.

These “classic” broadcasting models, once dominant, are now in a defensive crouch. Their 100% dependency on satellites, once their greatest strength (universal coverage), is now a vulnerability in the face of terrestrial “Over-the-Top” (OTT) streaming services like Netflix, Hulu, and Spotify. Viewers are increasingly “cutting the cord,” abandoning their satellite pay-TV packages in favor of the flexibility and on-demand nature of terrestrial internet streaming.

This has forced these satellite-dependent businesses to adapt. SiriusXM, facing “marketplace headwinds” from streaming, is now “doubling down” on the automotive market. It is retreating to its last, most defensible 100% satellite-dependent fortress: the moving car. The car is the one place where terrestrial internet (via 5G) is still less reliable than a ubiquitous satellite signal.

Connectivity in Motion: The Airborne and Maritime Markets

The business of selling connectivity to “things that move” – airplanes and ships – is, by definition, 100% satellite-dependent. As these assets move far from land, satellites are the only way to maintain a broadband connection. This entire market segment is currently undergoing a complete revolution, driven by the shift from GEO to LEO satellites.

The In-Flight Connectivity (IFC) business is run by companies like Gogo and Viasat. Their model is B2B: they sell connectivity services to airlines, which in turn offer that service to their passengers. For decades, this business was 100% dependent on high-latency GEO satellites. The result was the notoriously slow, laggy, and expensive in-flight Wi-Fi that was barely usable for basic email.

The shift to LEO constellations is a “quantum leap” over this old model. Airlines are now investing billions to retrofit their fleets with new antennas that can talk to these LEO networks. The result is a service that provides “Home or office broadband speeds” at 40,000 feet. This isn’t just an “improvement”; it’s a change in kind that creates entirely new business models. The old GEO service was a low-quality, “grudge purchase.” The new LEO service is a high-quality, broadband-equivalent product. This allows an airline to sell “Premium Wi-Fi” packages, enabling passengers to do things that were previously impossible: stream HD Netflix, play online games, and participate in live Zoom and Teams video calls.

The maritime market is experiencing the exact same transformation. The business of providing SATCOM to commercial shipping fleets, cruise ships, and military vessels has always been 100% satellite-dependent for navigation, communication, and safety. This market was also reliant on old GEO systems.

The entry of LEO providers like Starlink has caused a massive disruption. In a single year, the total bandwidth utilization in the maritime market doubled. This indicates that ships weren’t just “upgrading” their old systems; they were starting to use broadband-heavy applications for the first time. The market share for non-geostationary orbit (NGSO) solutions, which includes LEO, is projected to jump from 20% in 2023 to 90% by 2033. This new LEO capability enables new businesses: a shipping company can now conduct remote, high-definition video-guided diagnostics on an engine at sea, potentially saving a costly and time-consuming trip to port.

The Remote Industrial Internet: Satellite IoT

While LEO broadband constellations get headlines for selling maximum speed for high revenue, a separate and equally 100% satellite-dependent industry is being built on the exact opposite premise. This is the Satellite Internet of Things (Sat-IoT) market.

The Sat-IoT business model, run by companies like Myriota, ORBCOMM, and Kineis, is the “small data” business. It is the economic inverse of LEO broadband. Its customers don’t want speed. They want minimum data, ultra-low cost, and extreme power efficiency.

The business model involves selling two things:

1. Hardware: Rugged, power-efficient, and relatively simple satellite terminals or “trackers.”
2. Data Plans: Low-cost subscription plans for transmitting very small packets of data.

The 100% dependency is based on reach, not speed. The value proposition is connecting industrial sensors in the unconnected 85% of the world. A water utility, for example, doesn’t need to stream video from a remote reservoir. It needs a sensor that can wake up once a day, transmit a single “water level” measurement (a packet of a few bytes) via satellite, and then go back to sleep, all while running on a battery that needs to last for ten years.

This “small data” model is enabling massive industrial businesses. In remote industrial monitoring, sensors are placed on oil and gas pipelines, renewable energy sites (wind farms, solar installations), and other utilities. Because these assets are, by definition, far from terrestrial networks, their monitoring is 100% dependent on Sat-IoT. This allows operators to “remotely diagnose and troubleshoot issues,” detect leaks in real-time, and enable “predictive maintenance,” all of which reduces cost, improves safety, and ensures environmental compliance.

The other major Sat-IoT business is asset tracking. Logistics companies are 100% dependent on satellites to track their assets – freight wagons, shipping containers, and industrial machinery – once they move “off the grid.” A container on a ship or a truck in a remote region is invisible to a terrestrial network. Sat-IoT provides “full visibility” of the global supply chain.

Connecting the Unconnected: Rural and Remote Broadband

The final and most direct SATCOM business model is that of the LEO constellation operators themselves, like Starlink and OneWeb. These companies are, in effect, global Internet Service Providers (ISPs) whose entire network infrastructure is in space.

The most visible business model is B2C (Business-to-Consumer): selling high-speed, low-latency internet access directly to individual homes in “rural and remote regions” and “digital deserts” that are underserved by terrestrial broadband. For these customers, the LEO satellite service is not a “backup”; it is their primary, 100% satellite-dependent connection to the modern world.

A massive, and perhaps more lucrative, “hidden” business model is B2B (Business-to-Business): selling “cellular backhaul” to terrestrial mobile operators (telcos). In this model, the telco (like Vodacom in Africa) is not the competition; it is the customer.

Here’s how this 100% dependent business works: a telco wants to provide 5G service to a remote village, but it can’t, because the cost of running a fiber optic “backhaul” link to that village is too high. Instead, the telco builds its 5G tower and simply points a satellite dish at the sky. The LEO-ISP company sells a high-speed, B2B satellite link to the cell tower. The tower then provides normal 5G service to its customers in the village. Those customers, on their phones, have no idea their call is being “backhauled” to space.

This “hybrid connectivity model” is a powerful new business. The LEO constellation isn’t competing with 5G; it’s enabling 5G’s expansion into previously uneconomical markets.

Pillar Three: Earth Observation (EO)

The third pillar of dependency is the Earth Observation (EO) business. This is the industry of “seeing” the Earth from space. For decades, this market was dominated by governments. Agencies like NASA (with its Landsat program) and the European Space Agency (with its Copernicus program) launched hugely expensive, sophisticated satellites and collected petabytes of data for scientific and defense purposes.

The EO business model was revolutionized when these government agencies adopted “free and open” data policies, making their vast archives of satellite imagery available to anyone, often for free. This act of commoditizing the raw data had a paradoxical effect: it created the commercial EO industry.

The real business isn’t selling the data; it’s in the “cloud computing and AI” that can process this free, complex, petabyte-scale data into a simple, sellable answer. The 100% dependency for this new industry isn’t necessarily on owning a satellite; it’s on the availability of this constant stream of satellite data and, more importantly, on the proprietary algorithms that analyze it.

The New Business Model: From Raw Data to “Insights-as-a-Service”

The old EO business model, which is now almost obsolete, was “price-per-kilometer.” A company would sell a raw satellite image (the “pixels”) to a customer for a high fee, often with a large minimum order size. This model was “prohibitively expensive” and required the customer to be a geospatial expert capable of analyzing the complex data.

The new, 100% satellite-dependent business models are all “as-a-service” and are built “up the value chain.”

• Data-as-a-Service (DaaS): This is the first step up. Instead of selling a single, raw image, a company sells a subscription to a continuous, “analysis-ready” data stream. The customer (an agribusiness, for example) gets access to an automatically updated feed of all imagery for their specific areas of interest.
• Insights-as-a-Service (IaaS): This is the dominant new model. The company goes one step further and sells a “decision-ready insight,” not raw data. The 100% dependency on satellites is completely hidden from the customer. The business sells the answer, not the pixels. For example, instead of selling an agribusiness a complex multispectral image of a farm, an IaaS company sells a simple “crop health score” of 8.5/10, or a “yield forecast.” The customer doesn’t know, or care, how that number was derived from satellite data.
• Platform-as-a-Service (PaaS): This model is run by companies like Google Earth Engine and Sentinel Hub. They provide a massive, cloud-based platform that contains petabytes of satellite data and the processing power to analyze it. Other businesses then build their own IaaS applications on top of this platform, paying for compute time and access rather than having to download and manage the raw data themselves.

These new “as-a-service” models have opened up the EO market to entirely new industries that are now 100% dependent on satellite insights.

Applications Driving the EO Market

This IaaS business model is creating new, 100% satellite-dependent niches in many sectors, particularly insurance, finance, and climate.

1. Insurance and Disaster Response

This is the business of selling geospatial intelligence to (re)insurance companies. Its 100% dependency is on a specific, high-tech sensor: Synthetic Aperture Radar (SAR).

Unlike a normal optical camera, which is “passive” and just captures reflected sunlight, SAR is an “active” sensor. It beams its own radio-wave “flash” at the Earth and records the echo that bounces back. Because it provides its own light, it can see at night. And because its radio waves pass right through clouds, fog, and rain, it can see in any weather.

This capability is the entire business model. Imagine a hurricane makes landfall. The only thing an insurance company wants to know is: “What properties were damaged?” The entire area is 100% cloud-covered for days, making optical satellites useless. SAR is the only technology that can see through the clouds and identify which areas are flooded.

The IaaS business model here is clear: an insurer, 100% dependent on this data, subscribes to a SAR data provider. Immediately after a catastrophic event, this allows the insurer to “Streamline Claims Management.” Instead of waiting days or weeks for a claims adjuster to be able to physically access a flooded neighborhood, the insurer uses near-real-time SAR data to “assess damages swiftly.” They can pre-approve claims, detect fraud, and proactively manage their exposure, all from space.

2. Finance and Economic Forecasting

This is the business of “Economic Nowcasting.” It is 100% dependent on analyzing satellite imagery to gain a financial edge. Companies like SpaceKnow and QuantCube sell “Smart Data” and “activity indices” directly to financial institutions like hedge funds and traders.

Their value proposition is simple: “Know the future before it happens.” This business uses AI and machine learning algorithms to analyze satellite imagery and monitor real economic activity on the ground, weeks or months before “official” government data is released.

The business model involves:

• Using AI to automatically count the number of cars in the parking lots of major retailers like Walmart or Target, every day. This data is aggregated into a “German Retail Index” or a “US Retail Index” that provides a highly accurate, real-time indicator of consumer activity, long before the companies report their quarterly earnings.
• Monitoring activity at factories, ports, mines, and refineries to create indices of industrial production or commodity stockpiles.
• Counting every ship in every major port to track global supply chain movements.

The 100% satellite-dependent product is this data feed. The financial firm subscribes to the “parking lot index” as a predictive signal, allowing them to trade on that information and generate “alpha,” or a financial return. This business model has successfully turned satellite photos into a high-frequency financial instrument.

3. Climate and Emissions Monitoring

This is an emerging and powerful IaaS business, 100% dependent on new, highly specialized satellite-based sensors. Companies like GHGSat have launched satellites with a unique capability: they can pinpoint and measure greenhouse gas (GHG) emissions, like methane, from specific industrial sites on Earth.

Their high-resolution sensors can detect a methane leak from a single “coal mining” operation, a “landfill,” or a “natural gas pipeline.” The business model is selling these “actionable metrics and insights.”

The customers for this 100% satellite-dependent data fall into three categories:

1. The Emitters: Oil & gas companies, mining operators, and agricultural firms buy this data to find and fix their own leaks, saving them money on lost product and reducing their environmental footprint.
2. Regulators and Governments: These groups buy the data to monitor policy compliance and verify if companies are meeting their emissions reduction targets.
3. Financial Services: Investors and insurers buy this data for ESG (Environmental, Social, and Governance) risk assessment. They use it to understand which companies in their portfolio have a “methane problem,” as that represents a significant financial and regulatory risk.

The Hidden Foundation: The Ground Segment Business

All of these satellite-dependent businesses – from ride-sharing to DTH TV – share a 100% dependency on another, completely terrestrial business: the “ground segment.” Satellites in space are useless unless you can talk to them. The ground segment is the entire Earth-based infrastructure of antennas, control systems, and data processing centers that communicates with satellites.

The most visible part of this is the “Teleport.” A teleport is a large, secure ground station that acts as a hub, connecting the satellite network in space to terrestrial networks like the internet or TV broadcast centers. This is the facility that uplinks the DTH TV signal or downlinks the petabytes of Earth Observation data.

For decades, the business model was “build-your-own.” A satellite operator like SiriusXM or DirecTV had to bear the massive capital expense (CAPEX) of building and operating its own global network of large, expensive, dedicated ground stations.

This model created a high barrier to entry and has been completely disrupted by a new business model: “Ground-Segment-as-a-Service” (GSaaS).

The GSaaS business model is a direct enabler of the new space economy. Companies like Viasat (with its Real-Time Earth network) build a global network of antennas and then sell access “on a pay-per-use basis” or via a monthly subscription. This turns a new satellite company’s massive CAPEX into a flexible, predictable operating expense (OPEX).

The GSaaS business model is, in effect, the “Amazon Web Services (AWS) for Space.” Before AWS, every internet startup had to buy, install, and manage its own servers – a high CAPEX barrier. After AWS, a startup could “rent” server capacity by the hour (OPEX), allowing it to scale.

GSaaS is the exact same thing for space. A LEO startup like GHGSat doesn’t need to build a dozen ground stations around the world to talk to its constellation. It just “rents time” on the GSaaS network’s antennas as its satellites pass overhead. This 100% satellite-dependent business enables all the other 100% satellite-dependent businesses to exist. Without it, the business case for most LEO and small-satellite startups would collapse.

The Next Frontier: Moving the Ground Segment into Space

This ground-segment model is already being disrupted by the next bottleneck: the data downlink. The “exponential growth in sensor-generated data” from new EO satellites is “surpassing the capacity of current RF and laser transmission infrastructure.” In short, the new satellites are collecting too much data to send back to Earth. It’s a “petabyte problem.”

The solution is a new, emerging business model: “Data centers in space,” or “On-Orbit Data Processing.”

This business model is 100% satellite-dependent because the business is a satellite. The idea is to solve the data bottleneck by not sending the raw data down at all. The processing, which is increasingly AI-driven, is done on the satellite in orbit.

Instead of transmitting petabytes of raw, unprocessed EO imagery (which “cannot be transmitted back to Earth” efficiently), the satellite processes the data on-board. It “reduces the data through local processing to look for relevant data.”

This is the logical and ultimate conclusion of the “Insights-as-a-Service” business model. The raw data never even touches Earth. The satellite itself identifies the relevant event, performs the analysis, and then sends down only the answer – a tiny packet of data that says: “Methane leak detected at coordinates X, Y,” or “New construction of 10 buildings detected in this zone.”

The 100% satellite-dependent business model of the near future is a data center in orbit, selling its processed, AI-generated answers directly to terrestrial customers.

The Total Dependency Risk

For every business discussed in this article, the 100% dependency that enables their entire model is also their single greatest, most unique vulnerability. These companies have built their foundations on an invisible infrastructure they do not control, exposing them to a complex and systemic web of risks that “normal” terrestrial businesses never have to consider.

A business 100% dependent on satellites is, in effect, fighting a “four-front war” against risks that are natural, man-made, and malicious.

1. Natural Threats: Space Weather

This is a direct, unpredictable threat from the sun. Solar flares and Coronal Mass Ejections (CMEs) periodically blast the solar system with high-energy particles. When these particles hit the Earth’s magnetic field, they can be devastating to satellites.

• Impact on Hardware: The particles cause “internal charging” and “surface charging” on the satellite’s electronics, leading to “destructive arc discharges.” This can cause “phantom commands” (where the satellite starts doing things it wasn’t told to), “misoperation,” data corruption, or “complete failure of the satellite.”
• Impact on Signals (GNSS): The particles super-heat and “ionize” the atmosphere, which disrupts the PNT signals passing through it. This causes “propagation delay” (range errors) and “ionospheric scintillations” (loss of lock). For a GNSS-dependent business like a ride-sharing app or an autonomous tractor, this results in inaccurate or no position information. The service would simply stop working correctly.
• Impact on LEOs: Geomagnetic storms also heat the upper atmosphere, causing it to “swell.” This “increased atmospheric drag” acts like a brake on LEO satellites, pulling them out of orbit and shortening their lifespan. A 2022 storm, for example, was responsible for the destruction of a batch of 40 new Starlink satellites.

2. Man-Made Physical Threats: Orbital Debris

The orbital “highways” are a minefield. Of the roughly 34,000 large objects currently tracked in orbit, only about 25% are working satellites. The rest is “junk”: dead satellites, discarded rocket stages, and fragmentation from old explosions. There are an estimated 130 million additional pieces of debris, from 1mm to 1cm, that are too small to be tracked.

The risk is the speed. These objects travel at over 25,000 km/hr. At that velocity, a collision with a 1cm object can be “mission-ending.” A single accidental collision in 2009, between a dead Russian satellite and an active Iridium communications satellite, created thousands of new, high-velocity debris pieces that still threaten satellites today. For any business 100% dependent on a satellite – like a DTH TV provider – this creates a constant, low-level risk that its multi-million dollar asset could be randomly destroyed, instantly ending its service.

3. Malicious Digital Threats: Jamming and Spoofing

This is a direct, ground-based attack on the satellite signal.

• Jamming: This is a “brute force” attack. A malicious actor uses a ground-based transmitter to “shout” noise on the same frequency as the satellite. The weak satellite signal is drowned out, and the receiver (a phone, a ship’s navigation system) can no longer hear it.
• Spoofing: This is a more sophisticated “man-in-the-middle” attack. The attacker transmits false satellite signals, “lying” to the receiver to trick it into calculating an incorrect position or time.

This is a direct and “intensifying” threat to the GNSS-dependent business models. It’s a “grave concern” in geopolitical conflict zones. A spoofer could be used to send an autonomous tractor into a ditch, or to tell a commercial ship it is in a different location, perhaps to help it evade sanctions.

4. Ground-Based Threats: The Unseen Vulnerability

The most overlooked risk is a cyber-attack on the ground stations and teleports. This was proven possible in a 2022 attack against Viasat’s ground systems. Because many space systems are “legacy systems” with “weak configuration,” they are vulnerable.

An attacker who breaks into a ground station can “send fake commands or block real ones.” This is the ultimate vulnerability: if you hack the ground station, you own the satellite.

This four-front war – against astrophysics, space junk, signal warfare, and terrestrial cyber-attacks – is the ultimate price of 100% dependency. A business like Uber or a precision-ag service finds its entire operation at the mercy of a solar flare, a piece of decades-old debris, a malicious spoofer, or a hacker attacking a teleport it doesn’t even know exists.

Summary

The analysis of Earth-based businesses 100% dependent on satellites reveals that space is no longer a distant, future-tense concept. It is a vital, present-day, and fully integrated utility. This “invisible infrastructure” has become the foundation for entirely new categories of business on Earth, many of which are now fundamental to the global economy.

These businesses fall into three distinct categories of 100% dependency, each built on one of the three pillars of satellite service:

• Pillar 1 (GNSS): Businesses built on knowing where things are. This includes the on-demand mobility of ride-sharing and the hyper-efficient, autonomous world of precision agriculture.
• Pillar 2 (SATCOM): Businesses built on connecting the unreachable. This ranges from the “classic” DTH broadcasting models and the LEO-revolutionized in-flight and maritime broadband markets, to the “small data” industrial IoT and the “hybrid” cellular backhaul models connecting remote communities.
• Pillar 3 (EO): Businesses built on understanding the planet. This is the new “Insights-as-a-Service” (IaaS) economy, where satellite data is processed into predictive, high-value answers for industries like insurance, finance, and climate monitoring.

These terrestrial businesses are, in turn, 100% dependent on another layer of “hidden” terrestrial businesses, such as the “Ground-Segment-as-a-Service” (GSaaS) providers who act as the “AWS for Space.”

This total dependency, which has enabled the creation of multi-billion-dollar markets from nothing, is also the source of their greatest and most unique systemic risk. The operations of these companies are exposed to a complex web of vulnerabilities, from solar flares and orbital debris to malicious signal spoofing and cyber-attacks on unseen ground stations. The success of these 21st-century businesses is, and will remain, entirely tied to the stability of an infrastructure floating in the void.