The GEOINT
Playbook
An investment thesis on the future of geospatial intelligence
and our outlook on digitizing the physical world.
Report by Space Capital (R)Executive Summary
This is largely due to the proliferation of spatial analysis; a critical feature
of modern enterprise and consumer applications. Yet despite the growth in
The global
geospatial data creation and, subsequently, the tools to conduct geospatial
1
geospatial market analysis, working with this type of information remains complex and
is expected tothe number of products limited. This is in large part due to the broader
grow from $63.1 industry-wide trend of market consolidation amongst existing incumbents
and well-funded technology startups.3 This points to a conflicting theme
billion to $147.6 within the geospatial stack: companies that begin as a modular technology
billion in the nextstack (unbundled) then evolve into a vertically integrated software solution
five years.2 (bundled). The new “As-a-service” paradigm has unlocked scalable modular
development across compute, storage, application programing interfaces
(APIs), etc. and is accelerating the pace of innovation.
In this playbook we will walk through our thesis, which analyzes geospatial
intelligence (GEOINT) through the lens of technology layers: Infrastructure,
Distribution, and Applications. This framework helps us connect the dots
from the origin and constraints of the geospatial stack to evolution and
inflection within the market. It also helps us see the larger role that space-
based technology plays in an ecosystem that intersects with the modern tech
industry and serves customers across a wide variety of markets.
Key Takeaways
Infrastructure: A variety of geospatial sensor platforms now capture data
at different altitudes, benefiting from low-cost components, commoditized
storage/compute, and decades of geographic information systems (GIS)
product development.
Distribution: Adoption of cloud, AI/ML capabilities, and increasingly powerful
APIs and software development kits (SDKs) are expanding the user base
and applications beyond data engineers, GIS specialists, and subject matter
experts.
Application: A seemingly infinite number of venture-scale businesses are now
being built in multi-trillion dollar global industries like Agriculture, Insurance,
Climate Markets, and Augmented Reality, with the market potential looking
similar to Location-based Services when the iPhone first embedded GPS.
(R)The GEOINT Playbook | Report by Space Capital 2Executive Summary
NASA began to develop
observation technology to better
understand our planet at scale
(remote sensing) in the 1960s.
Landsat 1 was launched in 1972
and the resulting data proved
capable of serving a range of
applications including agriculture,
forestry, mapping, geology,
hydrology, coastal resources,
and environmental monitoring.
Around the same time, Esri, a
geographic information system
(GIS), became the first company to
digitize mapping information for
commercial use. This early form
of quantitative and computational
geography enabled users to see
the promise of working with large
geospatial datasets to understand
where things happen (patterns,
clusters, hot spots), why they
happen, when they happen (location
decision), and where things should
be located (optimization).
Geographic Information System (GIS). (Source: City of Newberg)
As a result of this technology, a standard for interacting with
geospatial data was established: data as layers (raster and vector),
where each layer can be stacked on top of one another and
analysis can be done at any level.
(R)The GEOINT Playbook | Report by Space Capital 3 Executive Summary
Then, in the 1990s and 2000s, significant advancements in computational infrastructure enabled technical innovations
that changed mapping. Although domain-knowledge was still required to interact with geospatial data, three technical
innovations unlocked never before seen functionality: 1) GPUs were released and became a standard in rendering
complex multidimensional scenes, 2) APIs gained traction amongst developers for serving and requesting all types of
data, and 3) the internet gained traction which educated the modern consumer on the advantages and convenience
of web mapping (navigation). In the 1990s, a group of engineers at Intrinsic Graphics unknowingly developed the core
technology behind Google Earth; 3D graphics libraries for video games. Shortly after the release of their inaugural
demo, the team created a company called Keyhole in order to improve the product stack to stream interactive 3-D
maps with satellite imagery and aerial photographs.4 Then, in 2004, Google acquired Keyhole, the then three-year old
digital-mapping software company.5,6 Historically, Keyhole was primarily used for defense; this acquisition expanded
Google’s business line for commercial use cases (including advertising).
Today, the use of small satellites and
commercial off-the-shelf components has The adoption of cloud, edge
computing, AI/ML capabilities, and
made it more cost effective to capture increasingly powerful geospatial
timely geospatial data at a global scale.APIs and SDKs are making the
benefits of geospatial intelligence
more accessible. Developers no
longer need to be experts in image capture, data processing, or object detection, and instead can focus on building
specialized applications tailored to unique customer needs. Demand for geospatial data is being quantified through
marketplaces and used to inform what sensors and platforms will be built in the future. The ability to collect, process,
and analyze endless geospatial data is creating powerful new applications that are helping to reshape how entire
industries operate and transform our relationship with our planet.
(R)The GEOINT Playbook | Report by Space Capital 4Contents
The GEOINT Playbook
Infrastructure6
Distribution 22
Applications 39
Conclusion 52
Primary Research 53
Endnotes54
(R) The GEOINT Playbook | Report by Space Capital