The global geospatial imagery analytics market is expected to
reach $14,687.9 million by 2023, registering a CAGR of 28.7% during the
forecast period. The rising demand for such solutions from enterprises due to
the strong competition and advancements in the geospatial imagery analytics
technology is the major factors driving the growth of the market. Indian Space Research Organisation (ISRO) launched 104
satellites in February 2017, out of which 88 were small satellites. Since nano
and small satellites are of low mass and size, usually under 500 kg, they are
easier to launch. This means that the number of satellites around the earth
will be increased, leading to high-revisit rates and greater data frequency.
Due to these advances in satellite manufacturing (ranging from creating unique
designs to mass assembly of standard products), the adoption of space-based
sensing with continual improvements in image resolution at a lower cost is
expected to increase. This is further predicted to drive the adoption of
geospatial imagery analytical methods.
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Geospatial imagery
analytics is used to leverage and recognize the unique characteristics of
unstructured geospatial data (geospatial images and videos). The method helps
understand the specifications and intricacies of an area by identifying the
patterns and relations in a geographic space and the changes they experience over
time. The global geospatial imagery analytics market was expected to
reach $3,196.2 million in 2017, and it is further projected to grow at a CAGR
of 28.7% in the near future. Apart from satellites, geospatial imagery is
collected through geographic information system (GIS) and unmanned aerial
vehicles (UAVs).
Technological
advancements are driving the adoption of geospatial imagery analytics. The
manual processing done for analyzing any pattern or demographic change in large
datasets, after the images have been captured by collection mediums, make the
whole process slow, complex, and monotonous. In order to deal with this,
service providers are focusing on integrating the deep learning, artificial
intelligence (AI), and big data technologies in geospatial imagery analytics
and are integrating these in their services rapidly. Various industries, such
as banking, financial services & insurance (BFSI), disaster management,
retail & e-commerce, and military, are getting beneficial results from these
technological advancements. The demand for these services has risen
considerably in the recent past as these technological advancements enable
end-users with a faster and more-efficient analysis of data.
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A great opportunity
for geospatial imagery analytics market players has arisen due to the
increasing use of location-based services (LBS), which make use of such
technology. According to a study, the number of users utilizing LBS in the U.S.
alone grew from around 196 million to nearly 219 million during 2016–2017. This
rise in the use of these services is due to the increasing number of
internet-enabled devices around the world.
Location-based
features are generally integrated in internet-connected devices to help
consumers in the interpretation of real-time maps for useful insights. At the
core of LBS are geospatial data analytics services. Hence, the growing adoption
of smartphones and the quick sharing capability of hyper-local information is
leading to the rising adoption of LBS, thereby further creating growth
opportunities for the vendors providing these services.
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