![]() This AI-generated output segmentation data can be utilized for diverse business purposes such as pattern identification and object tracking. Telescope® uses an in-house developed machine learning framework to classify information from a satellite image into one of the following six categories: buildings, greenery, water, soil, utilities, or others. Telescope® is a next-generation AI satellite image segmentation solution capable of resolving complex business and significant operational requirements. This is where Affine seeks to add value with our home-grown tool, Telescope®. A vast trove of satellite image data is waiting to be utilized for value generation across multiple domains varying from real estate, military, agriculture, urban planning, and disaster management, to name a few. In parallel, Artificial Intelligence (AI) has also been maturing quickly in the last few years, allowing organizations worldwide to automate drawing insights from vast quantities of data at a faster pace than ever before. As per a recent report, the global geographic information systems (GIS) market is expected to reach US$13.6 billion in 2027, up from US$6.4 billion last year. The amount of data being acquired from satellites is also increasing thanks to the falling costs of electronic components and machine vision exponentially, along with increasing private sector participation. While there were fewer than 20 remote sensing satellite launches in 2008, in this year alone, there have been greater than 150. Our new offering in satellite image segmentation Telescope, powered by Azure, can be integrated seamlessly into Azure storage/database services and build customer-oriented applications to minimize geospatial analysis challenges.ĭuring the last few years, the number of satellites has exploded exponentially.
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