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GSi-Platform
Predicative modelling to forecast outcomes under different scenarios.
GSi-Platform
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GSi-Timber
GSi-Timber, a world first, where big data meets big forests.
GSi-Timber
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GSi-Carbon
GSi-Carbon has full global coverage of forest carbon stocks back to 2001
GSi-Carbon
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GSi-Blowdown
Monitoring forest damage caused by extreme weather events.
GSi-Blowdown
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GSi-Crop
GSi-Crop provides mapped crop yield predictions for any given crop.
GSi-Crop
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GSi-Soil
A remote sensing solution to monitor soil carbon.
GSi-Soil

Predictive Analytical Software

Why is GSi Unique? GSi has developed highly efficient machine learning predictive analytical software which has proven to be over 100,000 times faster than readily available open source software.

This level of performance means you can generate new insights on new scales.  The machine learning element allows the software can be trained to understand what it is analysing, before making quantifiable predictions.

The quantification provides peace of mind as it really helps you understand the accuracy and credibility of the results.

The software can analyse complex data sets with multiple variables and inputs.   One of those inputs can be remote sensing observations from satellite where GSi has a particular skill base, or equally plane or unmanned aerial vehicle (UAV) observations.  Earth observation analytics has, until now, usually been carried out on one or a few images and requiring manual interpolation.

Big Data Analytics

GSi has managed to take this to a completely new level, by applying big data analytics with machine learning. The big data element enables GSi to capture and analyse multiple images to provide a continuous analysis, not just at local scales, but even globally.

For example, GSi has captured satellite observations covering the earth’s surface of the planet every eight days  all the way back from 2001.  GSi processes, filters and analyses these satellite images to allow for an on-going global big data time-series analysis.  GSi can work with any remote sensing observations at any resolution.

Furthermore, remote sensing imagery is often confounded by errors from cloud cover, atmospheric distortion and geographic projection.  GSi has developed unique methods which enables it to detect and remove such errors.  This enables GSi to observe the earth more clearly, to reduce errors and make better predictions , constantly and on global scales.