Earth Observation Remote Sensing
Since the 1972 launch of Landsat -1 , thousands of earth and weather observation satellites have been launched. Nearly 971 EO satellites were in orbit around earth in late 2020 according to the Union of Concerned Scientists.
In all there are some 4,900 active satellites in space today. Their numbers are growing exponentially with weekly launches of satellites in private/ commercial communication as well as EO Low Earth Orbit (LEO) constellations.
This has led to hundreds of petabytes of Earth Observation data ( 1 PB is 1,048,576 GB of data. In scale, that is equal to 1,000 high resolution images per day on your phone for your entire life.).
Satellites not only take very high resolution images of planet earth, they are fitted with a range of sensors.
Satellites are equipped with sensors capturing multiple spectral bands, from visible to infrared, at high spatial resolution.
They include visible-light cameras, infrared and microwave radiometers, spectrometers, ultraviolet backscatter sensors, colour scanners; hyperspectral sensors that combine information from several spectral bands; multi-angle spectrometers combine the views from several azimuths; Synthetic Aperture Radar (SAR) that can sense through cloud cover and without daylight, and more.
Land use decision making in the world is largely at the industrial age era of 1800s and in many cases at pre-industrial levels without widespread use of data and digital tools or what we call #natureinformatics.
$13 billion nature based global economy hardly uses these #naturemetrics for smart decision making.
(The WEF report calculates that nearly 15% of global GDP is highly dependent on nature, while moderately dependent industries generate 37% ($31 trillion).
Statistics are besides the point because decisions on planet’s life giving Oxygen, Food and water should be based on these #naturemetrics. They are not.
At ForestSAT we are great believers in democratisation of earth observation data and machine learning tools so that use of EO data becomes as prevalent globally as the use of an X-Ray machine was in 1980s and CT Scans now are to medical care worldwide. Just as It would be impossible to imagine basic healthcare, surgical interventions and effective treatments without use of radiology by doctors worldwide.
Similarly we believe EO data & #natureinformatics should be universally available and become basic tool to digital age land use, forest preservation and conservation.
#NatureTech is digitally powered Land Use decision making based #naturemetrics
We are using machine learning on #NatureMetrics , or years of data on burned forest areas in temperate forests to reverse engineer forest fires and analyse the health of trees, soil, flora and fauna in standing forests to understand the change that can lead to a forest turning into a tinderbox, ready to explode and die.
We are developing a deep understanding of complex dynamics in forest ecosystems to understand cause and effect sequences to the minutest of details so as to accurately predict risk of fires in specific areas and be able to develop AI to deliver actionable recommendations and decision support to prevent fires. Regenerate and re-green forests so that they are resilient enough to be our gift to coming generations for thousands of years.
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