Comparing it to the greatest revolutions in history of agriculture is not too bold a statement and ambition. By harnessing the still largely untapped power of satellite data analysis, in combination with vast but disperse agronomic knowledge developed to date, we will soon See further, Know earlier, Act quicker.
Unprecedented capabilities are encapsulated into the multiple layers of granular information captured by satellites that continuously orbit around our planet, which includes:
- Real-time production levels and projections;
- Real-time production capacity;
- Accurate agriculture output quality;
- Complete agriculture production planning based on soil fertility and other factors;
- Weather and climate-synchronized calendar for the seeding, fertilization, pruning and harvest timing;
- Early-warnings for crops pests and diseases and related remedy measures planning; and
- Continuous online monitoring and management of the environmental conditions evolutions affecting agriculture production.
We can set a new milestone for agriculture, at the verge of a new, greater challenge for our development of and on this planet: climate change.
Why these ground-breaking capabilities haven’t been explored so far?
Because, despite being known and used for more than 50 years, to mine satellite data presents two main challenges:
Data processing constraints
Firstly, satellite data comes in a plethora of dissimilar data formats. One of the main technical challenges with satellite datasets exploration relates to the capability of making different datasets compatible in order to extract more value for a combined and more complete analysis. The automation of the analysis of satellite data is the single greatest difficulty to extract and make more widely available its benefits.
Data costs constraints
Secondly, the high infrastructure investment in the upstream space industry, which is responsible for providing manufacturing, launching and operating the satellites, is reflected in the high costs of satellite data acquisition. Nowadays, commercial users can pay significant sums for satellite data derived intelligence (on average between $2,000 to $3,000 per task) and a price ranging from $5 to $30 per square kilometre depending on the image resolution. The advent of smaller and cheaper satellites (e.g. cubesats) is promising to shake up the market, but they are some away time from being available.
(Source – http://weathersafe.co.uk/index.php/blog/42-satellite-data-remote-sensing-and-precision-farming-the-revolution-is-our-hands)