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How does Virdis detect unsuitable regions like water bodies, deserts, polar areas, urban zones, or very high altitude regions before generating crop plans? |
Replies: 1 comment
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I built this into Virdis because not every selected polygon should be treated like a farmable field. If a user draws a region that is mostly water, too dry, too cold, too high, or heavily urban, the crop planning system should not try to force a recommendation. That would make the platform feel inaccurate very quickly. So before crop planning begins, I check for edge cases using multiple signals such as:
This lets the system decide whether the region is actually suitable for agricultural planning or whether it should switch to a different mode or block crop recommendations entirely. The main reason for doing this was trust. If the platform confidently suggests crops for a lake or a dense urban area, it stops feeling useful. I wanted the logic to be strict enough to stay realistic, but flexible enough to still work with mixed or borderline regions. That edge case handling ended up being just as important as the analytics itself. |
I built this into Virdis because not every selected polygon should be treated like a farmable field.
If a user draws a region that is mostly water, too dry, too cold, too high, or heavily urban, the crop planning system should not try to force a recommendation. That would make the platform feel inaccurate very quickly.
So before crop planning begins, I check for edge cases using multiple signals such as:
This lets the system decide whether the region is actually suitable for agricultural planning or whether it should switch to a different mode or block crop recommendations entirely.
The ma…