As we know, crop yield estimation has been done traditionally with farmer's expert knowledge, deductive sampling in representative areas, and remote sensing with satellite imagery. Farmer's Expert knowledge might be biased and not data driven. Deductive sampling are limited to spatial variability, cost-intensive and laborious. Similarly, satellite imagery has many challenges such as limited spatial and temporal resolution and has limited accuracy in field level yield estimation. Other way of yield estimation is using previous years yield distribution to generate yield map for current years but it can't represent current growing conditions. So how UAV can be useful in such situation for better yield estimation.
my project is exactly in this area. Sampling and measuring spatial data in agriculture with drones. Artificial Intelligence can be used to help the drone decide where should it go to make samples. Also, if the sample locations are known, Orienteering Problem can be used to solve it.
The benefit using UAV for estimating crop yield:
1. Saving time
2. High accuracy
3. Cover large area
4. Low cost (high cost only at the beginning, for investing UAV)
5. Generate Big Data
6. Those data can be used to train Artificial Intelligence for detecting pest and disease during agriculture process, so at the end can provide accurate crop yield
7. Real time compare to satellite imagery
8. Having Fun :-) for hobbyist
It would be necessary for the drone to be equipped with a multispectral camera, in this way the development of the crops can be followed with an appropriate technique such as taseled cap.
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