5. How to Detect Crops Early in the Season
Temporal analysis of satellite images
6. Deliverable: Model in Python and Crop Detector
Application
https://youtu.be/EPtDwFKibOI
7. Features:
- Time Series Data
- RGB
- Near-infrared
- vegetation index
- Crop Type:
- 60% corn
- 40% 6 other crops
Image Data
May
July
August
8,000 Images for 900 Fields
11. Images only
RGB, near infrared, vegetation index
24% Error
Random Forest
Crops detectable early in the season!
12. Images only
RGB, near infrared, vegetation index
24% Error
Weather
19% Error
Lasso regression analysis + SMOTE to
balance data sets
Random Forest
Crops detectable early in the season!
min & max temp, precipitation, etc.
13. Images only
RGB, near infrared, vegetation index
24% Error
Weather
19% Error
Lasso regression analysis + SMOTE to
balance data sets
Random Forest
Crops detectable early in the season!
min & max temp, precipitation, etc.
21%
Improvement!
14. Tatiana Dashevskiy
PhD in Physics, Applied dynamical systems in
neuroscience
Post Doc Seattle Children’s Research
Institute