Olive Tree Water Stress Detection Using Daily Multispectral Imagery
- Resource Type
- Conference
- Authors
- Brinkhoff, James; Schultz, Alex; Suarez, Luz Angelica; Robson, Andrew J.
- Source
- 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Geoscience and Remote Sensing Symposium IGARSS , 2021 IEEE International. :5826-5829 Jul, 2021
- Subject
- Aerospace
Geoscience
Photonics and Electrooptics
Signal Processing and Analysis
Irrigation
Sensitivity
Planets
Vegetation mapping
Real-time systems
Sensors
Indexes
Olive
Remote Sensing
Water Stress
- Language
- ISSN
- 2153-7003
Daily calibrated multispectral imagery (Planet Fusion) of an olive irrigation deficit trial was used to assess the degree and speed to which vegetation indices indicate water stress. We developed normalization techniques to increase sensitivity to differences across a grove. The normalized difference vegetation index (NDVI) was able to significantly detect differences between the control and deficit treatments for the Arbequina variety. For the Picual variety, the green red vegetation index (GRVI) was the best indicator. Though multispectral imagery is not as quick at indicating irrigation deficits as in-field sensor data, it is complementary in being able to capture the spatial variability of water stress.