This is an example and starting point for multispectral image analysis designed for beginngers. The lessons can be taught in approximately 2 hours. They start with importing and visualizing drone based multispectral data in QGIS and move through how to extract data values for areas of interest in both a manual, low throughput method and a more automated, high throughput method.
These methods were first developed for analyzing drone based multispectral images for the Grain Cropping Systems Lab at UC Davis and thus are geared towards use in agronomic crops in a research settting. The methods can be used with different image caputre (such as satillite) as well as in different research or production settings.
These methods have been presented at Maptime Davis (Analyzing Drone Data October 2018) , UC Davis Plant Sciences Drone Data in Ag Research workshop (March 2019) and will be a part of UC ANR's DroneCamp 2020 (Multispectral Data Visualization and Extraction with QGIS).
- To install QGIS go to: https://qgis.org/en/site/forusers/download.html. For more detailed instructions about how to install QGIS go to: https://qgis.org/en/site/forusers/alldownloads.html. These lessons currently use the long-term (most stable) release of QGIS, QGIS 3.10.5 (A Coruña).
- QGIS is available on Windows, macOS, Linux and Android. Please note that these lessons were developed and tested on Windows. The software appearance and behavior may differ based on operating systems.
If you have any questions or feedback, please open an issue or contact Taylor Nelsen (mailto:[email protected])
Please cite as
Nelsen, Taylor, Drone-Data-in-Agricultural-Research, 2020, GitHub repository, https://github.com/tnelsen/Drone-Data-in-Agricultural-Research