We have been testing and comparing four different methods for collecting spatial information about onion crops and their development, looking to identify variability.
The tools used are:
- GreenSeeker NDVI (supported by AgriOptics) (Time series here)
- CoverMap canopy cover (supported by ASL) (Time series here)
- UAV imagery (supported by Altus UAS)
- Satellite imagery (obtained 23 November 2016)
We’ve mapped the paddock many times now using both CoverMap and GreenSeeker using different logging software.
We found the CoverMap app is very sensitive to brightness. Initially we were mapping sun and shade variation depending on which way the tractor faced and if cloud cover changed. By wrapping the system so only diffuse light reaches the area we are getting much more stable images.
The GreenSeeker software limited the number of points we could record. We get four times as many using alternative software, so the GreenSeeker itself can record dense information. The image below is a canopy map created from the GreenSeeker data. It shows variation in NDVI, the normalised difference vegetation index.
The map above is a corresponding map created from CoverMap data collected at the same time as the GreenSeeker NDVI. The map looks more “speckly”. This is because it was made from many more data points so identifies variation in more detail.
We think the GreenSeeker and CoverMap maps do show a similar story. We attempted a statistical comparison by “overlaying” the maps and comparing points. The results are shown in the graph below.
We see some agreement shown by this analysis. How much is expected?