Crop development
Anomalous dynamics in crops: an early satellite signal
Anomalous dynamics is a sharp or unusual change in a crop that does not fit the normal course of the season for that crop and stage. It is not a diagnosis but an early signal that something is wrong: the cause may be stress, an abrupt change in field work, extreme weather or an artefact in the image. Its value is spotting a problem before the more specific risks are triggered.
Crops: Cotton, Wheat, Rice
When it is dangerous
The signal works all season, with no link to crop stage. It is potentially the earliest signal of all, and also the noisiest.
Causes
- Crop stress with a cause not yet known
- An abrupt change in field operations
- Extreme weather
- Clouds, shadows or an image processing error
Signs on the field
- Field greenness drops or rises sharply outside the normal seasonal course
- The field behaves differently from what is expected for the crop and stage
- A sudden jump in crop moisture or in the radar signal
How ClusterOS notices it
ClusterOS builds the expected seasonal course of a field from NDVI and NDMI, indices of green biomass and crop moisture from Sentinel-2 optical images, and looks for break points where the series departs sharply from it. The main source of noise is clouds, shadows and atmospheric correction errors: without a good cloud mask false alarms would dominate. The signal is more reliable when confirmed by Sentinel-1 radar, which sees through clouds. The signal itself does not name a cause: that comes from the other risks on the field and, for an important alert, a field visit.
What to do
- Check whether other risks are flagged on the field for the same dates
- Compare with the weather and the operations log for those dates
- Check the image for clouds or shadows over the field
- If the signal repeats on clear images, visit the field
Questions
What does an anomaly mean in satellite crop monitoring?
It is a sharp or unusual change in the field indices compared with the expected course of the season. It tells you that something changed on the field, not what changed – the cause is found separately.
Why do false anomalies happen?
Most often because of clouds, shadows and image processing errors. That is why the signal is checked against neighbouring clear images and against radar, which does not depend on cloud cover.
Learn about this risk on your fields before it becomes a loss
We will show ClusterOS on your own fields: history since 2019, crop stage and all 24 risks.
Other risks in «Crop development»
Scientific basis
- Verbesselt J., Hyndman R., Newnham G., Culvenor D. (2010) Remote Sensing of Environment 114(1):106–115, DOI: 10.1016/j.rse.2009.08.014
- Verbesselt J., Zeileis A., Herold M. (2012) Remote Sensing of Environment 123:98–108, DOI: 10.1016/j.rse.2012.02.022