Many agronomists and farm managers are familiar with the use of ET-based irrigation scheduling.
Crop Water Use (ETc) = Reference Evaporation (ETo) x Crop Coefficient (Kc), or simply [ETc=ET0 * Kc].
The Kc is a simplified way of representing the ratio of water use by the crop in question, and required farm manager/agronomist to closely follow the crop development and understand field variability to accurately determine it, and prescribed the required water amount. See the reference guide from the California Almond board, as an example.
Use of remote sensing imagery in the estimation of crop water use
In practice, it is simply not possible to regularly take measurements of both the evapotranspiration in several areas in each block in your orchard with the pressure bombs, and accurately determine the Kc coefficient for each of the representative management zones.
FluroSense platform developed by FluroSat offers its customers, including the global drip-irrigation leader, Netafim, access to weather data, and remote sensing data, including high-resolution and Terravion aerial imagery. This combination of information allows agronomists to take accurate data-driven irrigation management decision. Let's see how!
As presented by Netafim's chief R&D agronomist, Dr Itamar Nadav on the webinar with FluroSat, Netafim has conducted countless studies across the globe to determine and verify correlations between remote sensing imagery and frequently used vegetation indices, like NDVI and crop-specific coefficients, Kc's. See the relationships that they derived on the graph below.
As you can see, the study results presented above demonstrate that NDVI and Kc for citrus and almonds crops, in particular, are highly correlated. Hence agronomists and farm managers can rely on NDVI measurements to schedule irrigation by replacing the Kc with the NDVI through the transformation described below.
Turning remote sensing imagery into actionable information with FluroSense
It is not straightforward, however, to derive the NDVI for each block of trees, given that the signal reflected in remote sensing imagery combines both the soil reflectance and the NDVI of the tree canopy. Here Netafim has benefited from the Tree health monitoring algorithms developed by FluroSat in its FluroSense platform. The raw NDVI imagery gets transformed into an NDVI score for each individual tree, which makes it extremely easy to use NDVI for irritation instead of Kc.
Thermal imagery to replace time-consuming measurements of crop stem water potential
With the recently Terravion's latest pan-sharpened thermal imagery added to FluroSense tree analysis, we found even more proof points to demonstrate to you why you should include remote sensing-based analytics into your orchard managem4nt routine.
The temperature values extracted on the per-tree basis by FluroSense algorithms from this "crisp" thermal image (shown above) has been found to have a very high correlation (R2=0.8) with the stem water potential of the almond trees depicted in the imagery above.
Practical tips on how to improve your operations through the adoption of remote sensing
This is one more proof point that irrigation can be done using remote sensing imagery. If thermal imagery is not available to you, you can simply use NDVI. You can also see that both NDVI and thermal imagery closely reflects the EC map of the orchard in question, giving yet another reason to start looking at your trees "from above" and getting accurate per-tree management reports.
If you are a current Terravion customer, FluroSat offers you free Flurosense demo and report on your imagery. If you are interested to get your orchard management to the next level of granularity, get in touch!
If you are interested to learn more about the research into use of remote sensing for tree coop irrigation management, watch the full webinar below.
Happy irrigation scheduling!
[VirtualAg Expert Series] Tree crop irrigation management using remote sensing delivered by Netafim and FluroSat