Welcome to Skippy Scout
Skippy Scout provides a complete crop scouting solution, from initial field overview via satellite data or your own imported maps, through to fast, automated drone flight and image collection, to the new image analysis and field reporting system.
Crop yield strongly correlates to how much time and effort farmers and agronomists put into checking and analysing fields, soil and the crop in question when out scouting. Identifying early signs of weeds, pest damage and disease is paramount when crop scouting so that the farmer can act quickly to resolve the problem.
We use Skippy Scout to do just that.
The best way to get a closer look at a crop is through scouting. This usually means walking through fields looking for these early signs. While this technique has been used for generations and is still used today, it does have its limitations;
With modern field sizes growing all the time, traditional field walking is becoming less and less efficient. This is where Skippy Scout comes into play.
Most people choose the walking pattern of a “W” through the field to get a good idea of general crop health, and to spot any problems which could be occurring, however by using Skippy Scout, you can massively broaden this search and capture crop information that contains much more detail.
By sending Skippy to the corners of the field and including places you wouldn’t have walked in your usual “W” pattern, you can get a greater understanding of the field, whilst still walking the same amount of ground or even less ground, if you wanted to put more trust into Skippy!
Skippy Scout has built-in satellite data for the “Business” and “Enterprise” level subscriptions, granting access to the latest NDVI (Normalised Difference Vegetation Index) maps for your fields, making scout point selection far easier.
How to prepare for crop scouting using other maps:
Before scouting, it’s a good idea to get a general overview of the field, in order to know where there could be potential problems.
NDVI is a multispectral index that is commonly applied to multispectral satellite data to create a map. The index provides numerical values corresponding to vegetation health, and these values range in the form of decimal points, from -1 to 1 and give an indication of “Near Infrared” (NIR) reflectance in the canopy. These NDVI values are usually very accurate at early stages of growth, but then plateau once a crop’s canopy is too thick, because the satellite’s sensors cannot pick up a value that represents the whole plant.
That being said, a Business or Enterprise tier Skippy user would not have to take any of these numerical values into account, as Skippy would provide them with an up-to-date satellite “heat map”, showing red vs green, where green indicates high growth and red indicates low growth or crop senescence.
Skippy automatically provides this satellite layer within the app, meaning that it can be used to dictate where scout points are placed; whether it’s in anomalous red areas which usually indicate lower growth, or uncharacteristically green areas, which could mean high crop growth, but sometimes indicate high growth of something that is not “supposed” to be there i.e. weeds. You could even look at certain areas of interest on foot and have the drone cover the rest of the field.
It’s also a good idea to look at previous crop cycles. Yield maps as well as emergence maps from previous years can show areas which have caused problems before. This could be down to topography, typical pest damage or different soil types among many other factors. It’s always important to look at these to make educated decisions on how to tackle a given problem. If an area of the field gets flooded every year it might be better to pull it out of rotation rather than spend money and resources on it for very little return.
The next step is creating a scouting route. This is all down to a user’s judgement. It’s a good idea to send skippy to a variety of points around the field as it generates a field report with health averages in it, at the end of every flight. For users who don’t want to rely 100% on the software, a different route of the standard “W” formation can be completed whilst the drone is off doing its own points.
How to scout an OSR field using Skippy Scout:
If you have not yet downloaded or activated the app you can follow the simple guides here: https://skippy.farm/how-it-works-v2-5/
First, check the NDVI overlay on the field to look for areas with high and low growth. If you are on the standard farmer subscription which does not have satellite data included, previous field knowledge can be very valuable. Even a random point selection over the whole field (provided it covers the field evenly) can work well.
After selecting the points (we recommend a maximum of around 25), the “scout now” button can now be selected and your iPhone or iPad can be connected to a DJI drone, such as a Mavic 2, Mavic Air 2 or Phantom 4.
The app will then create a flight plan between its takeoff location and the various scout points, and will complete a series of pre flight checks before giving you the option to “fly now”.
When “fly now” is tapped, the app will control the drone, taking off and starting the automated flight. At every point, it will drop to 2 metres above the crop and take a single image. At the end of the flight these images will be uploaded to Skippy’s servers, where the AI system will analyse them.
Within minutes, a PDF field report containing all of the flight’s images and the results from the AI’s analysis of those images, will be sent to your email address.
At each point, the AI will have now calculated the crop’s Green Area Index (GAI), percentage cover, discoloured leaves/unhealthy crop, weed presence, disease presence and even pest damage.
This level of analysis on the side of the field is essential for making accurate decisions as fast as possible and the GAI calculations can help you make informed spray and fertiliser decisions. It will help to see if more fertiliser is needed on a specific part of the field to even out the crop cover. The new trends function on the field reports is also great at looking at the field on a larger scale. It will portray the changes between two different flights so that it’s possible to see if the field’s condition is improving or declining. A recently added flower fraction calculation although in its early stages can help when deciding on spray timings for Oilseed Rape crops and a field report including this calculation can be seen below.