We all know that fields have natural variations that are often hard to be physically measured. As a result, some areas boast more lush vegetation growth, while others might become little barren wastelands. This happens not because of imprecise application of fertilizers, but without precise knowledge about the field’s variations, proper application can be quite challenging.
For example, too little nitrogen starves your crops, but an overdose creates an imbalance of salt and water in the soil, thus dehydrating your plants. What’s worse, excessive levels of nitrogen in the soil contribute to the overall greenhouse effect, moreover, also leading to the waste of money and resources. If only there was a way to find out beforehand exactly where to apply more fertilizer, and where less. Enter zoning.
Crop Zoning From Space
We offer a solution to the problem of identifying the areas with higher or lower productivity. EOSDA Crop Monitoring is equipped with a field zoning feature, based on high-resolution satellite imagery, and the vegetation index per pixel calculations. Check out how many variations your field actually has and apply fertilizers accordingly.
Where Do I Start?
Okay, so to use the feature, you need to go to a zoning tab. As you can see, the symbol serves as a tell-tale sign: an arrangement of several agricultural zones of different sizes.
One click should be enough to take you to the Zoning tab. Check the title at the top of the fields list and the symbol to the right, to make sure.
On the right side of the screen, you should see the full list of the fields you have already added to the system in the Fields tab.
To find a particular field you want, either scroll down the list or enter the name/coordinates in the search bar.
Scrolling is easy: click and drag the scrollbar to the right, or simply roll the mouse wheel while hovering over the list.
You start with the natural view of your field. Let’s see how to break it into zones step-by-step.
- Select the spectral index. Five are currently available: NDVI, NDRE, MSAVI, ReCl, and NDMI.
You always know which vegetation index has been selected by looking at the Vegetation Index bar.
2. Select the date. Zoning-based view of the field is only available on the dates when the image was taken by a satellite, and if the clouds did not form an obstacle.
Click the little arrow and scroll through the drop-down list of available cloudless images.
3. Decide on a number of zones that you would like to break your field into. You may choose any number between 2 and 7.
4. Set the minimal zone area, if you like. 1000 square meters is the default minimum which you can set to a higher number, but not lower.
5. You’re all set now. Calculate away!
How Many Zones Would You Like?
Depending on how thorough you want to be with applying fertilizers, you can break the field in up to 7 zones. This is how the view based on the three zones will look like on the screen:
It already gives a rough idea of the vegetation variations within the field: high, middle, and low.
By increasing the number of zones, you will get a higher degree of variation, thus getting more detailed feedback about your field.
For comparison, here is a field with four zones:
As you can see, among and around the two of the previously established zones, there is an additional irregular pattern of a slightly different color. This might prompt you to investigate by sending scouts to check if there are any issues with how the crops are growing within the strange pattern.
However, you might want to consider to keep increasing the number of zones to get a better picture.
You can try 5, 6, or even 7 zones!
Now, a strange pattern within the high vegetation zone has been revealed. Its color is just one grade lower, so it should not be a huge problem at the moment. Nevertheless, it could signal a serious underlying problem. In any case, it is worth a check.
Pay attention to the menu on the right: it tells you that the saturated green stands for the highest vegetation level detected by the satellite, while the red indicates the lowest. Between them, there are shades of green and orange, serving as higher or lower values.
Finally, the seven zones might give you a picture similar to the one above, with maximum detail. The green here has turned out to be not as uniform as it seemed in the three-zoned view. At this level of detail, we recommend a cautious approach before taking a final step, i.e. applying fertilizers. It is advisable to treat this image as a hypothesis that must be tested by a scout’s presence in the field.
(An object causing obfuscation/An object obstructing the image)
A rogue object, such as a cloud or plane, that happened to be over the field when an image was taken, might make a field or part of it go red. In other words, the system can mistake an obstruction of view for a low vegetation index. No worries! Just find a horizontal slider under “Opacity” in the menu to see if there were any objects caught in the image. To do this, move the slider all the way left, until the field’s natural view is back on the screen.
Opacity is automatically set at an optimal value of 80%, to both retain a well-defined zone division and get a possible glance at a rogue object if there are any. But as you move the slider to the left, the appearance gradually changes to the natural view.
With opacity set at 0%, you can’t see any zones, while 100% opacity won’t show you any clouds, even if there are some over the field. The answer is somewhere in the middle. Move the slider to the left or right, to be absolutely sure about the legitimacy of the low vegetation readings.
Send Out The Scouts
The next stage is to send people to the field to physically investigate the potential problem areas detected through zoning. An application is your online assistant, a powerful tool, with almost supernatural abilities. However, it should not be treated as a replacement for every other field-management technique, but rather a useful measurement tool.
Having taken all of the necessary precautions described above, you can now spread the correct amount of fertilizer over different areas of the field. To do this, simply set the necessary UOM/ac values accordingly for each zone.
The system automatically calculates the total amount of nutrients required for one acre (or hectare for the metric system), taking into account the zone’s area value. When the calculations are ready, you can download both the image and UOM values as a zip file. This file is recognized by such major suppliers as Amazon, Trimble, Raven, AG Leader, John Deere, Topcon, among others.
The Zoning feature is digital farming in action, with satellites monitoring your crops, and bringing the analyzed data to your screen. Our task was to make the user-experience better, so a farmer could manage fields with considerably less effort. If used properly, Zoning will save you a lot of time and resources. It will help keep those crops growing healthy and their yields increasing.
Kateryna Sergieieva joined EOS Data Analytics in 2016. She has a Ph.D. in information technologies and a 15-year experience in remote sensing.
Kateryna is a Senior Scientist at EOSDA. Her specialty is the development of technologies for satellite monitoring of natural and artificial landscapes and surface feature change detection. Kateryna is an expert in the analysis of the state of mining areas, agricultural lands, water objects, and other features based on multi-layer spatial data.
Kateryna is an Associate Professor conducting research at the Dnipro University of Technology. She is the author of over 60 scientific papers.