Remote assessment of field productivity zones — another step towards precision farming

Each field has its own self. Every farmer knows: different fields have different fertility potential and different productivity. Some fields are even, with similar productivity across the whole area, some are «motley» with fertile zones neighbouring zones with low productivity. Productivity of different field zones can be detected and assessed with the help of yield maps and NDVI maps.
Yield map is obtained along with combine harvesting using mapping systems. A prerequisite for obtaining an objective yield map is the combine sensors calibration before harvesting. If this is observed, we get a reliable map of data on crop yield at each point of the field. Yield is an integral indicator which depends on the cultivar features of a crop and is influenced by literally all environmental factors and cultivation technologies in this season: weather conditions, soil fertility at each part of the field, slope exposure and steepness, all methods of cultivation technology and scrupulosity in their performance, depth of soil treatment, depth of seeding down and many other things.

As factors act with different force at different points of the field at the same time, it is quite difficult to single out the influence of each given factor using a yield map during one season. In a single year of observation low productivity of some field zones can be occasional, for example, because of local single-shot hail at a part of the field and yield loss in that place. To eliminate the influence of such accidental differences not a single yield map, but a time series of such maps must be used, in other words, a «Washington pie» of yield where each layer is a yield map for one season. It is even better if a multi year set of NDVI spatial distribution maps is used for the fertility assessment time series, not yield maps. This allows to detect low productivity zones having constant localisation with high credibility. If there are such zones at the field and if they are reproduced annually, their occurrence is not accidental, and this is connected with some consistent issue which negatively affects crop development year after year.

What is the reason for low productivity zones occurrence? There can be several reasons. They include field relief peculiarities, agrochemical and agrophysical soil properties, and technological operations influence. All this affects crop condition at different field areas, and we can see it at NDVI maps through the satellite monitoring system. Problem zones will be noticeable both at single maps and when analysing image series. ExactFarming platform allows to compare productivity of different fields on the whole and detect zones of different productivity within a single field. A built-in algorithm allows to detect problem zones - areas where crops develop worse than average year after year. One can get an idea of general field productivity comparing this field with others using the series of historical images for a particular period. Also for each particular field the map of historical productivity can be built, stability and variability in space and time of detected zones of different productivity can be assessed. In ExactFarming field productivity and uneven zones map can be viewed directly from the card of the field. Here the uneven zones area in ha and percentage ratio of zones can also be estimated.
Why get this information? It allows to detect contour of problem and good zones at the field. Zones of different productivity are determined remotely in this case. But to know the reason for this unevenness occurrence and check if it can be eliminated with agricultural methods, additional ground inspections are needed. Using the contour detected, soil sampling for agrochemical analysis is recommended, and then variable rates of fertilisers must be applied at such zones on the results of agrochemical analysis. Also attention must be paid to agrophysical soil properties at different field zones. Perhaps, unevenness is reasoned by agrophysical peculiarities of the zones detected and their hydrological conditions. In this case it is acceptable to apply different seeding norms to different field parts or to change the crop treatment technology. Thus, the historical field productivity map analysis allows to remotely detect zones, that the individual variable rate approach can be consequently applied to, which means direct transition to precision farming technologies.

Author – Sofia Zhelezova, PhD., Biology
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