Today, we had a regular meeting of the Club of Anonymous Fans and Unmanned Aerial Vehicles and Drones, so it’s time to talk about the practical application of unmanned aerial drones in agriculture in Ukraine. We will speak narrative in the first person, but any similarity of facts and names – is pure coincidence. Sit back, we start.
“We came to do aerial photography on the field with sugar beet. The objectives of the aerial photography of the field with beets have been linked with a desire to improve the economic benefits of growing crops for the Customer. By the way, our Customer was a large agricultural holding with a huge land bank, which was planted not only sugar cane but also other crops. The Customer is interested in the drones, as satellite images were a bit pricey, even for their rubber budget. Therefore, we agreed to our aerial survey methods.
Immediately it should be noted that the management of the Customer is not typical agricultural industry workers, who do everything the old-fashioned style. It was clear that they were willing to take risks for the sake of winning the subsequent (read – a good harvest) so that our cooperation can be attributed it to the category of such risks.
Looking ahead, I note that in their opinion, these risks have paid off and they got what they wanted. Although this benefit is indirect, because the value was not derived from data from drones pictures, and by improving the quality of work of employees of the Customer. I will explain in detail: the majority of Customer’s employees knew that either the drones or any other unmanned vehicles will fly over the fields and monitor the growth of plants. Therefore, all employees tried to work more efficiently and did not want to get punished for bad attitude to work, and that, accordingly, has yielded good results in terms of productivity of their fields. In short, the use of unmanned aerial vehicles improved a discipline of the Customer’s employees.
But, from the point of view of efficiency of application of geoinformation technologies, I can say that the work was carried out efficiently, although the interpretation of the data obtained during aerial drones has been ineffective.
And now I will explain why.
Let’s start with a specific purpose – why did we take this aerial photography? To be able to analyze the level of beet seedlings after seeding, to evaluate the quality of seeds, the need for top dressing, but most importantly – to take effective decisions and act. That is, to save the crop, where the worst of vegetation indices were obtained. It is also important to understand that these actions are not made globally, in other words, not the entire field, but locally and point, in those places where we saw a negative trend.
Somewhere in a month, our goals were scaled and we also do aerial photos to identify the place of condensation of undesirable vegetation, ie weeds that struggle was better and more effective with them. Again, we had to deal with the localization of specific point of foci of such undesirable vegetation. By the way, to kill weeds many companies use manned aircraft and the complex of aviation-chemical works, although it should be borne in mind that these chemicals work negatively affect the yield of major crops.
With goals completed.
So what have we had in practice?
First, we flew about ten fields (total area of 70 square kilometers). We took height – 100 meters, with a resolution of 1.5 cm / pixel. Beet shoots could be seen clearly, but immediately faced with the problem of huge amounts of data to quickly process and analyze that just unreal. And whether it is necessary?
Plus there were problems with the performance of work of our team. We flew 12 flights (three flight days of four flights each day) using our UAV “Peter be-E”, and managed to take only a tenth of the required material.
In the calculations, we assumed that planting beets lasted about two weeks. In fact, we had to carry out an aerial survey for the same time. In the end, we came to the conclusion that the time is very expensive to fly with full coverage and overlap for stitching. Therefore, we made a representative survey, the overlapping on the direct and, therefore, the data obtained from our 10% shot areas can be interpreted for the entire crop area.
Of course, first of all, it affected the representativeness because we simply define a coating which we have to fly around to meet deadlines. In addition, we are seriously puzzled by the problem of image processing with high extension. Calculate the amount for beet bushes in each frame, you can use the program to analyze images with Definiens. Of course, the cost of using this software is very expensive – more than 20 000 euros for a single license. But you can get started with a trial version, and the results of the use to decide whether it is necessary at all. Although more interesting for us was not only counting the number of bushes in each frame image, but also the construction of the bushes density function per unit area. The order of frames we have arranged according to the log file on a digital map of the terrain … “
At this point we briefly interrupted. Stay tuned.
Continuing the story, read our blog tomorrow. In the meantime, we wish you a successful flight and high-precision images!