The world’s population is projected to hit 9 billion people by the end of 2050. Naturally, the consumption of food will rise accordingly. Experts suggest a nearly 70% growth in demand for agricultural products and this is an optimistic forecast considering the overall shortage of cultivated areas and climate change.
Such high demand is pushing agriculture industry to embrace innovations and look for new ways in order to overcome productivity obstacles. Drones are one of the solutions that is already here to intensify farmers’ production.
Drone Mapping Software Market Prospects
The Census of Agriculture numbers around 2.2 million farms in U.S. with a total area of 922 million acres. 88% of those households are small family farms with the average area of 230 acres. This is the best-targeted audience drone industry could ever wish to have.
Just look at this number: 1.85 million farms that can immediately benefit from agricultural drones and eager to do so because of hardening competition and demand increase. Based on these and other figures PwC estimates the market at $32.4 billion. Not bad for a start!
Another thing to mentions: some analytics already site that 80% of the global drone industry revenues are related to agriculture.
Benefits of Drones Used in Agriculture
There is six major application of drones for agricultural use:
As you may notice three of them (field analysis, monitoring, health assessment) are built around field mapping software instead of costly machinery. From an investment point of view, these fields grant a higher return of investment rate and better flexibility in terms of product development process.
Advantages of Farm Mapping Software
Soil and Field Analysis
Thermal image used to find water leaks
The identification of field condition allows farmers to take informed actions, save on irrigation or enhance nitrogen-level management. Drones can acquire precise 3D volumetric data, which reveal hills and drainage points and save on the number of personnel required. Based on this data farmers can plan their planting pattern and distribute crops according to the specifics of the landscape.
It must be acknowledged that vast fields areas become the main stop factor that lowers or even completely negates the crop monitoring. Nevertheless, unpredictable weather conditions require from farmers to take immediate actions without waiting for season end. It is no longer possible to decide what went wrong based on after-effects and season statistics.
Crop monitoring provides flexibility and allows farmers to adjust their strategy during the season and even within a month. Crop monitoring also allows farmers to reduce field maintenance costs and focus only on the most critical areas thus saving their resources.
Previously, crop monitoring was possible only with the help of satellite imagery. Obviously, this service was extremely expensive, an image quality could suffer from weather conditions and resolution left much to be desired. Fortunately, the Unmanned Aerial Vehicles (UAV) are here to become a better alternative.
The health analysis is performed by gathering the data from several sources thermal, multi spectral, infrared sensors. This way farmers can learn a sunlight absorption and transpiration rate of their crops. Further on one could apply NDVI mapping method in order to know health condition of the field.
In essence, normalised difference vegetation index (NDVI) is a mapping method that reveals green portions on the map and indicates early warning based on the slight color deviations of the crops.
Frankly speaking, NDVI is well-known among industry players. What makes it different now is an image resolution and image acquisition speed, that can be achieved using drones instead of satellites. Drones can acquire a much more detailed map and measure areas within centimeters, compared to meters.
“By having this information up-front farmers may be able to turn that from that being a $3,000 to $4,000 a ton yield to $5,000 a ton depending on what the issue actually is.”
Jonathan Smith – Status Imaging Director
The drone can be also used to spot bacterial or fungal infections on trees. The health information can be gathered from multispectral images that track changes in plants and indicate their health. A swift response can save an entire orchard.
In addition, as soon as a sickness is discovered, farmers can use remedies to get a more precise picture and track plant’s condition during treatment in order to identify the efficiency of medicine.
All those mapping practices are used as a foundation to a comprehensive farming management concept called – Precision Agriculture. Precision Agriculture gained a decent popularity inside the industry and viewed as one of most promising trends.
The concept is based on observing, measuring and responding to inter- and intra-field variability in crops. If you need a deeper understanding, here’s a great article The Economist have published on this matter.
The goal is to distribute farm’s resources more efficiently and gain maximum yield of course. This is achieved by minimizing a variability of crop health within a single field, thus taking action point wise.
Agriculture Mapping Software Functions
Obviously, Precision Agriculture requires a lot of data. Moreover, it requires gathering data on regular basis. And that is where drones mapping software comes in handy!
Technically UAV drones can gather a vide variety of data just by capturing imaginary of livestock, fields, and specific plants. Here’s a rough list of info you can acquire from images:
- Plant count, height.
- Plant stress monitoring.
- Leaf area indexing.
- The presence of disease, nutrients, weeds.
- Relative biomass estimation.
- Yield monitoring.
- Animals movement.
- Tree сlassification.
- Drought assessment.
- 3D field surveying (elevations, holes, suitable water drainage points).
How Farm Mapping Software Works
Let’s start from types of imagery that can be acquired by drones:
- Thermal/IR. This kind of sensors can see hotspots and measure land and plant temperature.Thermal sensors are also used to detect the water, because of its cooler temperature signature, which helps detect drought or leak in irrigation.
- Multispectral. Used for health assessment and normalized difference vegetation index.
- LIDAR. Despite its high cost, it may be used once for initial 3D field surveying.
- Hyperspectral data. The combination and overlaying of images from multiple channels used for more in-depth analysis.
How Agricultural Drones and Software Can Measure Health
Most agriculture software uses multi-spectral imagery to reveal health conditions. Based on imagery taken by agricultural drones those algorithms analyze changes of near-infrared (NIR) light and visible light (VIS) reflected by crops.
Specifically, the algorithm analyses the changes in the volume of green color on VIS image and NIR light. Roughly speaking, the more green and reflected light present – the better health of the plant.
By using this data farmers can monitor health changes over time by calculating and tracking NDVI. The NDVI calculation principle is pretty much based on the same method. NDVI = (NIR-VIS)/(NIR+VIS).
Here is an example of the NDVI-processed image.
That’s basically how agricultural health mapping software works.
It must be acknowledged that NDVI is the most popular index but not the most precise one. Hence there are many other indexes that can be added to the agricultural mapping tool, like CWSI (Crop Water Stress Index) and CCCI (Canopy Chlorophyll Content Index), etc.
The development of such sophisticated system can add value to your agriculture apps and get you a better position in a competitive market. But this is another story that requires a deeper dive into the science of agriculture image processing.
We can make one, just get in touch with us to get started!