The benefits of using UAV technology to measure crop health and improve production have excited agriculturalists for years. By seperating light bands such as blue, green, red, and near-infrared and measuring the intensity of light reflected from plants, stress can be identified significantly sooner than with the naked eye. Crop yields can be boosted by using imagery to assist in scouting, identifying nitrogen deficiencies, and detecting faulty application equipment and irrigation systems.
Technologies such as digital cameras, UAVs (Drones) and big data computing have matured to a point where regular, high quality imagery is available to all farmers.
The affordability of unmanned aircraft means that NDVI imagery of your pastures and crops can be collected frequently, processed quickly and acted onb instantly to optimise plant health and maximise crop yeild. Change detection images allow you to quickly determine if problems exist that are causing the vegetation stress.
Information that NDVI images can provide:
- Chlorophyll levels
- Plant stress and health
- Fertilizer optimisation
- Nitrogen management
- Insect, pest ferral animal detection
- Disease detection
- Plant species Identification
- Harvest planning
Thanks to advancements in battery cell technology and the miniturisation revolution, unmanned aerial services have reached a price-point where they are a viable tool for everyone.
UAVs are capable of acquiring high resolution imagery and data. The highest spatial resolution data available from conventional platforms such as satellites and manned aircraft is typically in the range of 20-100 cm/pixel. UAVs are capable of flying much lower and slower. They collect imagery at a resolution 100 to 200 times higher – even as detailed as 1 cm/pixel!
Our UAVs lift high-definition multi-spectral wave length cameras, thermal imagery sensors, LIDAR, FLIR and many other payloads. For precision agriculture multi-spectural imaging is providing significant upside to farmers.
- Visible spectrum cameras create imagery that is processed using feature matching and photogrammetric techniques to create high resolution images of vast blocks of farm land.
- Thermal infra-red cameras can be used to map soil moisture enabling assessment of irrigation efficiency
- Thermal imaging can detect livestock, ferral animal and other heat emitting sources
- Multi spectral cameras enable the calculation of vegetation indices that relate to vegetation vigour and health.
The versatility of the UAV system is enhanced by “on-demand data collection”, providing accurate information that spans the critical times in the crop growing season.
Light Reflectivity in Plants
The Visible Spectrum
The light we see with our eyes is just a small part of the electromagnetic spectrum. The spectrum includes radio waves from long radio waves that we use to broadcast radio and TV to short gamma rays emmitted by the sun. We can use specially designed equipment and sensors to detect specific bands of light and capture bands of light (like infra-red) that are beyond what is normally visible to humans. Specific bands of lightr can be mixed and manipulated to provide an insight into the health of crops, pastures, in fact any vegetation.
There is an infinite number of wavelengths and therefore an infinite number of colours. As light interacts with an object – like a plant, the wavelengths are either absorbed or reflected. Some of the reflected waves reach our eye giving the object its colour.
Plants use more blue and red light for photosynthesis. Much of the green light is reflected giving plants a green colour.
At Uaviation, we over-fly farmland and collect imagery that measures the amount of absorption and reflectance that radiates from crops and pastures. Farmers and agronomists can use that imagery to manage the health of their crops and pastures.
Usable Light Bands
Uaviation’s imagery typically captures four bands of light: red, green, blue, and near-infrared (NIR).
Plant health, type, biomass, stress, damage and many other yeild-affecting factors can be interpreted by manipulating the light bands and measuring reflectivity. We isolate the different bands of light so that points of interest appear throughout the field. These images include Near Infra-red / Red / Green (NRG) and Normalized Difference Vegetation Index (NDVI).
Each band of light in the visible and non-visible spectrum plays a part in understanding plant health.
Multi-spectral imagery manipulates the colour spectrum to make it easier to spot anomalies in crops and pastures – before they affect yield. Differences in colour may indicate an area of concern. In this minupulated image, patches of the field appear yellow and red alerting us to zones that need our attention. Spots in this image were found to be dense patches of healthy blackberry weeds. If left untreated, this area of the field would have yielded poor results over thw seson.
Aerial imagery aids agriculturalists to focus on the areas that need their attention.
Crop Damage and Soil Compaction
Multi-spectral imagery can be a great aid in assessing the impact of crop damage. In this image – courtesy of the Department of Agriculture, the damage to a wheat crop caused
by bands of Australian plague locust nymphs can be viewed and measured.
Soil compaction is difficult to identify from the ground, but its impact is easily identifiable in multi-spectral imagery. Large equipment, high traffic, and early field operations on wet soils create compaction zones.
Irrigation and Fertiliser
In Australia, Irrigation is no small expense. If your crops are heavily dependent on supplemental water during rapid growing periods, it is essential that problems with irrigation are detected as early as possible.
NDVI images of pivot fields and other irrigated fields can identify under and over watering, faulty equipment such as clogged water nozzles, blocked irrigation channels or leaking pipelines.
Nutrient management is expensive and significantly impacts yield. Imagery from before application can assist in planning. Imagery obtained shortly after application can highlight areas of equipment failure during the application process.