Machine learning interpretation of aerial infrared imagery has been proved to be useful in identifying crops suffering water stress.  Our multispectral and infrared imaging can assist farmers to determine which crops are undergoing water stress, and then pave a way forward to maximising irrigation scheduling.

Normalised Difference Vegetation Index (NDVI) is derived from infrared and near infrared analysis of plant canopies.  It is widely recognized as a useful tool in identifying plant vigour and therefore also plant stress.  We can utilize our infrared and hyperspectral cameras to undertake NDVI surveys to provide fast analysis of crop health and assist in yield prediction at a level of detail not currently possible from satellite imagery.

Our drones are equipped with high-end forward-looking infrared (FLIR) cameras which can quickly identify differences in ground and crop temperatures.   This provides crucial information to farmers such as which areas are receiving too little or too much water, irrigation problems and leaking pipes – even those which are beneath the ground.  Thermal imaging can also identify subtle differences in crop temperatures, which can be useful in detecting a range of pests and plant diseases.

Airborne hyperspectral imaging has been demonstrated as a leading technology in identifying pests and disease in crops such as winegrapes, citrus, almonds, pasture and broad acre crops. It is also useful for identifying weed cover in crops and land condition change.  Modern machine learning algorithms and AI can reliably assist with interpreting these images to provide farmers with accurate analysis of the prevalence of common management problems such as diseases and pests.  By accurately identifying the extent of these problems, we assist farmers to minimize expenditure on fertilisers, pesticides and herbicides, as well as helping with yield prediction.

Counting plants is crucial for farmers in estimating yields and therefore profits.   Aerial imaging provides a unique and speedy method to analyse large areas of crops, fruit trees and vineyards.   These images can then be interpreted using machine learning and AI techniques to reliably provide growers with estimates of plant numbers and plant performance – and therefore predict yields – as well as identify acreage which is underperforming.

Our high-resolution, airborne hyperspectral, infrared and colour cameras place us in a unique position to assist farmers with accurate estimates on crop size, vitality, plant (and variety) numbers, and therefore also profit estimates.  Add to this our machine learning and AI capabilities, AirborneLogic is an ideal partner for farmers seeking to create crop uniformity, maximize yields with minimum inputs.

AirborneLogic offers a diverse range of consulting services to both the private and public sectors.  Whether it is thermal imaging of urban areas, high resolution drone photography or machine learning analysis of hyperspectral imaging, for agriculture, we have a diverse portfolio of clients and capabilities.   Contact us to discuss your requirements.