Chapter 8

UAV Remote Sensing in Precision Agriculture

UAV Remote Sensing Applications in Precision Agriculture

Unmanned Aerial Vehicles (UAVs) are now very commonly used in remote sensing applications for precision agriculture. Equipped with sensors of different types, UAVs can be exploited to identify which zones of the crops need different management, e.g. some kind of input. This gives the farmers the ability to react on time in any problem detected. UAVs can be used in a plethora of different applications on precision agriculture, such as health monitoring and disease detection, growth monitoring and yield estimation, weed management and detection, etc. can be exploited in a variety of applications related to crops management, by capturing high spatial and temporal resolution images. These technologies are expected to revolutionize agriculture, enabling decision-making in days instead of weeks, promising significant reduction in cost and increase in the yield.

Weed Mapping and Management

Among the most popular applications of UAVs in precision agriculture is Weed mapping. The use of herbicides is the dominant choice for weed control. In conventional farming, the most common practice of weed management is to spray the same amounts of herbicides over the entire field, even within the weed-free areas. However, the overuse of herbicides can result in the evolution of herbicide-resistant weeds and affect the growth and yield of the crops.

Sensors

Remote sensors for weed detection play a crucial role in modern agriculture by identifying and monitoring weeds in fields efficiently and accurately. These sensors use various technologies to capture data, process it, and differentiate between crops and weeds based on their unique properties.

Machine Learning for Mapping Weeds

Machine learning (ML) for weed detection has revolutionized modern agriculture by providing accurate, efficient, and scalable methods for distinguishing weeds from crops. Machine learning leverages data from various sensors (e.g., RGB, multispectral, hyperspectral, LiDAR, thermal) to train models that can classify, detect, and map weeds in agricultural fields. Machine learning is a general term for automated pattern recognition in which a computer groups data based on various feature descriptors.

Crop Monitoring and Yield Estimation

UAVs are also frequently used to monitor the growth of crops and provide estimations regarding yield. The lack of means for systematically monitoring the progress of cultivation is considered one of the major obstacles to increasing agricultural productivity and quality. Regular collection of information and visualization of crops using UAVs provides increased opportunities to monitor crop growth and record the variability observed in several parameters of the field.

Disease and Insect Surveillance

Satellite RS is generally used for large-scale studies. However, the use of satellite platforms for the detection of diseases and insects is limited owing to the high spatial and temporal resolution of data required for this purpose. More so, the availability of cloud-free data during the crop season is another issue that limits the use of satellites. UAVs are considered one of the most efficient methods for disease and insect surveillance, monitoring, and management solutions.

Machine Vision and Machine Learning for Detecting o Insect Pests and Diseases

Deep learning algorithms have recently emerged as a promising new alternative to enhance computer vision-based systems for autonomous crop disease and insect monitoring. Without any human assistance, they can perform autonomous feature extraction, providing farmers with data that might improve crop yields and decrease treatment costs. Some plants do not have visible symptoms of infection, and the effect becomes noticeable too late for any action to be taken. Although some diseases produce some manifestation in the visible spectrum for a trained pathologist to detect, variations in symptoms could lead to false identification.

Phenotyping

UAV-based field phenotyping has become a common method to estimate crop phenotypes due to the platform’s capacity to capture and/or directly measure field traits with one or more sensors. RGB sensors are commonly used to monitor crop height dynamics. These sensors allow the creation of DEMs through a photogrammetric SfM process.

Crop Spraying

In addition to assisting in data collection, UAVs have the potential to carry out site-specific interventions within the scope of precision agriculture. In this sense, spraying of agricultural pesticides stands out since traditional spraying systems, whether manual, tractor, or aerial, do not always meet the particular needs of the production system. Vertical takeoff, ability to maneuver in a small space, automated and geolocated operation, quick access to points of interest, and difficulty to access without causing damage to the crop are some of the favorable features that make UAVs suitable for agricultural spraying.

UAVs Versus Aircraft Crop Spraying

Precision Targeting. One major difference between spray drones and traditional aircraft crop spraying is the level of precision targeting each option offers. Spray drones have sophisticated GPS and GIS technology that allows them to map out the exact areas that need treatment and deliver chemicals with extreme accuracy. On the other hand, aircraft spraying, while efficient over large expanses, often lacks this degree of precision. The altitude and speed of planes and helicopters can lead to a wider dispersal pattern.

Swath Testing

Before applying pesticides with your spray drone, it is highly recommended to perform swath testing using water-sensitive papers (WSP) or a continuous sheet of paper to determine the effective swath using the intended application parameters, i.e., height, speed, and nozzle type/droplet size. It is very important to understand the drone's spray performance (coverage) and adjust the swath accordingly to avoid significant application issues. The major drawback of WSP is that the assessment is performed visually using handheld lenses, and the card side-by-side is compared with known spray patterns.

Label Restrictions

In addition to the requirement for registering a drone, two certificates must be obtained from FAA to spray using drones: an FAA “Part 107 Certificate” to fly a drone and a “Part 137 Certificate” to apply pesticides using drones or to apply pesticides using drones while under the direct supervision of a person who holds this certificate.

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