Aerial Imaging: A Bird's Eye View to the Future of Agriculture (original) (raw)
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Software applications for the use of aerial images in precision agriculture
2019
Precision agriculture represents a new branch developed due to the new technologies, which represents, for most farmers, a challenge in their use in order to obtain improved productions from year to year, and the conservation of the potential of agricultural lands. Determining the problems of agricultural crops, was done recently through field inspections, which requires a great deal of time. The emergence of drones, dedicated applications for using the results obtained with the help of drones and other new technologies, such as multi-spectral satellite imagery, opens a new perspective for farmers, which allows them to obtain better results in the field of crops but also the conservation of agricultural land. The use of drones and the applications dedicated to the processing of the data obtained with them, will allow to increase the efficiency of the farms and also to conserve the potential of agricultural lands. It will be possible to determine precisely the areas in which to inter...
The use of a UAV as a remote sensing platform in agriculture
2009
One of the limitations of using hobbyist remotely controlled aircraft with an attached digital camera is that a great number of images look alike and unless a large number of natural features or artificial targets are present at the location, it was hard to identify and orientate the images. This paper investigates the use of an unmanned aerial vehicle (UAV) for use in agricultural applications. Trials were conducted, in collaboration with researchers from the Australian Research Centre for Aerospace Automation (ARCAA)-Queensland University of Technology (QUT), on the ability of the UAV autopilot to accurately trigger the 2-camera sensor when at a desired location. The study area was located at Watts Bridge Memorial Airfield, near Toogoolawah (152.460º,-27.098º) in South East Queensland, Australia. The airfield has dedicated areas for use of remotely controlled aircraft, with the mission being undertaken on 5 March 2008. The target and waypoints were arranged so that the UAV flew in an anticlockwise flight pattern. Three separate missions were flown with images being acquired when over target on each of the nine passes. Although capturing the target in the image was achieved on every flight, the accuracy of capturing the target in the middle of the image was variable. The offset from the centre of the image to the target (zero in the perfect system) ranged from just under 15 to just over 60 % of the image extent. The misalignment was due to a combination of crosswind , GPS / autopilot error, the UAV not being level when the image was acquired, and / or inaccuracies in positioning the sensors in the hinged pod. The capacity to accurately acquire images over predetermined points is essential to ensure coverage and to expedite mosaicing of the images. It will also expand the application of these technologies into the broader-scale applications, such as imaging in broadacre cereal cropping or imaging along transects.
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1988
Field trials play an important role in plant breeding. However, the heterogeneity of fields is a serious problem since it severely influences the comparison of varieties of cultivated plants. The use of aerial photography for mapping the heterogeneity of a trial field with one barley variety was evaluated. By performing additional grain yield measurements at sample points it was shown that the infrared reflectance could be used for estimating yield (linear correlation coefficient 0~90). As a result the spatial pattern of infrared reflectance displayed the spatial pattern of grain yield. Results will be used for improving the experimental lay-out of field trials.
A Toolbox for Aerial Image Acquisition and its Application to Precision Agriculture
Precision farming has increasingly focused on lowering production costs. Remote sensing techniques, mainly aerial imagery in the visible and infrared bands, have been employed to achieve this goal. The GPS (Global Positioning System) system allows easy geo-referencing of these images, making it possible to produce maps showing problems in the crop that can be easily located and corrected. The main problem is the high cost associated with the acquisition of aerial photographs with the necessary periodicity. This paper introduces TIA, a Toolbox for aerial Image Acquisition. TIA adds tools to manned and unmanned aircraft, easing tasks associated with acquisition and processing of aerial imagery. The first step towards implementation of TIA was a requirements analysis that produced a list of useful functions. These functions include mission planning, automatic mission execution, pilot guidance and geo-referencing of photographs and video frames using a GPS receiver. TIA was implemented in an architecture composed of three computer modules: a Palmtop computer that acts as a display/keyboard unit, a main computer and a camera controller. Each computer module has a corresponding software module. The toolbox has been tested onboard a ultralight aircraft and is currently being integrated into a fixed-wing unmanned aerial vehicle (UAV). To evaluate the usability of TIA, a test mission was carried out at a big farm, in the central savannas of Brazil. About 360 photographs were taken from an 800 ha crop area. Images were segmented using a technique based on neural networks. Results have revealed several problems on the fields, including nematode and weed infestation, irregular seeding, and water erosion. It is expected that its use in the next season at the farm will result in substantial gains in productivity, through the periodical analysis of the aerial imagery collected and the adoption of intra season corrective measures. Further work on TIA includes new tests using a near infrared camera, a stability augmentation system for light aircraft flying, an altitude laser sensor for photographic scale correction and a self-levering camera support.
Airborne video systems for agricultural assessment
Remote Sensing of Environment, 1991
Remote sensing data has not been used to its fullest potential for management of natural resources largely because these data are not readily available. Video remote sensing has been proposed as an alternative to provide near-real-time information about natural resources. This paper reviews the status and development of airborne video imaging systems and their application for resource management, with special emphasis on agriculture. Video imagery has been used to detect or assess a variety of agricultural variables such as plant species, chlorosis, grass phytomass levels, cotton and alfalfa root rot infestations, Wind erosion, soil moisture and irrigated crops, soil drainage and salinity, and insect pests. The digitization and computer processing of video imagery has also been demonstrated. Presently video does not have the detailed resolution of film, but it can provide farm managers with immediately available remote sensing data that can allow them to make quick decisions concerning their operations.
Image analysis aplications in precision agriculture
Revista Visión electrónica, 2017
Unmanned Aircraft Vehicles (UAVs) are currently used for multiple applications in various fields: forestry, geology, the livestock sector and security. Among the most common applications, it is worth to stand out the image acquisition, irrigation, transport, surveillance and others. The study that one presents treats of the implementations that are realized by means of aerial images acquired with UAVs directed to the farming. Images acquired until recent years had been using satellites, however due to the high costs that are incurred and low accessibility to these technologies, UAVs, have become a tool for greater precision and scope for making decisions in agriculture. Information from databases of international magazines, groups and research centers is taken to determine the current state of implementations in Precision Agriculture (PA). This article describes tasks such as: soil preparation; limits and land areas, vegetation monitoring; classification of vegetation, growth, height, plant health; diseases management, pests and weeds, fertilization and inventory developed from analysis of aerial images acquired with UAVs
2011
This work presents a solution for the aerial coverage of a field by using a fleet of aerial vehicles. The use of Unmanned Aerial Vehicles allows to obtain high resolution mosaics to be used in Precision Agriculture techniques. This report is focus on providing a solution for the full simultaneous coverage problem taking into account restrictions as the required spatial resolution and overlap while maintaining similar light conditions and safety operation of the drones. Results obtained from real field tests are finally reported