Abstract
Abstract. The use of Unmanned Aerial Vehicle (UAV) imagery systems for Precision Agriculture (PA) applications drew a lot of attention through the last decade. UAV as a platform for an imagery sensor is providing a major advantage as it can provide high spatial resolution images compared to satellite platform. Moreover, it provides the user with the ability to collect the needed images at any time along with the ability to cover the agriculture fields faster than terrestrial platform. Therefore, such UAV imagery systems are capable to fit the gap between aerial and terrestrial Remote Sensing. One of the important PA applications that using UAV imagery system for it showed great potentials is weed management and more specifically the weed detection step. The current weed management procedure depends on spraying the whole agriculture field with chemical herbicides to execute any weed plants in the field. Although such procedure seems to be effective, it has huge effect on the surrounding environment due to the excessive use of the chemical, especially that weed plants don’t cover the whole field. Usually weed plants spread through only few spots of the field. Therefore, different efforts were introduced to develop weed detection techniques using UAV imagery systems. Though the different advantages of the UAV imagery systems, they systems didn’t draw the users interest due to many limitations including the cost of the system. Therefore, the proposed paper introduces a new weed detection methodology from RGB images acquired by low-cost UAV imagery system. The proposed methodology adopts detecting the high-density vegetation spots as indication for weed patches spots. The achieved results showed the potential of the proposed methodology to use low-cost UAV imagery system equipped with low-cost RGB imagery sensor for detecting weed patches in different cropped agriculture fields even from different flight height as 20, 40, 80, and 120 meters.
Highlights
Starting from mid-1980’s, the concept of smart farming or precision agriculture (PA), has been raised in the agriculture industry as a management system. later, during the last two decades, the PA was considered as one of the top ten revolutions in the agriculture industry (Crookston, 2006)
The methodology was capable to indicate if the image of the field contains a large weed patch or just small scattered of weed plants as shown in case (7) in figure (7), as the weed image as totally black which means that the system didn’t detect any weed patches
The proposed paper provides a new weed detection methodology that can be used as part of a smart weed management system
Summary
Starting from mid-1980’s, the concept of smart farming or precision agriculture (PA), has been raised in the agriculture industry as a management system. later, during the last two decades, the PA was considered as one of the top ten revolutions in the agriculture industry (Crookston, 2006). To enhance the quality and quantity of the field’s output while protecting the surrounding environment from any harm that might be caused due to the excessive use of these inputs (Zhang and Kovacs, 2012) To perform such smart management system, it is important to collect different information and process them to make the farmer able to take the right decision at the right time for the right spot of the field (Mulla, 2012). RS technology showed huge ability to provide valuable information for the farmer through using satellite or airborne platforms for different imagery systems Such systems acquire images covering large areas within short time (Zhang and Kovacs, 2012). Weed is any wild plant that grows in the agriculture field which
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