Precision weed management, an application of precision agriculture, accounts for within-field variability of weed infestation and herbicide damage. Unmanned aerial vehicles (UAVs) provide a unique platform for remote sensing of field crops. They are more efficient and flexible than manned agricultural airplanes in acquiring high-resolution images at low altitudes and low speeds. UAVs are more universal than agricultural aircraft, because the latter are used only in specific regions. We have developed and used UAV systems for red–green–blue digital and color–infrared imaging over crop fields to identify weed species, determine crop injury from dicamba at different doses, and detect naturally grown glyphosate-resistant weeds. This article presents remote sensing technologies for weed management and focuses on development and application of UAV-based low-altitude remote sensing technology for precision weed management. In particular, this article futher discusses the potential application of UAV-based plant-sensing systems for mapping the distributions of glyphosate-resistant and glyphosate-susceptible weeds in crop fields.

Traditional field survey methods for detection of water leaks in irrigation canal systems are costly and timeconsuming. In this study, a rapid, cost-effective method was developed for identifying irrigation canal locations likely to have leaks and/or seepage. The method involves the use of a multispectral imager equipped with red, near infrared, and thermal sensors which is mounted on an aircraft and flown at low altitude to collect the images. A three-step process, image acquisition, image processing, and field reconnaissance, was developed for processing the imagery and identification of locations likely to have leaks. The method was evaluated in the Lower Rio Grande Valley of Texas, USA. Images were collected of 24 selected canal segments within 11 irrigation districts in this region. Evaluation of the imagery indicated that 140 sites had possible canal leakage problems (point leak and/or seepage). A field site evaluation form was developed and used to document the type and severity of the leaks at 28 of the sites. Twenty-six sites were confirmed to have leaks, representing a success rate of 93%. The methods used in this study should have widespread application for detecting leaks and seepage in irrigation canals. Les méthodes utilisées dans cette étude devraient avoir une application généralisée de détection des fuites et des infiltrations dans les canaux d'irrigation.

GR and GS Palmer amaranth plants have unique hyperspectral reflectance properties, and there are four distinct regions of the spectrum that can separate the GR from GS plants. These results demonstrate that hyperspectral imaging has potential application to distinguish GR from GS Palmer amaranth plants (without a glyphosate treatment), with future implications for glyphosate resistance management. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

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