Comparison of two aerial imaging platforms for identification of Huanglongbing-infected citrus trees

By F. Garcia-Ruiz, S. Sankaran, J. Maja, Won Suk Lee, Jesper Rasmussen, Reza Ehsani. 2013

336 citations recorded by the source corpus.

Subfields: Ecology, Horticulture, Plant Science

View Paper: https://www.semanticscholar.org/paper/394d9c9d3214a11466c3ab82bed97bb0b5b0dfbf

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Citations in the corpus

Radiometric Calibration for Multispectral Camera of Different Imaging Conditions Mounted on a UAV Platform (2019, methodology): “The system was then used for plant detection by the calculated vegetation index [23].”
Field phenotyping system for the assessment of potato late blight resistance using RGB imagery from an unmanned aerial vehicle (2016, positive): “…recently been applied to crop growthmonitoring (Lelong et al., 2008; Torres-S anchez, Pe~na, Castro, & L opez-Granados, 2014), disease detection (Garcia-Ruiz et al., 2013) and weed detection (Pe~na, Torres-S anchez, Castro, Kelly, & L opez-Granados, 2013; Torres-S anchez, L opez-Granados,…”
Identification of Plant-Leaf Diseases Using CNN and Transfer-Learning Approach (2021, methodology): “SVM is also a popular supervised-machine-learning technique used for classiﬁcation purposes [11,12].”
Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level (2015, background): “In agriculture, tree health monitoring with hyper or multispectral UAV data and image analysis has been studied, for example, in olive orchards [29] and citrus trees [30].”
Unmanned Aircraft System (UAS) Technology and Applications in Agriculture (2019, background): “Popular machine learning models include random forest classifiers, support vector machines, bag of visual words, and convolutional neural networks (CNNs) [29,72,120].”
Unmanned Aerial Vehicles (UAVs) in environmental biology: a review (2019, background): “Garcia-Ruiz et al. (2013) used a hexacopter with a Tetracam camera sensing six narrow bands that could be configured in different ways by centring a particular band at different wavelengths to detect infected orange trees.”
Using Deep Learning for Image-Based Plant Disease Detection (2016, methodology): “…et al., 2012) the detection of citrus huanglongbing using near infrared spectral patterns (Sankaran et al., 2011) and aircraft-based sensors (Garcia-Ruiz et al., 2013) the detection of tomato yellow leaf curl virus by using a set of classic feature extraction steps, followed by…”
Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation (2017, neutral): “[95] for detecting citrus greening and by Yang et al.”
Monitoring cotton (Gossypium hirsutum L.) germination using ultrahigh-resolution UAS images (2018, background): “…et al. 2015), while a georeferenced 2D orthomosaic image provides a uniform scale and geometrically corrected view over the entire test field, facilitating applications such as crop disease and damage detection (Di Gennaro et al. 2016; Garcia-Ruiz et al. 2013; Yang and Hoffmann 2015).”
Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives (2017, methodology): “…multi-band imaging sensor was deployed to acquire high-resolution aerial imaging for Huanglongbing (HLB) detection, which yielding that there’s significant difference for the 710 nm spectral reflectance and the NIR-R index values between healthy and HLB-infected trees (Garcia-Ruiz et al., 2013).”
Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges (2018, neutral): “Another challenge, when UAVs are used to cover large areas, is that it needs to return many times to the charging station for recharging [105], [109], [112].”