High-resolution airborne hyperspectral and thermal imagery for early detection of Verticillium wilt of olive using fluorescence, temperature and narrow-band spectral indices.

doi:10.1016/J.RSE.2013.07.031

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High-resolution airborne hyperspectral and thermal imagery for early detection of Verticillium wilt of olive using fluorescence, temperature and narrow-band spectral indices.

Journal Article•DOI•

High-resolution airborne hyperspectral and thermal imagery for early detection of Verticillium wilt of olive using fluorescence, temperature and narrow-band spectral indices.

Rocío Calderón¹, Juan A Navas-Cortes¹, Carlos José Pereira de Lucena¹, Pablo J. Zarco-Tejada¹•Institutions (1)

Spanish National Research Council¹

01 Dec 2013-Remote Sensing of Environment (Elsevier)-Vol. 139, pp 231-245

TL;DR: In this article, the authors explored the use of high-resolution thermal imagery, chlorophyll fluorescence, structural and physiological indices (xanthophyll, carotenoids and blue/green/red B/G/R indices) calculated from multispectral and hyperspectral imagery as early indicators of water stress caused by Verticillium wilt infection and severity.

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About: This article is published in Remote Sensing of Environment.The article was published on 2013-12-01. It has received 334 citations till now. The article focuses on the topics: Water flow & Chlorophyll fluorescence.

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Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges

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Hazim Shakhatreh¹, Ahmad Sawalmeh², Ahmad Sawalmeh³, Ala Al-Fuqaha⁴, Ala Al-Fuqaha⁵, Zuochao Dou, Eyad Almaita⁶, Issa Khalil⁷, Noor Shamsiah Othman², Abdallah Khreishah⁸, Mohsen Guizani⁹ - Show less +7 more•Institutions (9)

Yarmouk University¹, Universiti Tenaga Nasional², Northern Borders University³, Western Michigan University⁴, Khalifa University⁵, Tafila Technical University⁶, Qatar Computing Research Institute⁷, New Jersey Institute of Technology⁸, University of Idaho⁹

26 Aug 2021

TL;DR: The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civil application domains, including real-time monitoring, providing wireless coverage, remote sensing, search and rescue, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection.

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Abstract: The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civil application domains, including real-time monitoring, providing wireless coverage, remote sensing, search and rescue, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. Smart UAVs are the next big revolution in the UAV technology promising to provide new opportunities in different applications, especially in civil infrastructure in terms of reduced risks and lower cost. Civil infrastructure is expected to dominate more than $45 Billion market value of UAV usage. In this paper, we present UAV civil applications and their challenges. We also discuss the current research trends and provide future insights for potential UAV uses. Furthermore, we present the key challenges for UAV civil applications, including charging challenges, collision avoidance and swarming challenges, and networking and security-related challenges. Based on our review of the recent literature, we discuss open research challenges and draw high-level insights on how these challenges might be approached.

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901 citations

Cites background from "High-resolution airborne hyperspect..."

...For instance, aerial thermal images can be used to detect early stage development of soil-borne fungus [123]....
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Journal Article•DOI•

Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry

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Telmo Adão, Jonáš Hruška, Luís Pádua, Jose Bessa, Emanuel Peres, Raul Morais, Joaquim J. Sousa - Show less +3 more

30 Oct 2017-Remote Sensing

TL;DR: A survey including hyperspectral sensors, inherent data processing and applications focusing both on agriculture and forestry—wherein the combination of UAV and hyperspectrals plays a center role—is presented in this paper.

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Abstract: Traditional imagery—provided, for example, by RGB and/or NIR sensors—has proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can provide. This kind of high-resolution spectroscopy was firstly used in satellites and later in manned aircraft, which are significantly expensive platforms and extremely restrictive due to availability limitations and/or complex logistics. More recently, UAS have emerged as a very popular and cost-effective remote sensing technology, composed of aerial platforms capable of carrying small-sized and lightweight sensors. Meanwhile, hyperspectral technology developments have been consistently resulting in smaller and lighter sensors that can currently be integrated in UAS for either scientific or commercial purposes. The hyperspectral sensors’ ability for measuring hundreds of bands raises complexity when considering the sheer quantity of acquired data, whose usefulness depends on both calibration and corrective tasks occurring in pre- and post-flight stages. Further steps regarding hyperspectral data processing must be performed towards the retrieval of relevant information, which provides the true benefits for assertive interventions in agricultural crops and forested areas. Considering the aforementioned topics and the goal of providing a global view focused on hyperspectral-based remote sensing supported by UAV platforms, a survey including hyperspectral sensors, inherent data processing and applications focusing both on agriculture and forestry—wherein the combination of UAV and hyperspectral sensors plays a center role—is presented in this paper. Firstly, the advantages of hyperspectral data over RGB imagery and multispectral data are highlighted. Then, hyperspectral acquisition devices are addressed, including sensor types, acquisition modes and UAV-compatible sensors that can be used for both research and commercial purposes. Pre-flight operations and post-flight pre-processing are pointed out as necessary to ensure the usefulness of hyperspectral data for further processing towards the retrieval of conclusive information. With the goal of simplifying hyperspectral data processing—by isolating the common user from the processes’ mathematical complexity—several available toolboxes that allow a direct access to level-one hyperspectral data are presented. Moreover, research works focusing the symbiosis between UAV-hyperspectral for agriculture and forestry applications are reviewed, just before the paper’s conclusions.

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736 citations

Cites methods from "High-resolution airborne hyperspect..."

...Verticillium wilt—which is a disease that affects olive cultures in the way that it blocks the water flow at the vascular plant level—was studied by [138] with the use of thermal imagery, chlorophyll fluorescence, structural and physiological indices (xanthophyll, chlorophyll a + b, carotenoids and blue/green/red B/G/R indices) calculated from multispectral and hyperspectral data as early indicators of the infection’s presence and severity....
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Journal Article•DOI•

Machine Learning for High-Throughput Stress Phenotyping in Plants

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Arti Singh¹, Baskar Ganapathysubramanian¹, Asheesh K. Singh¹, Soumik Sarkar¹•Institutions (1)

Iowa State University¹

01 Feb 2016-Trends in Plant Science

TL;DR: This work provides a comprehensive overview and user-friendly taxonomy of ML tools to enable the plant community to correctly and easily apply the appropriate ML tools and best-practice guidelines for various biotic and abiotic stress traits.

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633 citations

Cites background from "High-resolution airborne hyperspect..."

...[11], hyperspectral [12–15], thermal [16,17], fluorescence [16,18], and 3D laser scanning [19] to trichromatic (RGB) [20] imaging in conjunction with advanced autonomous vehicles, have truly opened up the possibility of high-throughput stress phenotyping (HTSP)....
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Journal Article•DOI•

Overview and Current Status of Remote Sensing Applications Based on Unmanned Aerial Vehicles (UAVs)

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Gonzalo Pajares¹•Institutions (1)

Complutense University of Madrid¹

01 Apr 2015-Photogrammetric Engineering and Remote Sensing

TL;DR: An overview of different areas of remote sensing applications based on unmanned aerial platforms equipped with a set of specific sensors and instruments is presented, each independent from the others so that the reader does not need to read the full paper when a specific application is of interest.

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Abstract: Remotely Piloted Aircraft (RPA) is presently in continuous development at a rapid pace. Unmanned Aerial Vehicles (UAVs) or more extensively Unmanned Aerial Systems (UAS) are platforms considered under the RPAs paradigm. Simultaneously, the development of sensors and instruments to be installed onboard such platforms is growing exponentially. These two factors together have led to the increasing use of these platforms and sensors for remote sensing applications with new potential. Thus, the overall goal of this paper is to provide a panoramic overview about the current status of remote sensing applications based on unmanned aerial platforms equipped with a set of specific sensors and instruments. First, some examples of typical platforms used in remote sensing are provided. Second, a description of sensors and technologies is explored which are onboard instruments specifically intended to capture data for remote sensing applications. Third, multi-UAVs in collaboration, coordination, and cooperation in remote sensing are considered. Finally, a collection of applications in several areas are proposed, where the combination of unmanned platforms and sensors, together with methods, algorithms, and procedures provide the overview in very different remote sensing applications. This paper presents an overview of different areas, each independent from the others, so that the reader does not need to read the full paper when a specific application is of interest

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587 citations

Journal Article•DOI•

Advanced methods of plant disease detection. A review

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Federico Martinelli¹, Riccardo Scalenghe¹, Salvatore Davino¹, Stefano Panno, Giuseppe Scuderi², Paolo Ruisi¹, Paolo Villa³, Daniela Stroppiana³, Mirco Boschetti³, Luiz Ricardo Goulart, Cristina E. Davis⁴, Abhaya M. Dandekar⁴ - Show less +8 more•Institutions (4)

University of Palermo¹, University of Catania², National Research Council³, University of California⁴

01 Jan 2015-Agronomy for Sustainable Development

TL;DR: Modern methods based on nucleic acid and protein analysis are described, which represent unprecedented tools to render agriculture more sustainable and safe, avoiding expensive use of pesticides in crop protection.

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Abstract: Plant diseases are responsible for major economic losses in the agricultural industry worldwide. Monitoring plant health and detecting pathogen early are essential to reduce disease spread and facilitate effective management practices. DNA-based and serological methods now provide essential tools for accurate plant disease diagnosis, in addition to the traditional visual scouting for symptoms. Although DNA-based and serological methods have revolutionized plant disease detection, they are not very reliable at asymptomatic stage, especially in case of pathogen with systemic diffusion. They need at least 1–2 days for sample harvest, processing, and analysis. Here, we describe modern methods based on nucleic acid and protein analysis. Then, we review innovative approaches currently under development. Our main findings are the following: (1) novel sensors based on the analysis of host responses, e.g., differential mobility spectrometer and lateral flow devices, deliver instantaneous results and can effectively detect early infections directly in the field; (2) biosensors based on phage display and biophotonics can also detect instantaneously infections although they can be integrated with other systems; and (3) remote sensing techniques coupled with spectroscopy-based methods allow high spatialization of results, these techniques may be very useful as a rapid preliminary identification of primary infections. We explain how these tools will help plant disease management and complement serological and DNA-based methods. While serological and PCR-based methods are the most available and effective to confirm disease diagnosis, volatile and biophotonic sensors provide instantaneous results and may be used to identify infections at asymptomatic stages. Remote sensing technologies will be extremely helpful to greatly spatialize diagnostic results. These innovative techniques represent unprecedented tools to render agriculture more sustainable and safe, avoiding expensive use of pesticides in crop protection.

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553 citations

Cites background from "High-resolution airborne hyperspect..."

...Recently, the fusion of thermal, fluorescence and optical hyperspectral airborne data has been successfully used to assess olive plants infected by Verticillumwilt (Calderón et al. 2013)....
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Derivation of leaf-area index from quality of light on the forest floor

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Carl F. Jordan

01 Jul 1969-Ecology

TL;DR: The Leaf—area index of a forest can be measured by determining the ratio of light at 800 μm to that at 675 μm on the forest floor, based on the principle that leaves absorb relatively more red than infrared light.

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Abstract: Leaf—area index of a forest can be measured by determining the ratio of light at 800 μm to that at 675 μm on the forest floor. It is based on the principle that leaves absorb relatively more red than infrared light, and therefore, the more leaves that are present in the canopy, the greater will be the ratio.

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Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture

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D. Haboudane¹, John R. Miller¹, John R. Miller², Elizabeth Pattey³, Pablo J. Zarco-Tejada⁴, Ian B. Strachan⁵ - Show less +2 more•Institutions (5)

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15 Apr 2004-Remote Sensing of Environment

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01 Feb 1996-Remote Sensing of Environment

TL;DR: In this paper, the sensitivity of the normalized difference vegetation index (NDVI) to soil background and atmospheric effects has generated an increasing interest in the development of new indices, such as the soil adjusted vegetation index, transformed soil-adjusted vegetation index and atmospheric resistant vegetation index.

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Carnegie Institution for Science¹

01 Jul 1992-Remote Sensing of Environment

TL;DR: In this article, the authors presented a new "physiological reflectance index" (PRI) isolated from narrow waveband spectral measurements of sunflower canopies, which correlates with the epoxidation state of the xanthophyll cycle pigments.

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"High-resolution airborne hyperspect..." refers background or methods in this paper

...Leaf-level measurements conducted for temperature, stomatal conductance, fluorescence and the PRI570 in healthy and VW symptomatic trees showed that Tc − Ta and PRI570 were sensitive to V. dahliae infection and subsequent fungal colonization of affected trees and not simply influenced by structural effects driven by water stress....
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...At leaf level, the reduction in transpiration and G caused by VW infection was associated with a significant (P b 0.05) increase in the PRI570 and a decrease in fluorescence....
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...Leaf and near-canopy field measurements were conducted in the olive orchard located in Castro del Rio (Cordoba) during the summer of 2011 to take: a) diurnal measurements throughout the day to monitor the diurnal variation of crown temperature (Tc − Ta) and stomatal conductance (G) in trees covering a gradient in severity levels; and b) leaf and crown measurements at midday to monitor the variation along the VW severity levels of Tc − Ta, leaf chlorophyll fluorescence, leaf Photochemical Reflectance Index (PRI570) (Gamon et al., 1992) and leaf stomatal conductance (G)....
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...…(G) in trees covering a gradient in severity levels; and b) leaf and crown measurements at midday to monitor the variation along the VW severity levels of Tc − Ta, leaf chlorophyll fluorescence, leaf Photochemical Reflectance Index (PRI570) (Gamon et al., 1992) and leaf stomatal conductance (G)....
[...]
...Moreover, PRI570 was lowest (P b 0.05) in asymptomatic trees, and increased steadily with the increase in VW severity (Fig....
[...]

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Canopy temperature as a crop water stress indicator

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Ray D. Jackson, Sherwood B. Idso, Robert J. Reginato, Paul J. Pinter

01 Aug 1981-Water Resources Research

TL;DR: In this paper, a crop water stress index (CWSI) was calculated using infrared thermometry, along with wet and dry-bulb air temperatures and an estimate of net radiation.

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Abstract: Canopy temperatures, obtained by infrared thermometry, along with wet- and dry-bulb air temperatures and an estimate of net radiation were used in equations derived from energy balance considerations to calculate a crop water stress index (CWSI). Theoretical limits were developed for the canopy air temperature difference as related to the air vapor pressure deficit. The CWSI was shown to be equal to 1 - E/Ep, the ratio of actual to potential evapotranspiration obtained from the Penman-Monteith equation. Four experimental plots, planted to wheat, received postemergence irrigations at different times to create different degrees of water stress. Pertinent variables were measured between 1340 and 1400 each day (except some weekends). The CWSI, plotted as a function of time, closely paralleled a plot of the extractable soil water in the 0- to 1.1-m zone. The usefulness and limitations of the index are discussed.

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1,642 citations

"High-resolution airborne hyperspect..." refers background or methods in this paper

...Thermal remote sensing of water stress has been fulfilled using spectrometers at ground level (Idso et al., 1981, 1978; Jackson et al., 1977, 1981), thermal sensors at image level (Berni, Zarco-Tejada, Suárez, & Fereres, 2009; Cohen, Alchanatis,Meron, Saranga, & Tsipris, 2005; Leinonen & Jones,…...
[...]
...Working with hand-held infrared thermometers on herbaceous crops, Jackson and co-workers (Idso et al., 1978; Jackson et al., 1981) developed the Crop Water Stress Index (CWSI), which became a popular thermal-based stress indicator....
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