Spatio-temporal monitoring of wheat yellow rust using UAV multispectral imagery

[Display omitted] •A dedicated aerial system is developed for persistent crop monitoring.•Spatio-temporal monitoring is performed for wheat yellow rust.•Various indices are used for wheat segmentation at different stages.•Sensitive bands/indices for yellow rust severity are dynamically identified. T...

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Veröffentlicht in:Computers and electronics in agriculture 2019-12, Vol.167, p.105035, Article 105035
Hauptverfasser: Su, Jinya, Liu, Cunjia, Hu, Xiaoping, Xu, Xiangming, Guo, Lei, Chen, Wen-Hua
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container_start_page 105035
container_title Computers and electronics in agriculture
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creator Su, Jinya
Liu, Cunjia
Hu, Xiaoping
Xu, Xiangming
Guo, Lei
Chen, Wen-Hua
description [Display omitted] •A dedicated aerial system is developed for persistent crop monitoring.•Spatio-temporal monitoring is performed for wheat yellow rust.•Various indices are used for wheat segmentation at different stages.•Sensitive bands/indices for yellow rust severity are dynamically identified. This work is focused on the spatio-temporal monitoring of winter wheat inoculated with various levels of yellow rust inoculum during the entire growth season. A dedicated workflow is devised to obtain time-series five-bands (visible-infrared) aerial imageries with a multispectral camera and an Unmanned Aerial Vehicle. A number of spectral indices are drawn so that the sensitive ones can be identified by statistical dependency analysis; particularly, their discriminating capabilities are evaluated at different stages for both wheat pixel segmentation and yellow rust severity. Then the spatial-temporal changes of sensitive bands/indices are evaluated and analysed quantitatively. A validation field experiment was designed in 2017–2018 by inoculating wheat with one of the six levels of yellow rust inoculum. Five-bands RedEdge camera on-board DJI S1000 was used to capture aerial images at eight time points covering the entire growth season at an altitude of about 20 meters with a ground resolution of 1–1.5 cm/pixel. Experimental results via spatio-temporal analysis show that: (1) various bands/indices should be used for wheat segmentation at different stages; (2) no bands/indices differences are observed for yellow rust inoculated wheat plots in both incubation stage (9 days after inoculation) and early onset stage (25 days after inoculation); (3) NIR and Red are the sensitive bands for wheat yellow rust in disease stages (45 days after inoculation); and their normalized difference NDVI index provides an even higher statistical dependency; (4) bands/indices’ sensitivity to yellow rust changes over time and decreases in later Heading stage until being very low in Ripening stage (61 days after inoculation). This experimental study provides a crucial guidance for future early spatio-temporal yellow rust monitoring at farmland scales.
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This work is focused on the spatio-temporal monitoring of winter wheat inoculated with various levels of yellow rust inoculum during the entire growth season. A dedicated workflow is devised to obtain time-series five-bands (visible-infrared) aerial imageries with a multispectral camera and an Unmanned Aerial Vehicle. A number of spectral indices are drawn so that the sensitive ones can be identified by statistical dependency analysis; particularly, their discriminating capabilities are evaluated at different stages for both wheat pixel segmentation and yellow rust severity. Then the spatial-temporal changes of sensitive bands/indices are evaluated and analysed quantitatively. A validation field experiment was designed in 2017–2018 by inoculating wheat with one of the six levels of yellow rust inoculum. Five-bands RedEdge camera on-board DJI S1000 was used to capture aerial images at eight time points covering the entire growth season at an altitude of about 20 meters with a ground resolution of 1–1.5 cm/pixel. Experimental results via spatio-temporal analysis show that: (1) various bands/indices should be used for wheat segmentation at different stages; (2) no bands/indices differences are observed for yellow rust inoculated wheat plots in both incubation stage (9 days after inoculation) and early onset stage (25 days after inoculation); (3) NIR and Red are the sensitive bands for wheat yellow rust in disease stages (45 days after inoculation); and their normalized difference NDVI index provides an even higher statistical dependency; (4) bands/indices’ sensitivity to yellow rust changes over time and decreases in later Heading stage until being very low in Ripening stage (61 days after inoculation). 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subjects Agricultural land
Cameras
Dependence
Image segmentation
Inoculation
Inoculum
Monitoring
Multispectral image
Pixels
Ripening
Spatio-temporal analysis
Statistical dependency
UAV remote sensing
Unmanned aerial vehicles
Wheat
Workflow
Yellow rust
title Spatio-temporal monitoring of wheat yellow rust using UAV multispectral imagery
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