Wheat lodging assessment using multispectral uav data

S. Chauhan, R. Darvishzadeh, Y. Lu, D. Stroppiana, Mirco Boschetti, Monica Pepe, A.D. Nelson

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Abstract

Lodging is a major yield-reducing factors in wheat, causing reductions up to 80%. Timely detection of lodging can reduce its impacts and support proper decisions regarding expected yield, crop price or its insurance. Since the incidence of lodging is heterogeneous within a field, very high-resolution remote sensing data can be viable for accurate and prompt spatio-temporal assessment of lodging severity. As such unmanned aerial vehicles (UAVs) provide a versatile and cost-effective solution to monitor crops on a small scale with sub-centimetre spatial resolution. In this study, we analysed the spectral variability between different grades of lodging severity (non-lodged (NL), moderate (ML), severe (SL) and very severe (VSL)) and classified them using high-resolution UAV data. Multispectral orthomosaic UAV images with 5cm resolution and nine bands (covering the VIS-NIR spectrum with Sentinel-2 filters) were acquired in May 2018 for two wheat fields in Bonifiche Ferraresi farm, Jolanda di Savoia, Italy. Concurrent to the time of image acquisition, a field campaign was carried out in which crop characteristics and lodging related parameters were collected. The results showed that reflectance magnitude increased with lodging severity and demonstrated that the red-edge and NIR bands can be used to clearly discriminate between NL and lodged (all grades) wheat and to some extent between different lodging classes (ML, SL and VSL). The nearest neighbourhood classification performed using an object-based segmentation yielded optimal results with an overall accuracy of 90%, thus demonstrating the use of multispectral UAV data as a promising tool for wheat lodging assessment.
Original languageEnglish
Title of host publicationThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
EditorsG. Vosselman, S.J. Oude Elberink, M.Y. Yang
Place of PublicationEnschede
PublisherInternational Society for Photogrammetry and Remote Sensing
Pages235-240
Number of pages6
Volume42
Edition2/W13
DOIs
Publication statusPublished - 4 Jun 2019
Event4th ISPRS Geospatial Week 2019 - University of Twente, Enschede, Netherlands
Duration: 10 Jun 201914 Jun 2019
Conference number: 4
https://www.gsw2019.org/

Publication series

NameInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
PublisherCopernicus
ISSN (Print)1682-1750

Conference

Conference4th ISPRS Geospatial Week 2019
CountryNetherlands
CityEnschede
Period10/06/1914/06/19
Internet address

Fingerprint

wheat
lodging
crop
crop yield
segmentation
reflectance
spatial resolution
farm
filter
remote sensing
vehicle
cost

Cite this

Chauhan, S., Darvishzadeh, R., Lu, Y., Stroppiana, D., Boschetti, M., Pepe, M., & Nelson, A. D. (2019). Wheat lodging assessment using multispectral uav data. In G. Vosselman, S. J. Oude Elberink, & M. Y. Yang (Eds.), The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2/W13 ed., Vol. 42, pp. 235-240). (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives). Enschede: International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprs-archives-XLII-2-W13-235-2019
Chauhan, S. ; Darvishzadeh, R. ; Lu, Y. ; Stroppiana, D. ; Boschetti, Mirco ; Pepe, Monica ; Nelson, A.D. / Wheat lodging assessment using multispectral uav data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. editor / G. Vosselman ; S.J. Oude Elberink ; M.Y. Yang. Vol. 42 2/W13. ed. Enschede : International Society for Photogrammetry and Remote Sensing, 2019. pp. 235-240 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives).
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abstract = "Lodging is a major yield-reducing factors in wheat, causing reductions up to 80{\%}. Timely detection of lodging can reduce its impacts and support proper decisions regarding expected yield, crop price or its insurance. Since the incidence of lodging is heterogeneous within a field, very high-resolution remote sensing data can be viable for accurate and prompt spatio-temporal assessment of lodging severity. As such unmanned aerial vehicles (UAVs) provide a versatile and cost-effective solution to monitor crops on a small scale with sub-centimetre spatial resolution. In this study, we analysed the spectral variability between different grades of lodging severity (non-lodged (NL), moderate (ML), severe (SL) and very severe (VSL)) and classified them using high-resolution UAV data. Multispectral orthomosaic UAV images with 5cm resolution and nine bands (covering the VIS-NIR spectrum with Sentinel-2 filters) were acquired in May 2018 for two wheat fields in Bonifiche Ferraresi farm, Jolanda di Savoia, Italy. Concurrent to the time of image acquisition, a field campaign was carried out in which crop characteristics and lodging related parameters were collected. The results showed that reflectance magnitude increased with lodging severity and demonstrated that the red-edge and NIR bands can be used to clearly discriminate between NL and lodged (all grades) wheat and to some extent between different lodging classes (ML, SL and VSL). The nearest neighbourhood classification performed using an object-based segmentation yielded optimal results with an overall accuracy of 90{\%}, thus demonstrating the use of multispectral UAV data as a promising tool for wheat lodging assessment.",
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Chauhan, S, Darvishzadeh, R, Lu, Y, Stroppiana, D, Boschetti, M, Pepe, M & Nelson, AD 2019, Wheat lodging assessment using multispectral uav data. in G Vosselman, SJ Oude Elberink & MY Yang (eds), The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2/W13 edn, vol. 42, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, International Society for Photogrammetry and Remote Sensing, Enschede, pp. 235-240, 4th ISPRS Geospatial Week 2019, Enschede, Netherlands, 10/06/19. https://doi.org/10.5194/isprs-archives-XLII-2-W13-235-2019

Wheat lodging assessment using multispectral uav data. / Chauhan, S.; Darvishzadeh, R.; Lu, Y.; Stroppiana, D.; Boschetti, Mirco; Pepe, Monica; Nelson, A.D.

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. ed. / G. Vosselman; S.J. Oude Elberink; M.Y. Yang. Vol. 42 2/W13. ed. Enschede : International Society for Photogrammetry and Remote Sensing, 2019. p. 235-240 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AB - Lodging is a major yield-reducing factors in wheat, causing reductions up to 80%. Timely detection of lodging can reduce its impacts and support proper decisions regarding expected yield, crop price or its insurance. Since the incidence of lodging is heterogeneous within a field, very high-resolution remote sensing data can be viable for accurate and prompt spatio-temporal assessment of lodging severity. As such unmanned aerial vehicles (UAVs) provide a versatile and cost-effective solution to monitor crops on a small scale with sub-centimetre spatial resolution. In this study, we analysed the spectral variability between different grades of lodging severity (non-lodged (NL), moderate (ML), severe (SL) and very severe (VSL)) and classified them using high-resolution UAV data. Multispectral orthomosaic UAV images with 5cm resolution and nine bands (covering the VIS-NIR spectrum with Sentinel-2 filters) were acquired in May 2018 for two wheat fields in Bonifiche Ferraresi farm, Jolanda di Savoia, Italy. Concurrent to the time of image acquisition, a field campaign was carried out in which crop characteristics and lodging related parameters were collected. The results showed that reflectance magnitude increased with lodging severity and demonstrated that the red-edge and NIR bands can be used to clearly discriminate between NL and lodged (all grades) wheat and to some extent between different lodging classes (ML, SL and VSL). The nearest neighbourhood classification performed using an object-based segmentation yielded optimal results with an overall accuracy of 90%, thus demonstrating the use of multispectral UAV data as a promising tool for wheat lodging assessment.

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Chauhan S, Darvishzadeh R, Lu Y, Stroppiana D, Boschetti M, Pepe M et al. Wheat lodging assessment using multispectral uav data. In Vosselman G, Oude Elberink SJ, Yang MY, editors, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2/W13 ed. Vol. 42. Enschede: International Society for Photogrammetry and Remote Sensing. 2019. p. 235-240. (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives). https://doi.org/10.5194/isprs-archives-XLII-2-W13-235-2019