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Cotton growth modeling using unmanned aerial vehicle vegetation indices | IEEE Conference Publication | IEEE Xplore

Cotton growth modeling using unmanned aerial vehicle vegetation indices


Abstract:

Unmanned aerial vehicle (UAV) images have great potential for agricultural researches because of their high spatial and temporal resolutions. However, most UAV researches...Show More

Abstract:

Unmanned aerial vehicle (UAV) images have great potential for agricultural researches because of their high spatial and temporal resolutions. However, most UAV researches in the agriculture field have adopted vegetation indices without second derivative parameters related with a growth model. In addition, visible band vegetation indices in UAV researches have not been explored in detail despite of their importance in UAV application. In this study, three RGB vegetation indices that showed good performance in previous studies are adopted and growth modeling using time series vegetation indices is proposed. In addition, growth model-based second derivatives are extracted for crop growth analysis. R squares of the proposed method from three RGB vegetation indices were 0.8–0.9 and excessive green vegetation index (ExG) showed the best accuracy.
Date of Conference: 23-28 July 2017
Date Added to IEEE Xplore: 04 December 2017
ISBN Information:
Electronic ISSN: 2153-7003
Conference Location: Fort Worth, TX, USA

References

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