TR32-Database: Database of Transregio 32

Data Description of DOI 10.5880/TR32DB.KGA94.3

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Citation:Calderon, Rocio; Navas Cortes, Juan A.; Lucena, Juan C.; Zarco-Tejada, Pablo J. (2014): High-resolution hyperspectral and thermal imagery acquired from UAV platforms for early detection of Verticillium wilt using fluorescence, temperature and narrow-band indices. Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten. DOI: 10.5880/TR32DB.KGA94.3
Title(s):Main Title: High-resolution hyperspectral and thermal imagery acquired from UAV platforms for early detection of Verticillium wilt using fluorescence, temperature and narrow-band indices
Description(s):Abstract: Verticillium wilt (VW) caused by the soil-borne fungus Verticillium dahliae Kleb, is the most limiting disease in all traditional olive-growing regions worldwide. This pathogen colonizes the vascular system of plants, blocking water flow and eventually inducing water stress. The present study explored the use of high-resolution thermal imagery, chlorophyll fluorescence, structural and physiological indices (xanthophyll, chlorophyll a+b, carotenoids and B/G/R indices) calculated from multispectral and hyperspectral imagery as early indicators of water stress caused by VW infection and severity. The study was conducted in two olive orchards naturally infected with V. dahliae. Time series of airborne thermal, multispectral and hyperspectral imagery were conducted with 2-m and 5-m wingspan electric Unmanned Aerial Vehicles (UAVs) in three consecutive years and related to VW severity at the time of the flights. Concurrently to the airborne campaigns, field measurements conducted at leaf and tree crown levels showed a significant increase in crown temperature (Tc) minus air temperature (Ta) and a decrease in leaf stomatal conductance (G) across VW severity levels, identifying VW-infected trees at early stages of the disease. At leaf level, the reduction in G caused by VW infection was associated with a significant increase in the Photochemical Reflectance Index (PRI570) and a decrease in chlorophyll fluorescence. The airborne flights enabled the early detection of VW by using canopy-level image-derived airborne Tc-Ta, Crop Water Stress Index (CWSI) calculated from the thermal imagery, blue / green / red ratios (B/BG/BR indices) and chlorophyll fluorescence, confirming the results obtained in the field. Airborne Tc-Ta showed rising temperatures with a significant increase of ~2K at low VW severity levels. Early stages of disease development could be differentiated based on CWSI increase as VW developed, obtaining a strong correlation with G (R2=0.83, P<0.001). Likewise, the canopy-level chlorophyll fluorescence dropped at high VW severity levels, showing a significant increase as disease progressed at early VW severity levels. These results demonstrate the viability of early detection of V. dahliae infection and discrimination of VW severity levels using remote sensing. Indicators based on crown temperature, CWSI, and visible ratios B/BG/BR as well as fluorescence were effective in detecting VW at early stages of disease development. In affected plants, the structural indices, PRI, chlorophyll and carotenoid indices, and the R/G ratio were good indicators to assess the damage caused by the disease.
Contributor(s):Editor: Bendig, Juliane, University of Cologne
Editor: Bareth, Georg, University of Cologne
Data Manager: Transregional Collaborative Research Centre 32, Meteorological Institute, University of Bonn
Hosting Institution: University of Cologne, Regional Computing Centre (RRZK)
Subject(s):CRC/TR32 Keywords: Hyperspectral, Chlorophyll Fluorescence, High Resolution, UAV, Vegetation Index
DDC: 550 Earth sciences
Date(s):Issued: 2014-04-14
Resource Type:Text/Workshop paper
Size(s):8 Pages
821 Kilobytes
Licence:Creative Commons Attribution 4.0 International (CC BY 4.0)
Contact:Constanze Curdt

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