Tag Archives: winter rape

xxx Z. Jelínek, K. Starý, J. Kumhálová, J. Lukáš and J. Mašek
Winter wheat, winter rape and poppy crop growth evaluation with the help of remote and proximal sensing measurements
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Winter wheat, winter rape and poppy crop growth evaluation with the help of remote and proximal sensing measurements

Z. Jelínek¹*, K. Starý¹, J. Kumhálová¹, J. Lukáš² and J. Mašek³

¹Czech University of Life Sciences Prague, Faculty of Engineering, Department of Machinery Utilization, Kamýcká 129, CZ165 00 Prague, Czech Republic
²Crop Research Institute, v.v.i., Drnovská 507, CZ161 00 Prague, Czech Republic
³Czech University of Life Sciences, Faculty of Engineering, Department of Agricultural Machines, Kamýcká 129, CZ165 00 Prague, Czech Republic
*Correspondence: jelinekzdenek@tf.czu.cz

Abstract:

Monitoring of agricultural crops with the help of remote and proximal sensors during the growing season plays important role for site-specific management decisions. Winter wheat, winter rape and poppy are representatives of typical agricultural crops from the family Poacea, Brassicaceae and Papaveraceae, growing in relative dry area of Rakovník district in the Czech Republic. Ten Sentinel 2 satellite images acquired during vegetation season of the crops were downloaded and processed. Crops were monitored with the help of unmanned aerial vehicles (UAV) equipped with consumer grade Red Green Blue (RGB) camera and multispectral (MS) MicaSense RedEdge MX camera. In-field variability was assessed by computing RGB-based vegetation indices Triangular Greenness Index (TGI), Green Leaf Index (GLI) and Visible Atmospherically Resistant Index (VARI) and commonly used vegetation indices as Normalised Difference Vegetation Index (NDVI) and Green NDVI (GNDVI). The results derived from satellite and UAV images were supported with in-situ measurements of hand-held GreenSeeker and Chlorophyll Meter Content sensors. The study showed the usability of individual vegetation indices, especially the TGI index for chlorophyll content estimation, and VARI index for green vegetation fraction detection and leaf area index estimation, in comparison with selected hand-held devices. The results showed as well that leaf properties and canopy structure of typical characteristics of selected families can significantly influence the spectral response of the crops detected in different phenological stages.

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