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Master thesis

Linking digital image signals to the seasonal variations in photosynthetic pigments of different plant types

Abstract : Plant phenology is a sensitive indicator of climate change and influences soil-plant-atmosphere interactions at local and global scales. In recent years, phenology monitoring based on camera images taken over the growing season has become a popular tool. However, relationships between digital camera phenological records and leaf biochemical and spectral properties are poorly understood. In this study, measurements of key leaf biochemical properties such as photosynthetic pigment and nitrogen contents were made on a weekly basis over the spring and summer of 2015 on various Landes of Gascogne species (Pinus pinaster, Eucalyptus gundal, various vine varieties and grassland species) in Bordeaux, France. The size and spectral leaf properties were measured using a flatbed scanner (Canon LIDE 110, CANON, France) to extract colour indices (Green, Red, Blue and Green Excess indices). At the same time, digital cameras (Stardot SC5 IR, Stardot, California, USA) were installed in the field to automatically record daily pictures of the studied ecosystems and extract the same colour indices. The technique typically used for chlorophyll extraction in laboratory is laborious thus a portable chlorophyll meter was used to collect a larger dataset (Dualex Scientific +, Force A, Orsay). The aim of the study was to compare seasonal trajectories between leaf biochemical content and colour indices of the canopies. Our results show that phenological seasonal evolutions are well captured by information extracted from digital repeat photography. The digital images from camera and scanner have important implications for phonological research application and for assessing responses of vegetation to disturbances (climate change, frost, drought).
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Master thesis
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Submitted on : Tuesday, July 3, 2018 - 2:18:56 PM
Last modification on : Saturday, April 30, 2022 - 4:03:11 PM
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  • HAL Id : hal-01828807, version 1



Juliette Maire. Linking digital image signals to the seasonal variations in photosynthetic pigments of different plant types. Sciences de l'environnement. 2015. ⟨hal-01828807⟩



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