The comparison of several colour indices for the photographic recording of canopy phenology of Fagus crenata Blume in eastern Japan

Abstract

Background: To understand how forests and woodland respond to global climate change, phenological observations are being made at a number of sites worldwide. Recently, digital cameras have been deployed as part of the existing network of ecosystem CO₂ flux towers to provide a time-series of canopy images, and various numerical indices have so far been used by different authors.

Aims: To identify which are the most effective colour indices to calculate from the signals extracted from digital cameras, in order to provide recommendations to the scientific community.

Methods: Sample images of a Japanese beech (Fagus crenata) forest on Mt. Tsukuba (Japan) were used to define and calculate 12 colour signals and vegetation indices.

Results: Although the strength of green signal and green excess index were reliable indicators for estimating foliage growth period, the indices were susceptible to low-visibility weather conditions and distance from the camera. Hue provided a robust metric, showing much less scatter during the vegetative period and a good indication of spring bud break. The bud break dates derived from the indices were slightly earlier than those assessed by visual observation, while the abscission dates were later.

Conclusions: We propose that of all the candidate colour indices, hue is the most promising for the detection of bud break as it was least affected by atmospheric conditions.

Keywords:

• canopy phenology
• deciduous broadleaved forest
• digital image
• HSL
• RGB

Acknowledgements

This work was supported by the UK–Japan 2008 Collaborative Project Grant Award of the British Embassy, Tokyo and the British Council to commemorate the 150th anniversary of official diplomatic relations between Japan and the UK, and KAKENHI (19688012; Grant-in-Aid for Young Scientists (A)) of the Japan Society for the Promotion of Science. Salary for TM was made available through a Jim Gray Seed Trust awarded to LW by Microsoft Research. LW was supported by the Natural Environment Research Council Advanced Fellowship award NE/G014418/1. Yousei Hayashi is thanked for the meteorological data collected at Mt. Tsukuba. We thank Andrew Richardson and his team for allowing us to use their MATLAB code. We are indebted to the Phenological Eyes Network (PEN) for their support with the camera systems.