Chin J Plant Ecol ›› 2012, Vol. 36 ›› Issue (11): 1125-1135.DOI: 10.3724/SP.J.1258.2012.01125

Special Issue: 青藏高原植物生态学:遥感生态学

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Simulations of phenology in alpine grassland communities in Damxung, Xizang, based on digital camera images

ZHOU Lei1,2, HE Hong-Lin1,*(), ZHANG Li1, SUN Xiao-Min1, SHI Pei-Li1, REN Xiao-Li1,2, YU Gui-Rui1   

  1. 1Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    2University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2012-08-08 Revised:2012-09-22 Online:2012-08-08 Published:2012-11-09
  • Contact: HE Hong-Lin

Abstract:

Aims Phenology refers to periodic appearances of life-cycle events. It is crucial for predicting plant phenological responses to climate change and for identifying the period of carbon-uptake. Tracking the real-time canopy status accurately, especially in harsh environments, is becoming a large challenge for understanding and modeling vegetation-climate interactions. Our objective focuses on how to obtain relatively accurate real-time canopy status in Qinghai-Xizang Plateau using digital camera images.
Methods A standard, commercially available webcam was mounted at the top of the eddy covariance tower at the Damxung Rangeland Station. Images were collected every half an hour from 9:30 a.m. to 5:00 p.m. local time each day. We extracted red, green, and blue color channel brightness data for a region-of-interest (ROI) from each image (ROI, the subset of image, can better describe the target’s characters). The size of ROI is [100:180] and [10:380]), and it composed the different greenness indices according to the equations. We confirmed the best one that can reflect the size of leaf area index and variations in chlorophyll content by comparing different indices.
Important findings The absolute greenness index (2G_RB) is able to describe the canopy status qualitatively and quantitatively and is powerful in tracking community phenological stages. This indicates that digital cameras can be used in monitoring real-time phenology of alpine grassland community. Linear regression analysis of soil moisture indicates greenness is best explained by surface soil moisture (≤10 cm). By comparing canopy phenological events with conventional meteorological data, we also speculate that precipitation plays a critical role in triggering the spring phenological response in semiarid alpine grassland.

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Key words: absolute greenness index, alpine grassland community, digital camera, phenological phase