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Journal of Applied Remote Sensing

Monitoring the distribution of C3 and C4 grasses in a temperate grassland in northern China using moderate resolution imaging spectroradiometer normalized difference vegetation index trajectories
Author(s): Linlin Guan; Liangyun Liu; Dailiang Peng; Yong Hu; Quanjun Jiao; Lingling Liu
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Paper Abstract

Using remote-sensing technologies, this study sought to provide an up-to-date map of C3/C4 distribution representative of temperate grassland in northern China. Several studies focused on the central grasslands of North America have demonstrated that C4 species coverage can be discriminated from C3 species by using time-series vegetation index data based on their phenological differences. Considering that the hydrothermal patterns and C4 percentage of grass flora in the study area and North America are different, we first examined temporal features of C3/C4 communities by using multitemporal moderate resolution imaging spectroradiometer normalized difference vegetation index data throughout the 2010 growing season. It was found that the asynchronous seasonality exhibited by communities with varied C3/C4 compositions also existed in our study region. Based on this asynchrony and separation rate, a hierarchical decision tree was developed to classify four grassland types with varied C3/C4 compositions. As a result, a classification map of the mixed C3/C4 grassland was generated with an overall accuracy of 87.3% and a kappa coefficient of 0.83. The geographic distribution of C3 and C4 species showed that the study area was dominated by C3 grasses, but C4-dominated grasslands accounted for 39% of the land cover. Thus C4 species also made an important contribution to grassland biomass, especially in dry and low-lying saline-alkaline habitats. The results also indicated that the trajectory-based methods for C3/C4 mapping rooted in asynchronous seasonality worked effectively in the climate regimes of both northern China and North America.

Paper Details

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J. Appl. Remote Sens. 6(1) doi: 10.1117/1.JRS.6.063535
Published in: Journal of Applied Remote Sensing Volume 6, Issue 1, January 2012
Show Author Affiliations
Linlin Guan, Institute of Remote Sensing and Digital Earth (China)
Liangyun Liu, Institute of Remote Sensing and Digital Earth (China)
Dailiang Peng, Institute of Remote Sensing and Digital Earth (China)
Yong Hu, Institute of Remote Sensing and Digital Earth (China)
Quanjun Jiao, Institute of Remote Sensing and Digital Earth (China)
Lingling Liu, Institute of Remote Sensing and Digital Earth (China)


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