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Estimating leaf area index of black locust (Robinia pseudoacacia L.) plantations based on texture parameters of Quickbird imagery.

ZHOU Jing-jing, ZHAO Zhong, LIU Jin-liang, ZHAO Qing-xia, ZHAO Jun   

  1. (Ministry of Education Key Laboratory of Environment and Ecology in Western China, College of Forestry, Northwest A&F University, Yangling 712100, Shaanxi, China)
  • Online:2014-05-18 Published:2014-05-18

Abstract: The black locust plantations located in Weibei area were chosen as research objects and the texture parameters of different window sizes from high resolution imagery were measured. Four different techniques, including simple linear regression model, quadratic regression model, power model and exponential model, were developed to describe the relationship between the texture parameters and field measurements of LAI and to select the most effective texture parameters and window size. The results showed that the texture parameters influenced the accuracy of LAI estimation. Angular second moment and entropy index yielded better adjust r2 than the other parameters. The r2 changed with the window size. Dissimilarity and contrast index gained the largest r2 when the window size was 9×9. The r2 of the other texture parameters reduced as the window size increased and a window size of 3×3 was more successful than any of the others. Power equation performed poorest than the other three techniques for estimation of LAI.