The Effects of GLCM parameters on LAI estimation using texture values from Quickbird Satellite Imagery.
Jingjing Zhou, Rui Yan Guo, Mengtian Sun, Tajiguli Tu Di, Shan Wang, Jiangyuan Zhai, Zhong Zhao
Author Information
Jingjing Zhou: College of Horticulture & Forestry Sciences/Hubei Engineering Technology Research Center for Forestry Information, Huazhong Agriculture University, Wuhan, Hubei, 430070, P.R. China.
Rui Yan Guo: College of Horticulture & Forestry Sciences/Hubei Engineering Technology Research Center for Forestry Information, Huazhong Agriculture University, Wuhan, Hubei, 430070, P.R. China.
Mengtian Sun: College of Horticulture & Forestry Sciences/Hubei Engineering Technology Research Center for Forestry Information, Huazhong Agriculture University, Wuhan, Hubei, 430070, P.R. China.
Tajiguli Tu Di: College of Horticulture & Forestry Sciences/Hubei Engineering Technology Research Center for Forestry Information, Huazhong Agriculture University, Wuhan, Hubei, 430070, P.R. China.
Shan Wang: College of Horticulture & Forestry Sciences/Hubei Engineering Technology Research Center for Forestry Information, Huazhong Agriculture University, Wuhan, Hubei, 430070, P.R. China.
Jiangyuan Zhai: College of Horticulture & Forestry Sciences/Hubei Engineering Technology Research Center for Forestry Information, Huazhong Agriculture University, Wuhan, Hubei, 430070, P.R. China.
Zhong Zhao: College of Forestry/Shaanxi comprehensive key laboratory of forestry, Northwest A&F University, Yangling, Shaanxi, 712100, P.R. China. zhaozh@nwsuaf.edu.cn.
When the leaf area index (LAI) of a forest reaches 3, the problem of spectrum saturation becomes the main limitation to improving the accuracy of the LAI estimate. A sensitivity analysis of the Grey Level Co-occurrence Matrix (GLCM) parameters which can be applied to satellite image processing and analysis showed that the most important parameters included orientation, displacement and moving window size. We calculated the values of Angular Second Moment (ASM), Entropy (ENT), Correlation (COR), Contrast (CON), Dissimilarity (DIS) and Homogeneity (HOM) from Quickbird panchromatic imagery using a GLCM method. Four orientations, seven displacements and seven window sizes were considered. An orientation of 90° was best for estimating the LAI of black locust forest, regardless of moving window size, displacement and texture parameters. Displacements of 3 pixels appeared to be best. The orientation and window size had only a little influence on these settings. The highest adjusted r values were obtained using a 3 × 3 moving window size for ASM and ENT. The tendency of CON, COR, DIS and HOM to vary with window size was significantly affected by orientation. This study can help with parameter selection when texture features from high resolution imagery are used to estimate broad-leaved forest structure information.
