Forest Classification Based on Forest texture in Northwest Yunnan Province

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Wang, Jinliang^1 ; Gao, Yan^1 ; Wang, Xiaohua^2 ; Fu, Lei^1

College of Tourism and Geographical Science, Yunnan Normal University, Chenggong, Kunming, 650500, China^1

Urban Planning Bureau of Liangping County, Chongqing Municipality, Liangping 405200, China^2

关键词: Co-occurrence-matrix;    Ecological systems;    Forest classification;    Intrinsic characteristics;    Remote sensed data;    Texture information;    Visual interpretation;    Wavelet transformations;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012071/pdf
DOI  :  10.1088/1755-1315/17/1/012071

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Forest texture is an intrinsic characteristic and an important visual feature of a forest ecological system. Full utilization of forest texture will be a great help in increasing the accuracy of forest classification based on remote sensed data. Taking Shangri-La as a study area, forest classification has been based on the texture. The results show that: (1) From the texture abundance, texture boundary, entropy as well as visual interpretation, the combination of Grayscale-gradient co-occurrence matrix and wavelet transformation is much better than either one of both ways of forest texture information extraction; (2) During the forest texture information extraction, the size of the texture-suitable window determined by the semi-variogram method depends on the forest type (evergreen broadleaf forest is 3×3, deciduous broadleaf forest is 5×5, etc.). (3)While classifying forest based on forest texture information, the texture factor assembly differs among forests: Variance Heterogeneity and Correlation should be selected when the window is between 3×3 and 5×5; Mean, Correlation, and Entropy should be used when the window in the range of 7×7 to 19×19; and Correlation, Second Moment, and Variance should be used when the range is larger than 21×21.