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An automatic extraction method for individual tree crowns based on self-adaptive mutual information and tile computing

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International Journal of Digital Earth 2015年第6期8卷 495-516页

作者： Ying Bao Qingjiu Tian Min Chen Hui Lin International Institute for Earth System Science Nanjing UniversityNanjingPR China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Nanjing UniversityNanjingPR China Institute of Space and Earth Information Science The Chinese University of Hong KongShatinHong KongPR China Shenzhen Research Institute The Chinese University of Hong KongShenzhenPR China Department of Geography and Resource Management The Chinese University of Hong KongShatinHong KongPR China

Forest data acquisition,which is of crucial importance for modeling global biogeochemical cycles and climate,makes a contribution to building the ecological Digital Earth(DE).Due to the complex calculations and large volumes of data associated with high-resolution images of large areas,accurate and effective extraction of individual tree crowns remains *** this study,two GeoEye-1 panchromatic images of Beihai and Ningbo in China with areas of 5 and 25 km2,respectively,were used as experimental data to establish a novel method for the automatic extraction of individual tree crowns based on a self-adaptive mutual information(SMI)algorithm and tile computing technology(SMI-TCT).To evaluate the performance of the algorithm,four commonly used algorithms were also applied to extract the individual tree *** overall accuracy of the proposed method for the two experimental areas was superior to that of the four other algorithms,with maximum extraction accuracies of 85.7%and 63.8%.Moreover,the results also indicated that the novel method was suitable for individual tree crowns extraction in sizeable areas because of the multithread parallel computing technology.

关键词： individual tree crowns GeoEye-1 automatic extraction tile computing mutual information

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