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

作　　者：Ying Bao Qingjiu Tian Min Chen Hui Lin 

机构地区：[1]International Institute for Earth System Science,Nanjing University,Nanjing,PR China [2]Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology,Nanjing University,Nanjing,PR China [3]Institute of Space and Earth Information Science,The Chinese University of Hong Kong,Shatin,Hong Kong,PR China [4]Shenzhen Research Institute,The Chinese University of Hong Kong,Shenzhen,PR China [5]Department of Geography and Resource Management,The Chinese University of Hong Kong,Shatin,Hong Kong,PR China

出　　处：《International Journal of Digital Earth》2015年第6期495-516,共22页国际数字地球学报（英文）

基　　金：This study was jointly supported by the National Science and Technology Major Project Grant No.[30-Y20A01-9003-12/13];the State Key Fundamental Science Funds Grant No.[2010CB951503];National Key Basic Research Program Project Grant No.[2010CB434801];National Key Technology R&D Program of China Grant No.[2012BAH32B03];National Natural Science Foundation of China Grant No.[41101439].

摘　　要：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 challenging.In 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 crowns.The 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 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]