| The Remote Sensing image has become a new source of information for forest resources survey not only because it can provide plenty of information of spectrum and spatial location of features but also because it has many advantages, such as macro, convenient, the cycle repeated, dynamic survey and low-cost and so on.Using the technology of RS along with GIS and GPS has become an inevitable trend.In this paper, the writer chose the QuickBird image of Dr. Sun yat-sen's Mausoleum 2006, the data of forest management inventory of Dr. Sun yat-sen's Mausoleum 2002 and the relief map of 1:10000 of Dr. Sun yat-sen's Mausoleum 1999 as the information source, chose the technology of RS and GIS as the main technical methods, studied the forest resources classification of Dr. Sun yat-sen's Mausoleum.The main contents and conclusions were summarized as follows through the research:(1) Classifying the QuickBird image of the research region in level 1 by Maximum Likelihood Classifier, there was a better result of the distinction between the forest and water, farmland ,other. The result was used for the statistics of the area of the four types of land in Dr. Sun yat-sen's Mausoleum and its six scenic spots.(2) Classifying the QuickBird image of the research region in level 2. The research showed that Support Vector Machine could has a better classification results and the results were used for the statistics of the area of broadleaf, conifer, con_broad, bamboo, nursery, water, farmland and other. But broadleaf and con_broad were mixed in some degree, so the area of the broadleaf was smaller than its real area and the area of the con_broad was bigger than its real area.(3) Calculated the biomass and productivity of Quercus,Pinus massoniana,Robinia pseudoacacia with the data of forest management inventory,2002, Dr. Sun yat-sen's Mausoleum. The research showed that the average productivity of Robinia pseudoacacia was the biggest among the three trees species. |
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