%0 Journal Article
%T Rubber Plantations in Xishuangbanna: Remote Sensing Identification and Digital Mapping<br>西双版纳橡胶林地的遥感识别与数字制图
%A LIU Xiaon
%A FENG Zhiming
%A JIANG Luguang
%A ZHANG Jinghua
%A <br>刘晓娜
%A 封志明
%A 姜鲁光
%A 张景华
%J 资源科学
%D 2012
%I 
%X Rubber plantations are the dominant artificial landscape across Xishuangbanna. Extraction and dynamic monitoring of rubber plantations is important to the region’s economic development and ecological protection. Based on MODIS-NDVI data we analyzed phenological characteristics of vegetation cover type and determined the temporal window for rubber forest detection. According to spectral differences between rubber forests at different growth stages we used object-oriented classification to discriminate spatial patterns with TM imagery. We found that the optimum temporal window for rubber detection was from January to February or from early June to late October. Using times series NDVI analysis we found that mature rubber forest has obvious differences compared with other land cover types and that young forest rubber was often confused with fallow farmland and tea garden. The NDVI characteristic of rubber forests is not the sole classification feature. Based on GPS and visual sampling total classification accuracy was 85.20%, about 5.20% higher than the decision tree method based on pixel classification. The accuracy of young rubber forest (<10 years old) was 92.50% and mature rubber forest (10 years old) was 76.42%, a ratio of 1.04∶]1. Remote sensing results were very close to the real condition, namely the area of private rubber plantation more than state-owned plantation. We propose a new method for the validation and improvement of rubber classification accuracy. Change analysis showed that the extraction method of mature rubber forest was more credible than for young rubber forest; mature rubber forest seldom transformed into other land use types. Rubber forest extraction and dynamic monitoring is important for rubber yield estimation, spatial distribution, environmental protection and local government decision-making. This is an effective method for monitoring rubber plantations dynamically and can be extended to other perennial vegetation extraction.
%K Remote sensing identification
%K Digital mapping
%K Young rubber forest
%K Mature rubber forest
%K MODIS-NDVI
%K Xishuangbanna<br>遥感识别
%K 数字制图
%K 橡胶幼林
%K 橡胶成林
%K MODIS—NDVI
%K 西双版纳
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=B5EDD921F3D863E289B22F36E70174A7007B5F5E43D63598017D41BB67247657&cid=B47B31F6349F979B&jid=9DEEAF23637E6E9539AD99BE6ABAB2B3&aid=F08440544A663446CA205EF30C0626AE&yid=99E9153A83D4CB11&vid=339D79302DF62549&iid=9CF7A0430CBB2DFD&sid=DF28BAAD0FD19027&eid=0420ACD7465FFFB2&journal_id=1007-7588&journal_name=资源科学&referenced_num=0&reference_num=42