应用面向对象的决策树模型提取橡胶林信息  

Extracting rubber plantation with decision tree model based on object-oriented method

作　　者：梁守真[1] 陈劲松[2] 吴炳方[3] 陈工[2] 

机构地区：[1]山东省农业科学院可持续发展研究所,山东济南25010 [2]中国科学院深圳先进技术研究院,深圳518055 [3]中国科学院遥感与数字地球研究所,北京100101

出　　处：《遥感学报》2015年第3期485-494,共10页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家自然科学基金(编号:41401407);中国科学院战略性先导科技专项(编号:XDA05050107);山东省农业重大应用技术创新课题(编号:1-0402);山东省农业科学院科技创新重点项目(编号:2014CXZ09-2)

摘　　要：橡胶林的无序和不合理种植引发了一系列的生态问题,快速监测橡胶林空间分布及动态变化,对橡胶的合理种植、区域生态环境保护以及有关部门的规划决策有重要的指导意义。以MODIS归一化植被指数NDVI时间序列数据和多时相的Landsat TM数据为基础分析橡胶林的季相和光谱特征,确定橡胶识别的关键时期和特征参数,构建面向对象的决策树分类模型,开展橡胶信息提取研究。结果表明,多时相的遥感数据可反映橡胶的季相特征,以TM数据为基础计算得到的陆表水分指数LSWI和归一化植被指数NDVI可作为橡胶识别的光谱特征参数,橡胶休眠期是利用遥感方法进行橡胶提取的最佳时期。相比于单时相数据,利用包含橡胶关键物候期的多时相遥感数据能得到更高的橡胶林提取精度。Rubber plantations are expanding rapidly in the tropical region of China because of their high profitability,while large areas of natural rainforests are deforested and replaced by artificial rubber trees. A series of ecological problems has occurred because of unreasonable and disordered plantation of rubber trees in some areas. Acquiring spatial distribution of rubber plantations rapidly and monitoring their dynamics can contribute to control and manage rubber plantations and to protect the local ecological environment. Remote sensing plays an important role in monitoring the dynamics of land use and cover. However,the high complexity of tropical ecosystems makes it difficult to extract information from a single-temporal image. This study aims to develop a method that extracts information about rubber plantations effectively and to improve classification accuracy of a tropical ecosystem with multi-temporal remote sensing images. Based on Moderate Resolution Imaging Spectroradiometer（ MODIS） Normalized Difference Vegetation Index（ NDVI） time series data and multi-temporal Landsat TM data,the seasonal characteristics and spectral characteristics of different objects,including rubber plantation,broadleaved evergreen forest,dry land,and paddy field in the study area,are analyzed and compared in this study. A decision tree model that integrates object-oriented technology is developed to extract rubber plantation in Hainan province. The model choose appropriate characteristic parameters and remote sensing data to separate rubber plantation and other land cover types. Rubber plantation demonstrates obvious seasonal characteristics according to time series data. During the dormant period of rubber trees,an obvious difference in spectral characteristics among different land covers is observed. NDVI and Land Surface Water Index（ LSWI） can be selected as the two main parameters to distinguish rubber plantation and other land covers in the study area. In addition,remote sensing data in winter are optimal for ex

关 键 词：橡胶 多时相影像 决策树 面向对象 陆表水分指数LSWI 归一化植被指数NDVI 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]