土地利用/土地覆被决策树分类方法研究——以河北省树县为例

Ping Wang, Jixian Zhang, Weidong Jia, Zongjian Lin
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引用次数: 3

摘要

采用决策树技术,利用其模仿人类判断和思维的过程模式和容错特性,提出了一种决策树分类方法。初步利用SPOT和TM,有效增强了LULC信息,建立了综合数据库;然后,利用CART系统,将地学综合分析与地面光谱特征信息相结合;建立了基于决策规则的决策树模型。最后,讨论了LULC决策树分类分层提取技术的广泛应用。以河北省三县为例,通过生态区划对研究区域进行划分,对各单元(县域)进行分类,利用多数据资源和地学规则构建决策树模型,并对方法进行验证。结果表明,该方法提高了分类的速度和精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A study on decision tree classification method of land use/land cover -Taking tree counties in Hebei Province as an example
Adopting the decision tree technology, utilizing its process pattern that imitates human judgment and thinking and fault-tolerance features, the authors developed a decision tree classification method. Initially utilizing SPOT and TM, the work effectively enhanced LULC information and established the synthetic database; then, combining geoscience synthetic analysis with ground spectral feature information, utilizing the CART system; the authors built the decision tree model that is based on the decision rules. At last, we discussed the wild use of LULC decision tree classified and stratified extractive technology. Taking three counties in Hebei province as examples, we divided the research area to classify each unit (county area) by ecological division, utilized multiple data resources and geoscience rules to build the decision tree model and test and verify the method. The results demonstrated that the method improves the speed and precision of classification.
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