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基于神经网络的区域生态环境分类方法研究
引用本文:乔平林,张继贤,卢秀山,高武俊,张运生.基于神经网络的区域生态环境分类方法研究[J].地理与地理信息科学,2004,20(2):97-99.
作者姓名:乔平林  张继贤  卢秀山  高武俊  张运生
作者单位:1. 山东科技大学地球信息科学学院,山东,泰安,271019;中国测绘科学研究院,北京,100039
2. 中国测绘科学研究院,北京,100039
3. 山东科技大学地球信息科学学院,山东,泰安,271019
基金项目:国家科技部重点项目(2001DIA1005)
摘    要:如何利用智能化信息提取技术,进行区域生态环境自动分类,一直是一种前沿性研究。该文在分析研究区自然景观特征的基础上,总结了影响区域生态环境的建模要素,基于神经网络技术,并根据生态环境的遥感探测机理,利用TM卫星遥感数据中的可见光、热红外、植被指数(NDVI)以及DEM数据,建立了基于BP神经网络的区域生态环境信息自动提取模型,形成了一种新的生态环境分类方法,其分类结果与实际情况完全一致。

关 键 词:生态环境分类  NDVI  人工神经网络  BP模型  TM影像
文章编号:1672-0504(2004)02-0097-03
修稿时间:2003年7月31日

An Artificially Neural Network Method for Regionally Ecological Classification
QIAO Ping-lin.An Artificially Neural Network Method for Regionally Ecological Classification[J].Geography and Geo-Information Science,2004,20(2):97-99.
Authors:QIAO Ping-lin
Institution:QIAO Ping-lin~
Abstract:The ecological classification is important for the environment problem study around the world today.The generation ,development and reversion of desertification are caused by the comprehensive influences from the climatic and environmental changes,and human activities.Extracting the information of ecological classification is one of the key steps in ecological classification research.In this paper, an artificially neural network(ANN) method for extracting the information of ecologically classification with TM image has been developed,which is based on the ground humidity,NDVI,and hypsography(DEM).The method has been applied to extract the information of ecological classification in the valley of Shiyang River in 2001.The results have illustrated a good performance,and it has shown great potential in this field.
Keywords:ecological classification  normalized difference vegetation index  artificially neural network(ANN)  BP model  TM image
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