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遥感技术与应用  2008, Vol. 23 Issue (3): 294-299    DOI: 10.11873/j.issn.1004-0323.2008.3.294
研究与应用     
基于特征波段的SPOT-5卫星影像水稻面积信息自动提取的方法研究
郑长春1,3,王秀珍1,2,黄敬峰3
(1.新疆农业大学资源环境学院,新疆 乌鲁木齐 830052;2.浙江省气象科学研究所,浙江 杭州 310004;3.浙江大学农业遥感与信息技术应用研究所,浙江 杭州 310029)
Decision Tree Algorithm of Automatically Extracting Paddy Rice Information 5from SPOT-5 Images Based on Characteristic Bands
ZHENG Chang-chun1,3,WANG Xiu-zhen1,2,HUANG Jing-feng 3
 (1.College of Resource and Environment,Xinjiang Agricultural University,Urumqi 830052|China;2.Zhejiang Meteorological Institute of Science|Hangzhou 310004|China;3.Zhejiang University Agricultural Remote Sensing and Information Technology Application Institute,Hangzhou 310029,China)
 全文: PDF(1314 KB)  
摘要:

为了快速、准确地从遥感影像上提取水稻信息,满足国家农情遥感监测系统要求,以黑龙江省852农场水稻提取为例,利用SPOT-5卫星影像数据,分析了水稻和其它背景地物的光谱特征,发现利用原有波段难以提取复杂的水稻信息,因此利用植被特征波段:归一化植被指数(NDVI)作为新波段融入原始影像中,在增加有效信息量的同时运用简单决策树模型提取水稻信息,并参照地块现状矢量图进行精度评价。结果表明,该方法的总体提取效果较好,其提取精度与通常的监督分类方法相比有了较大的提高,只是在水稻和玉米交界处有误判现象。

关键词: 水稻光谱分析信息提取决策树    
Abstract:

For meeting the demand for large-scale agricultural monitoring system with remote sensing technology,extracting paddy rice information on the remote sensing image must be rapidly,precisely and reliable conducted.In this paper,paddy rice identification with SPOT-5 image was taken as an example on the 852 farm in Heilongjiang province of China.Firstly,the spectral characteristics of paddy rice and other six land-use types in this area were analyzed to find the possibility of extracting of paddy rice from the background.The results show it is difficult to distinguish paddy rice information from background on the SPOT-5 images because of complexity of spectrum and lack of band information.Secondly,taking those into account,characteristic bands for paddy rice extraction were proposed and merged into SPOT-5 images in order to increase spectral information and improve the separability.Thirdly,a simple model of decision tree was applied to extract paddy rice information.Finally,the results were checked by visual and statistica1 accuracy assessment.The results suggest that the model based on characteristic bands is simple and effective,and the accuracy by the model is much higher than that by the supervised classification method.However,some pixels in the neighborhood area between paddy rice and corn were misjudged.

Key words:  Paddy rice    Spectral analysis    Information extraction    Decision tree
收稿日期: 2008-02-21 出版日期: 2011-10-25
:  TP 79  
基金资助:

国家“863”资助项目(2006AA120101);国家自然科学基金项目(40571115);国家科技支撑项目(2006BAD10A01);浙江省科技计划项目(2007C22028)。

通讯作者: 王秀珍(1963-):女,研究员,主要从事农业遥感与信息技术应用研究。E-mail:wxz0516@sina.com。     E-mail: xjzcc@126.com。
作者简介: 郑长春(1981-):男,硕士研究生,主要从事遥感作物估产研究。E-mail:xjzcc@126.com。
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引用本文:

郑长春,王秀珍,黄敬峰. 基于特征波段的SPOT-5卫星影像水稻面积信息自动提取的方法研究[J]. 遥感技术与应用, 2008, 23(3): 294-299.

ZHENG Chang-chun,WANG Xiu-zhen,HUANG Jing-feng. Decision Tree Algorithm of Automatically Extracting Paddy Rice Information 5from SPOT-5 Images Based on Characteristic Bands. Remote Sensing Technology and Application, 2008, 23(3): 294-299.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2008.3.294        http://www.rsta.ac.cn/CN/Y2008/V23/I3/294

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