Decision Tree Algorithm of Automatically Extracting Paddy Rice Information 5from SPOT-5 Images Based on Characteristic Bands

doi:10.11873/j.issn.1004-0323.2008.3.294

Remote Sensing Technology and Application

2008, Vol. 23

Issue (3): 294-299 DOI: 10.11873/j.issn.1004-0323.2008.3.294

article

Decision Tree Algorithm of Automatically Extracting Paddy Rice Information 5from SPOT-5 Images Based on Characteristic Bands

ZHENG Chang-chun^1,3,WANG Xiu-zhen^1,2,HUANG Jing-feng³

(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)

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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

Received: 21 February 2008 Published: 25 October 2011

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Cite this article:

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.

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

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