Comparison of Accuracy on Wetland Remote Sensing Classification between Independent Component Analysis and Principal Component Analysis Methods——A Case Study of Wetlands in Western Dongting LakeChinese Full Text

DONG Qi-liang;LIN Hui;SUN Hua;ZANG Zhuo;HU Jia;FAN Ying-long;Research Center of Forestry Remote Sensing ＆ Information Engineering,Central South University of Forestry and Technology;Research Institute of Forest Resources Information Techniques,Chinese Academy of Forestry;

Abstract: This study aimed at exploring method to improve the classification accuracy of high resolution remote sensing image,which could support the research on the wetlands in Dongting Lake area.The results showed the information of images processed by independent component analysis（ICA） and principal component analysis（PCA） methods had not been lost;after PCA and ICA processing,the sharpness of the images were deteriorated,but not enough to affect the visual interpretation of the typical wetland types;SPOT 5 image became clearer after PCA and ICA processing.ICA method could significantly improve the divisibility of the typical wetlands in Dongting Lake,but it still has shortages on classify marshes and paddy fields.For Landsat 5 TM image,compared to the original image,the overall accuracy increased by 11.83% after the image processed by ICA method,that was 5.35% higher than by PCA method.For SPOT 5 image,compared to the original image,the overall accuracy increased by 10.7% after the image processed by ICA method,that was 5.07% higher than by PCA method.Based on the higher-order statistics information,independent component analysis method could not only remove the correlation between the bands,but also obtain the independent component characteristics,enhancing separability between wetland types.It also could effectively remove the negative impact of the typical wetland classification,and improve the accuracy of wetland information extraction.

Keywords：

wetland information extraction; remote sensing classification; independent component analysis; Dongting Lake;

DOI：
10.13248/j.cnki.wetlandsci.2014.03.010
Series：
Subject：
Classification Code：
P237;X37

Mobile Reading

Read on your phone instantly

Step 1
Scan QR Codes

"Mobile CNKI-CNKI Express" App

Step 2
Open“CNKI Express”

and click the scan icon in the upper left corner of the homepage.

Step 3
Scan QR Codes

Read this article on your phone.
HTML
CAJ Download
PDF Download

Contents

Comparison of Accuracy on Wetland Remote Sensing Classification between Independent Component Analysis and Principal Component Analysis Methods——A Case Study of Wetlands in Western Dongting LakeChinese Full Text

DONG Qi-liang;LIN Hui;SUN Hua;ZANG Zhuo;HU Jia;FAN Ying-long;Research Center of Forestry Remote Sensing ＆ Information Engineering,Central South University of Forestry and Technology;Research Institute of Forest Resources Information Techniques,Chinese Academy of Forestry;

Read on your phone instantly

Citation Network

Related Literature