Mapping double-cropped irrigated rice fields in Taiwan using time-series Satellite Pour I'Observation de la Terre data

Chen, Chi-Farn; Huang, Su-Wei; Son, Nguyen-Thanh; Chang, Li-Yu

doi:doi:10.1117/1.3595276

GENERAL INFORMATION

You are not logged in Logged Out Log In

Journal of Applied Remote Sensing / Volume 5 / Research Papers

Previous Article | Next Article

Mapping double-cropped irrigated rice fields in Taiwan using time-series Satellite Pour I'Observation de la Terre data

J. Appl. Remote Sens. 5, 053528 (Jun 02, 2011); http://dx.doi.org/10.1117/1.3595276

Alerts
- Alert Me When Cited
- Alert Me When Corrected
Tools
Share
- Email Abstract
- Connotea
- CiteULike
- del.icio.us
- BibSonomy
- Tweet this Article
- Add to Facebook

Abstract

References (46)

Chi-Farn Chen, Nguyen-Thanh Son, and Li-Yu Chang

National Central University, Center for Space and Remote Sensing Research, Taoyuan County 32001, Taiwan cfchen@csrsr.ncu.edu.tw

Su-Wei Huang,

National Central University, Department of Civil Engineering, Taoyuan County 32001, Taiwan

Rice is the most important food crop in Taiwan. During recent decades, rice production in Taiwan has sharply declined because of industrialization and urbanization. Monitoring the areas of rice cultivation thus becomes important due to the official initiatives to ensure food supply. This study aims to develop a remote sensing classification approach for mapping double-cropped irrigated rice fields in Taiwan using time-series SPOT (Satellite Pour l’Observation de la Terre) data. Three study sites with different farming conditions in Taitung, Chiayi, and Taoyuan counties were chosen to test the new classification method. Data processing steps include: 1. filtering time-series SPOT-based normalized difference vegetation index (NDVI) using empirical mode decomposition (EMD) and wavelet transform, 2. classifying double-cropped irrigated rice fields using statistical methods (i.e., correlation analysis and sign-test statistics), and 3. assessing classification accuracy. The comparisons between the classification maps and ground-truth maps in 2005 indicated that classification using the EMD-based filtered NDVI time-series data yielded more accurate results than did the wavelet transform-based filtered data.

History

Received Nov 11, 2010
Accepted May 03, 2011
Revised Apr 27, 2011
Published online Jun 02, 2011

Digital Object Identifier

http://dx.doi.org/10.1117/1.3595276

Citation

Chi-Farn Chen, Su-Wei Huang, Nguyen-Thanh Son and Li-Yu Chang, "Mapping double-cropped irrigated rice fields in Taiwan using time-series Satellite Pour I'Observation de la Terre data", J. Appl. Remote Sens. 5, 053528 (Jun 02, 2011); http://dx.doi.org/10.1117/1.3595276