| dc.description.abstract | Rice is the most important staple food crop and the primary source of livelihoods for the majority of rural populations in Taiwan. The area allocated for rice cultivation accounts for approximately 5% (166,616 ha) of the total cultivating area. Therefore, rice monitoring is a crucial activity in Taiwan due to official initiatives. In recent years, optical satellite data acquired from sensors such as SPOT, MODIS, and FORMOSAT-2 satellites have been widely used for rice crop classification. However, because rice is mainly cultivated in the rainy season in Taiwan, the optical satellite data reveal challenges due to cloud cover during this season. The synthetic aperture radar (SAR) such as Radarsat-2 and ERS-2 data, which can penetrate clouds and operate in all weather conditions, are generally expensive. With the launch of Sentinel-1A in 2014, it is possible to acquire free VV and VH polarization data in the study region. This study aims to develop a mapping approach to delineate rice cultivation areas in Central Taiwan using the Normalized Difference Sigma-naught Index (NDSI) calculated from the time-series Sentinel-1A VV and VH polarization data. Two types of NDSI were used in this study: (1) static NDSI, which was calculated using only two images of sowing and heading dates, and (2) dynamic NDSI, which was calculated using the time series of images. An assessment of the applicability of VV and VH polarization data of Sentinel-1A and different types of NDSI for rice crop mapping was also performed. The methodology of this study comprises five steps: (1) data pre-processing, including radiometric, geometric corrections, and speckle noise filtering of the backscattering coefficient of VV and VH polarization data, (2) calculation of static and dynamic NDSI, (3) image segmentation, (4) threshold-based rice classification using the expectation-maximization algorithm, and (5) accuracy assessment of the mapping results using the ground rice reference data and government rice area statistics. The mapping results achieved from the ascending static NDSI VH and VV polarization data indicated the overall accuracies of 85.1% and 65.1% and Kappa coefficients of 0.69 and 0.29, respectively, while those from the ascending dynamic NDSI VH and VV polarization data indicated the better overall accuracies of 92.1% and 78.2% and Kappa coefficients of 0.85 and 0.56, respectively. Similarly, the results obtained the descending static NDSI VH and VV polarization data (overall accuracies of 92.0% and 81.1% and Kappa coefficients of 0.84 and 0.62) were better than those from the ascending static NDSI VH and VV polarization (overall accuracies of 88.1% and 69.1% and Kappa coefficients of 0.75 and 0.37). Furthermore, the RMSE value obtained by comparing the ascending and descending VH classification results and government statistics was lower than 1%, in all cases. Compared to VH polarization, the RMSE of VV polarization results was higher than that of VH results. This study demonstrates that the potential applicability of VH polarization data using the dynamic method for rice crop mapping in the study region. The methods were thus proposed for rice monitoring in the study region. | en_US |