Open Science Research Excellence
%0 Journal Article
%A Yi-Shiang Shiu and  Meng-Lung Lin and  Kang-Tsung Chang and  Tzu-How Chu
%D 2010 
%J  International Journal of Environmental, Chemical, Ecological, Geological and Geophysical Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 43, 2010
%T Mapping Paddy Rice Agriculture using Multi-temporal FORMOSAT-2 Images
%U http://waset.org/publications/1571
%V 43
%X Most paddy rice fields in East Asia are small parcels,
and the weather conditions during the growing season are usually
cloudy. FORMOSAT-2 multi-spectral images have an 8-meter
resolution and one-day recurrence, ideal for mapping paddy rice fields
in East Asia. To map rice fields, this study first determined the
transplanting and the most active tillering stages of paddy rice and
then used multi-temporal images to distinguish different growing
characteristics between paddy rice and other ground covers. The
unsupervised ISODATA (iterative self-organizing data analysis
techniques) and supervised maximum likelihood were both used to
discriminate paddy rice fields, with training areas automatically
derived from ten-year cultivation parcels in Taiwan. Besides original
bands in multi-spectral images, we also generated normalized
difference vegetation index and experimented with object-based
pre-classification and post-classification. This paper discusses results
of different image classification methods in an attempt to find a
precise and automatic solution to mapping paddy rice in Taiwan.
%P 264 - 270