Yi-Shiang Shiu

Publications

2 Quick Spatial Assessment of Drought Information Derived from MODIS Imagery Using Amplitude Analysis

Authors: Meng-Lung Lin, Yi-Shiang Shiu, Tzu-How Chu, Qiubing Wang, Fujun Sun

Abstract:

The normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) derived from the moderate resolution imaging spectroradiometer (MODIS) have been widely used to identify spatial information of drought condition. The relationship between NDVI and NDMI has been analyzed using Pearson correlation analysis and showed strong positive relationship. The drought indices have detected drought conditions and identified spatial extents of drought. A comparison between normal year and drought year demonstrates that the amplitude analysis considered both vegetation and moisture condition is an effective method to identify drought condition. We proposed the amplitude analysis is useful for quick spatial assessment of drought information at a regional scale.

Keywords: Remote Sensing, Drought, NDVI, NDMI, spatialassessment

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1 Mapping Paddy Rice Agriculture using Multi-temporal FORMOSAT-2 Images

Authors: Meng-Lung Lin, Yi-Shiang Shiu, Kang-Tsung Chang, Tzu-How Chu

Abstract:

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.

Keywords: normalized difference vegetation index, paddy rice fields; multi-temporal; FORMOSAT-2images, object-basedclassification

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