Anugrah Indah Lestari, Dony Kushardono


Identification of the rice plant growth phase is an important step in estimating the harvest season and predicting rice production. It is undertaken to support the provision of information on national food availability. Indonesia’s high cloud coverage throughout the year means it is not possible to make optimal use of optical remote sensing satellite systems. However, the Synthetic Aperture Radar (SAR) remote sensing satellite system is a promising alternative technology for identifying the rice plant growth phase since it is not influenced by cloud cover and the weather. This study uses multi-temporal C-Band SAR satellite data for the period May–September 2016. VH and VV polarisation were observed to identify the rice plant growth phase of the Ciherang variety, which is commonly planted by farmers in West Java. Development of the rice plant growth phase model was optimized by obtaining samples spatially from a rice paddy block in PT Sang Hyang Seri, Subang, in order to acquire representative radar backscatter values from the SAR data on the age of certain rice plants. The Normalised Difference Polarisation Index (NDPI) and texture features, namely entropy, homogeneity and the Grey-Level Co-occurrence Matrix (GLCM) mean, were included as the samples. The results show that the radar backscatter value (σ0) of VH polarisation without the texture feature, with the entropy texture feature and GLCM mean texture feature respectively exhibit similar trends and demonstrate potential for use in identifying and monitoring the rice plant growth phase. The rice plant growth phase model without texture feature on VH polarisation is revealed as the most suitable model since it has the smallest average error.


remote sensing satellite; SAR; C-band; texture feature; rice plant growth phase

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