Series: Earth and Environmental Science.įageria, N. The method for detecting biological parameter of rice growth and early planting of paddy crop by using multi temporal remote sensing data. Optimasi parameter dalam klasifikasi spasial penutup penggunaan lahan menggunakan data Sentinel SAR. Study on geometric correction algorithms for SAR images. IEEE Conference on Sustainable Information Engineering and Technology (SIET), 1, 425–9, doi: 10.1109/SIET.2017.8304176Ĭhoo, A. Prediction of paddy field area base on aerial photography using multispectral camera.
Potential of Sentinel-1 radar data for the assessment of soil and cereal cover parameters, Sensors (Switzerland) 17, doi: 10.3390/s17112617īroto, P.
Jakarta: Badan Pusat Statistik.īousbih, S., Zribi, M., Lili-Chabaane, Z., Baghdadi, N., El Hajj, M., Gao Q., & Mougenot, B. Proyeksi Penduduk Indonesia (Indonesia Population Projection) 2010-2035. Potret Perdagangan Beras 1–2.īadan Pusat Statistik Indonesia (2013). Agroinovasi Sinartani 2–7.īadan Pengkajian dan Pengembangan Perdagangan (2016). 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.īadan Litbang Pertanian (2012). The results show that the radar backscatter value (σ 0) 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 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. 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. 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. This study uses multi-temporal C-Band SAR satellite data for the period May–September 2016. 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. Indonesia’s high cloud coverage throughout the year means it is not possible to make optimal use of optical remote sensing satellite systems. It is undertaken to support the provision of information on national food availability. Identification of the rice plant growth phase is an important step in estimating the harvest season and predicting rice production.
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