Estimation of Rice Age in Sentinel-2 Image with Gaussian Mixture Model Approach

  • Muhammad Ardiansyah Departemen Ilmu Tanah dan Sumberdaaya Lahan, Fakultas Pertanian, IPB University, Jl. Meranti – Kampus IPB Dramaga, Bogor, West Java 16680
  • Khursatul Munibah Departemen Ilmu Tanah dan Sumberdaya Lahan, Fakultas Pertanian, IPB University, Jl. Meranti – Kampus IPB Dramaga, Bogor, West Java 16680
  • Nadhifah Raniah Program Studi Manajemen Sumberdaya Lahan, Departemen Ilmu Tanah dan Sumberdaaya Lahan, Fakultas Pertanian IPB University, Jl. Meranti – Kampus IPB Dramaga, Bogor, West Java 16680
Keywords: Multi-temporal, GMM, Rice field, Growth stage

Abstract

Monitoring the growth phase or age of rice is carried out to estimate the harvest area and production of rice plants. Remote sensing technology can monitor the age of rice plants, one of which is using Sentinel-2 imagery. This research aims to identify the age of rice plants, and to map/monitor the spatio-temporal distribution of rice age using GMM classification on multi-temporal Sentinel-2 images. The GMM classification is a simple method based on density function. The research was carried out in rice fields at the Agency of Agriculture, Plantation, Food and Horticulture, Cianjur Regency, West Java Province, with observation periods from May - August 2021. The results of the research showed that the temporal spectral response was different between the visible band (blue, green and red) and the near infrared band, where the 3 visible bands have a similar pattern with a lower value than the near infrared band. Result of GMM classification can show the continuity of rice age classes at each image acquisition from 0 - 130 days after planting, so it can be used to monitor the age or growth phase of rice.

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Published
2024-04-01
How to Cite
ArdiansyahM., MunibahK., & RaniahN. (2024). Estimation of Rice Age in Sentinel-2 Image with Gaussian Mixture Model Approach. Jurnal Ilmu Tanah Dan Lingkungan, 26(1), 21-28. https://doi.org/10.29244/jitl.26.1.21-28