In this video we follow the codes from the paper for rice mapping process.



The basic idea is to include the monthly images from Sentinel 1 and 2 in rice growing period. The monthly images from both the Sentinel 1 and 2 are stacked as the image. The stacked image is clustered from the unsupervised method. The spectra of the clusters are observed, and the rice pixels are identified.

Challenges during this method might be the presence of the clouds during the rice growing period. Also the method is not suitable for larger area, by larger area meaning the whole country, or even a district of any country.

This video is likely to be helpful for anyone wishing to build concepts of rice mapping process using Sentinel 1 and 2. You can follow the methods and shared codes from the paper for the study of the methods.

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paper
[ Title: HighResolution Mapping of Paddy Rice Extent and Growth Stages across Peninsular Malaysia Using a Fusion of Sentinel1 and 2 Time Series Data in Google Earth Engine
year: 2022
doi: https://doi.org/10.3390/rs14081875
codes shared in the paper: https://code.earthengine.google.com/6... ]

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Related Videos in the channel:
* Crop land classification in Earth Engine
   • Crop Land Classification in Earth Eng...  
* Rice Monitoring using Sentinel1 in Google Earth Engine [GEE]
   • Rice Monitoring using Sentinel1 in G...  

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Image from Commons: Vrouwen aan het werk in een rijstveld in Tanahu, Nepal, 26 april 2011 a.jpg



Any comments are welcomed.