4.3 Article

Monitoring rice growth status in the Mekong Delta, Vietnam using multitemporal Sentinel-1 data

Journal

JOURNAL OF APPLIED REMOTE SENSING
Volume 14, Issue 1, Pages -

Publisher

SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
DOI: 10.1117/1.JRS.14.014518

Keywords

rice growth status; monitoring; Sentinel-1 time series; Mekong delta

Funding

  1. Vietnam Academy of Science Technology [VT-UD-08/17-20]
  2. Georice research project: Towards Global Earth Observation of Rice, European Space Agency [4000113388/15/I-NB]

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Rice is one of the world's most dominant staple foods, and hence rice farming plays a vital role in a nation's economy and food security. To examine the applicability of synthetic aperture radar (SAR) data for large areas, we propose an approach to determine rice age, date of planting (dop), and date of harvest (doh) using a time series of Sentinel-1 C-band in the entire Mekong Delta, Vietnam. The effect of the incidence angle of Sentinel-1 data on the backscatter pattern of paddy fields was reduced using the incidence angle normalization approach with an empirical model developed in this study. The time series was processed further to reduce noise with fast Fourier transform and smoothing filter. To evaluate and improve the accuracy of SAR data processing results, the classification outcomes were verified with field survey data through statistical metrics. The findings indicate that the Sentinel-1 images are particularly appropriate for rice age monitoring with R-2 = 0.92 and root-mean-square error (RMSE) = 7.3 days (n = 241) in comparison to in situ data. The proposed algorithm for estimating dop and doh also shows promising results with R-2 = 0.92 and RMSE = 6.2 days (n = 153) and R-2 = 0.70 and RMSE = 5.7 days (n = 88), respectively. The results have indicated the ability of using Sentinel-1 data to extract growth parameters involving rice age, planting and harvest dates. Information about rice age corresponding to the growth stages of rice fields is important for agricultural management and support the procurement and management of agricultural markets, limiting the negative effects on food security. The results showed that multitemporal Sentinel-1 data can be used to monitor the status of rice growth. Such monitoring system can assist many countries, especially in Asia, for managing agricultural land to ensure productivity. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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