Abstract
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 R2 = 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 R2 = 0.92 and RMSE = 6.2 days (n = 153) and R2 = 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.
Highlights
Rice is one of the main cereal crops in the world that plays an important role in food security, especially in the context of climate change, environmental pollution, and population growth
Rice age was classified into 12 information layers with a 10-day interval after sowing/ transplanting, corresponding to the longest rice variety planted in this area, common rice varieties in the Mekong Delta are 85 to 105 days
In this study focused on the rice backscatter time series, the incidence angle was normalized by applying the nonlinear quadratic function to the VH polarization for the water surface to Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Applied-Remote-Sensing on 02 Nov 2021 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use match the backscattering of the surface scattering in rice fields, which has a much more important angular variation than that of the volume scattering (Fig. 9)
Summary
Rice is one of the main cereal crops in the world that plays an important role in food security, especially in the context of climate change, environmental pollution, and population growth. Climate change, resulting in an increase in extreme weather events such as drought and floods,[2] can damage rice crops and affect food security and farmer livelihoods at local and regional scales. It is, necessary to accurately and timely determine how much of the rice area is in any stage at any time or position on the map. High-temporal resolution optical sensors such as AVHRR,[4] SPOT VEGETATION,[5,6] and MODIS7–9 were used to map large-scale rice fields These optical images often have low spatial resolution (>250 m) when applied at a regional scale and are frequently affected by cloud cover. There are techniques[10,11,12] to reduce the effects of cloud, but in tropical monsoon regions like Vietnam, quasipermanent cloud cover limits the use of optical data during the rainy season
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
