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

Phung, Hoang-Phi and Lam-Dao, Nguyen and Nguyen-Huy, Thong ORCID: https://orcid.org/0000-0002-2201-6666 and Le-Toan, Thuy and Apan, Armando A. ORCID: https://orcid.org/0000-0002-5412-8881 (2020) Monitoring rice growth status in the Mekong Delta, Vietnam using multitemporal Sentinel-1 data. Journal of Applied Remote Sensing, 14 (1):014518. 014518-1.

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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.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Date Deposited: 13 Jul 2020 01:50
Last Modified: 27 Jul 2020 03:25
Uncontrolled Keywords: rice growth status; monitoring; Sentinel-1 time series; Mekong delta
Fields of Research (2008): 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070108 Sustainable Agricultural Development
07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070104 Agricultural Spatial Analysis and Modelling
07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070107 Farming Systems Research
04 Earth Sciences > 0499 Other Earth Sciences > 049999 Earth Sciences not elsewhere classified
07 Agricultural and Veterinary Sciences > 0703 Crop and Pasture Production > 070399 Crop and Pasture Production not elsewhere classified
Fields of Research (2020): 30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300210 Sustainable agricultural development
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300206 Agricultural spatial analysis and modelling
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300207 Agricultural systems analysis and modelling
37 EARTH SCIENCES > 3799 Other earth sciences > 379999 Other earth sciences not elsewhere classified
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3004 Crop and pasture production > 300499 Crop and pasture production not elsewhere classified
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970104 Expanding Knowledge in the Earth Sciences
Identification Number or DOI: https://doi.org/10.1117/1.JRS.14.014518
URI: http://eprints.usq.edu.au/id/eprint/38552

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