Rice Crop Monitoring in the Mekong Delta, Vietnam Using Multi-temporal Sentinel-1 Data with C-Band

Hoang-Phi, Phung; Nguyen, Lam Duc

doi:10.1007/978-981-15-5144-4_94

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…The study evaluated the ability to estimate rice yield in the 2018 crops by analyzing VH polarized Sentinel-1 data with in-situ data as shown in Figure 2. Radar images were collected during one rice crop, then go through the following steps: a) Pre-processing [26,27]; b) Rice mapping: applying threshold method for multi-temporal images acquired during the crop season [14,28]; c) Extracting radar backscatter values according to rice age at the sample fields [29,30]; d) Regression analysis and mapping estimated rice yield [24]. WS SA AW Figure 2.…”

Section: Methodsmentioning

confidence: 99%

Application of multi-temporal Sentinel-1 SAR data for yield estimation of rice crops in An Giang, Vietnam

Hoang-Phi

Nguyen

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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Rice is one of the main agricultural crops and plays an important role in food security. Therefore, it is essential to propose a method for monitoring the distribution of rice yield. Radar remote sensing data sources provide a sustainable solution for rice monitoring challenges in the countries located in the tropical monsoon region like Vietnam. The SAR (Synthetic Aperture Radar) remote sensing data from the Sentinel-1 satellite provided by the European Space Agency (ESA) is free of charge, has a large coverage and high spatial-temporal resolution. In this paper, rice growing areas in the An Giang province of Vietnam Mekong Delta were analyzed, which demonstrates the potential applications of multi-temporal data and proposes a method to estimate rice yield for agricultural management. The analysis results showed that in 2018 the Winter-Spring rice crop has the highest yield, and the Autumn-Winter crop has the lowest yield. Accurate and timely estimation of rice yield and production can provide important information in terms of spatial distribution and seasonal yield for government and decision-makers in policy making related to import and export.

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Section: Methodsmentioning

confidence: 99%

Application of multi-temporal Sentinel-1 SAR data for yield estimation of rice crops in An Giang, Vietnam

Hoang-Phi

Nguyen

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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“…The overall steps performed for better understanding of the behaviors of crop phenology based on the radar backscattering of S-1 data are presented in Figure 4. The rice-growing regions were extracted by the threshold classification method [25,35] (Figure 4a). In addition, this study also established the salinity isolines (4 g/L) using the observed dataset to assess the effect of salinity intrusion on rice-planted areas using GIS analysis tools on QGIS software.…”

Section: Methodsmentioning

confidence: 99%

“…In contrast, microwaves are mostly transparent to atmospheric conditions including haze, rain, snow, clouds, and smoke depending on wavelengths. Radar remote sensing satellites, such as Sentinel-1 and COSMO-SkyMed, acquire imaging data with high spatial and temporal resolutions appropriate for mapping rice cultivated areas [24,25], sowing date [26], and monitoring the number of days after planting [27].…”

Section: Introductionmentioning

confidence: 99%

Sentinel-1 SAR Time Series-Based Assessment of the Impact of Severe Salinity Intrusion Events on Spatiotemporal Changes in Distribution of Rice Planting Areas in Coastal Provinces of the Mekong Delta, Vietnam

Hoang-Phi

Lam-Dao²,

Pham-Van

et al. 2020

Remote Sensing

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Food security has become a key global issue due to rapid population growth, extensive conversion of arable lands, and declining overall productivity in some areas because of the effects of floods, water shortage, salinity intrusion, and plant diseases. In this study, we analyzed the relationship between the pattern of salinity intrusion and the spatiotemporal distribution of rice cultivation in the winter–spring crops of 2015, 2016, 2019 and 2020 in coastal provinces of the Vietnamese Mekong Delta. Sentinel-1 (S-1) data were used to extract the spatial distribution information of six rice growth stages based on a rice age algorithm. The classification accuracy of rice crop growth stages was found to have an overall accuracy of 85% and a Kappa coefficient of 0.80 (n = 373). For evaluating salinity intrusion effects, salinity isolines (4 g/L) were used to determine the percentage of rice areas affected. Results show that in the years observed to have severe salinity intrusion such as 2016 and 2020, a strong shift in planting calendar was identified to avoid salinity intrusion, with some areas being sown or transplanted 10–30 days earlier than normal planting. In addition, the lack of irrigation water and salinity intrusion limits rice cultivation in the dry season of coastal areas. Further analysis from the S-1 data confirms that the spatiotemporal distribution of rice cultivation is related to the change in government policy/recommendation affected by salinity intrusion. These findings demonstrate the potential and feasibility of using S-1 data to develop an operational rice crop adaptation framework on the delta scale.

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Rice Growth Stage Monitoring and Yield Estimation in the Vietnamese Mekong Delta Using Multi-temporal Sentinel-1 Data

Hoang-Phi

Lam-Dao

Nguyen-Van-Anh

et al. 2022

Remote Sensing of Agriculture and Land Cover/Land Use Changes in South and Southeast Asian Countries

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Rice Crop Monitoring in the Mekong Delta, Vietnam Using Multi-temporal Sentinel-1 Data with C-Band

Cited by 6 publications

References 12 publications

Application of multi-temporal Sentinel-1 SAR data for yield estimation of rice crops in An Giang, Vietnam

Application of multi-temporal Sentinel-1 SAR data for yield estimation of rice crops in An Giang, Vietnam

Sentinel-1 SAR Time Series-Based Assessment of the Impact of Severe Salinity Intrusion Events on Spatiotemporal Changes in Distribution of Rice Planting Areas in Coastal Provinces of the Mekong Delta, Vietnam

Rice Growth Stage Monitoring and Yield Estimation in the Vietnamese Mekong Delta Using Multi-temporal Sentinel-1 Data

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