Economic Feasibility of Diversified Farming System in the Flood-Prone Mekong Delta: Simulation for Dike Area in An Giang Province, Vietnam

Yokoyama, Shigeki; Le, Canh Dung; Fuji, Hideto; Fujihara, Yoichi; Hoshikawa, Keigo

doi:10.22004/ag.econ.280972

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“…The mixture of soil, vegetation, and water is also prevalent in An Giang because it is the major province for cultivated rice production in Vietnam [105]. The government developed a full-dike system in An Giang province for water management and to increase the productivity of agricultural activities in this region [106]. Therefore, a necessary comparison of surface water maps derived from Sentinel-2 NDWI and MNDWI products is needed to understand the impact of built-up and mixed pixels, especially for riverbank areas and paddy fields.…”

Section: Comparison Of Surface Water Detections Derived From Sentinel...mentioning

confidence: 99%

“…It should be noted that the algorithm needs an initial flood map for generating the next images; thus, we assumed that the initial flood map on March 12, 2017 (the driest month in the VMD [77]) is all non-flooded to activate the flood monitoring algorithm. However, An Giang province is a very complex area in terms of water dynamics and vegetation existence, such as rice cultivation [106], hydrological variations [18], a full-dike system for water management [86], and differences in agricultural calendar practices. The assumption that all pixels in the initial flood map on 12 March 2017 are non-flooded could make the model work, but the water pixels in the initial surface water map could potentially be flooded.…”

Section: Flood Mapping Algorithm Using Sar Sentinel-1 Time Series Datamentioning

confidence: 99%

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Surface Water Mapping and Flood Monitoring in the Mekong Delta Using Sentinel-1 SAR Time Series and Otsu Threshold

Tran

Menenti

2022

Remote Sensing

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The annual flood and the alteration in hydrological regimes are the most vital concerns in the Vietnamese Mekong Delta (VMD). Although synthetic aperture radar (SAR) Sentinel-1 imagery is widely used for water management, only a few studies have used Sentinel-1 data for mapping surface water and monitoring flood events in the VMD. This study developed an algorithm to implement (i) automatic Otsu threshold on a series of Sentinel-1 images to extract surface water and (ii) time series analyses on the derived surface water maps to detect flood water extent in near-real-time (NRT). Specifically, only cross-polarized VH was selected after an assessment of different Sentinel-1 polarizations. The dynamic Otsu thresholding algorithm was applied to identify an optimal threshold for each pre-processed Sentinel-1 VH image to separate water from non-water pixels for producing a time series of surface water maps. The derived Sentinel-1 surface water maps were visually compared with the Sentinel-2 Full Resolution Browse (FRB) and statistically examined with the Sentinel-2 Multispectral Instrument (MSI) surface water maps, which were generated by applying the Otsu threshold on the normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) images. The visual comparison showed a strong correspondence between the Sentinel-1 surface water maps and Sentinel-2 FRB images in three periods, including rice’s sowing season, flood period, and rice’s maturation stage. A good statistical agreement suggested that the performance of the dynamic Otsu thresholding algorithm on Sentinel-1 image time series to map surface water is effective in river areas (R2 = 0.97 and RMSE = 1.18%), while it is somewhat lower in paddy field areas (R2 = 0.88 and RMSE = 3.88%). Afterward, a flood mapping algorithm in NRT was developed by applying the change-detection-based time series analyses on the derived Sentinel-1 surface water maps. Every single pixel at the time is respectively referred to its state in the water/non-water and flooded/non-flooded maps at the previous time to be classified into a flooded or non-flooded pixel. The flood mapping algorithm enables updates at each time step to generate temporal flood maps in NRT for monitoring flood water extent in large-scale areas. This study provides a tool to rapidly generate surface water and flood maps to support water management and risk reduction in the VMD. The future improvement of the current algorithm is discussed.

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Section: Comparison Of Surface Water Detections Derived From Sentinel...mentioning

confidence: 99%

Section: Flood Mapping Algorithm Using Sar Sentinel-1 Time Series Datamentioning

confidence: 99%

Surface Water Mapping and Flood Monitoring in the Mekong Delta Using Sentinel-1 SAR Time Series and Otsu Threshold

Tran

Menenti

2022

Remote Sensing

View full text Add to dashboard Cite

show abstract

Economic Feasibility of Diversified Farming System in the Flood-Prone Mekong Delta: Simulation for Dike Area in An Giang Province, Vietnam

Cited by 1 publication

References 0 publications

Surface Water Mapping and Flood Monitoring in the Mekong Delta Using Sentinel-1 SAR Time Series and Otsu Threshold

Surface Water Mapping and Flood Monitoring in the Mekong Delta Using Sentinel-1 SAR Time Series and Otsu Threshold

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