Park, Edward

Preferred name
Park, Edward
Email
edward.park@nie.edu.sg
Department
Humanities & Social Studies Education (HSSE)
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    New systematically measured sand mining budget for the Mekong delta reveals rising trends and significant volume underestimations
    (Elsevier, 2022)
    Gruel, Charles-Robin
    ;
    Park, Edward 
    ;
    Switzer, Adam D.
    ;
    Sonu, Kumar
    ;
    Ho, Huu Loc
    ;
    Sameh, Kantoush
    ;
    Doan, Van Binh
    ;
    Feng, Lian
    The river beds of the Mekong Delta are some of the most intensively sand mined places in the world. However, sand mining budgets remain limited to rough and indirect estimates. Here, we provide a first systematic, field-based estimation of the Mekong Delta’s sand mining budget. This budget overcomes the limitations of relying on officially declared statistics and bathymetric surveys of short channel reaches. We applied Sentinel-1 radar imagery to monitor the distribution of sand mining activities using boat metrics-driven mining intensity maps correlated with a field-based bathymetry difference map which were derived from two extensive bathymetric surveys conducted in 2014 and 2017. The two surveys cover ∼ 100 km in the Tiền River, reaching approximately 15% of the Mekong Delta. We then extrapolated the Tiền River findings to the broader Vietnamese Mekong Delta from 2015 to 2020 and measured a continuous increase of the extraction budget by ∼ 25% between 2015 (38 Mm3/yr) and 2020 (47 Mm3/yr). We estimated a total sand mining budget of 254 Mm3 during the 6-year study period with an average annual rate of ∼ 42 Mm3. Our field-based annual rates are higher than both official declarations provided and estimates from previous studies which implies that a substantial portion of the sand mining budget remains unaccounted for. Riverbed sand mining remains a key threat to the Mekong Delta as it contributes to a multitude of other environmental threats including dam construction effects on sedimentation, ongoing subsidence, sea level rise and recurring saltwater intrusion. This study offers a new approach that can be implemented elsewhere to allow for systematic monitoring and quantification of sand mining activities that are vital for assessing future projections on environmental impacts.
    WOS© Citations 13Scopus© Citations 20  50
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    Publication
    Metadata only
    A deep learning framework to map riverbed sand mining budgets in large tropical deltas
    (Taylor & Francis, 2023)
    Suno Kumar
    ;
    Park, Edward 
    ;
    Tran, Dung Duc
    ;
    Wang, Jinyu
    ;
    Ho, Huu Loc
    ;
    Feng, Lian
    ;
    Sameh, A. Kantoush
    ;
    Van Binh, Doan
    ;
    Li, Dongfeng
    ;
    Switzer, Adam D.

    Rapid urbanization has dramatically increased the demand for river sand, leading to soaring sand extraction rates that often exceed natural replenishment in many rivers globally. However, our understanding of the geomorphic and social-ecological impacts arising from Sand Mining (SM) remains limited, primarily due to insufficient data on sand extraction rates. Conventionally, bathymetry surveys and compilation of declared amounts have been used to quantify SM budgets, but they are often costly and laborious, or result in inaccurate quantification. Here, for the first time, we developed a Remote Sensing (RS)-based Deep Learning (DL) framework to map SM activities and budgets in the Vietnamese Mekong Delta (VMD), a global SM hotspot. We trained a near real-time object detection system to identify three boat classes in Sentinel-1 imagery: Barge with Crane (BC), Sand Transport Boat (STB), and other boats. Our DL model achieved a 96.1% Mean Average Precision (mAP) across all classes and 98.4% for the BC class, used in creating an SM boat density map at an Intersection over Union (IoU) threshold of 0.50. Applying this model to Sentinel-1, 256,647 boats were detected in the VMD between 2014–2022, of which 17.4% were BC. Subsequently, the annual SM budget was estimated by correlating it with a recent riverbed incision map. Our results showed that, between 2015–2022, about 366 Mm3 of sand has been extracted across the VMD. The annual budget has progressively increased from 34.92 Mm3 in 2015 to 53.25 Mm3 in 2022 (by 52%), with an annual increment of around 2.79 Mm3. At the provincial-scale, Dong Thap, An Giang, Vinh Long, Tien Giang, and Can Tho were the locations of intensive mining, accounting for 89.20% of the total extracted volume in the VMD. Finally, our estimated budgets were validated with previous research that yielded a correlation coefficient of 0.99% (with bias of 2.65%). The automatic DL framework developed in this study to quantify SM budgets has a high potential to be applied to other deltas worldwide also facing intensive SM.

    Scopus© Citations 4  6