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Park, Edward
- PublicationOpen AccessSocio-geographical evaluation of ecosystem services in an ecotourism destination: PGIS application in Tram Chim National Park, VietnamEcotourism in national parks of developing countries is increasingly recognised as a promising option to achieve sustainable development goals, regardless, might imply various paradoxical managerial challenges. This paper, therefore, seeks to contribute a methodological framework utilising ES-based social landscape metrics (SLM) to address the potential barriers in managing ecotourism-integrated multi-functional national parks. We present a mixed-method case study in Vietnam's Tram Chim National Park (TCNP), conducted via semi-structural interviews and PGIS with tourists and locals. Multiple key informants, i.e. TCNP's authorities were also interviewed to provide their managerial insights and assist in verifying the PGIS results obtained from the tourists and locals. Via the quantified and mapped SLMs, the study reveals the differences between tourists and locals in terms of how and where they perceive and appreciate the intangible values of TCNP. Through spatial statistics, we reported important spatial correlations (i) between different categories of Ecosystem Services (ES) and (ii) between ES richness and diversity on different TCNP's land covers. As a contribution to the decision-making outlook, we remarked potential areas to expand of ecotourism activities based on the spatial hot and cold spots. This study concludes by highlighting opportunities for future research in expanding on socio-geographical assessments of ES, especially in the fields of ecotourism.
WOS© Citations 22Scopus© Citations 37 116 131 - PublicationMetadata onlySoutheast Asia’s dynamic sand trade and the need for better data
Sand is a vital resource for modern structures but there is limited information on the scale of sand mining or what happens to the sand after it was mined. Here, we focus on Southeast Asia (SEA) as rising affluence and population growth has turned the region into a global sand mining hotspot. We estimated the sand extraction budget in each Southeast Asian country and quantified the volume sand that was exported and imported. In addition, the destinations in which the sand was exported to were detailed and we also clarified the origins of the imported sand. Our analysis revealed that locally mined sand was mostly consumed domestically, and sand was imported if supply was insufficient. In addition, the sand trade in SEA was also predominantly regional. Unfortunately, our understanding of the sand trade in SEA was hampered by limited and inconsistent data. For example, missing data meant that production and trade flows were unavailable for some years. The volume of sand traded between each country was also uncertain due to the mismatch of trade data. Additional information on the type of sand traded was also lacking. The reliability and credibility of existing data should be strengthened to improve material accounting.
Scopus© Citations 1 19 - PublicationOpen AccessSoil moisture observations from shortwave infrared channels reveal tornado tracks: A case in 10-11 December 2021 tornado outbreak(Wiley, 2023)
; ;Lin, Yun ;McFarquhar, Greg M.; ;Gu, Yu ;Su, Qiong ;Fu, Rong ;Lee, Kee WeiZhang, TianhaoSatellite-based post-tornado assessments have been widely used for the detection of tornado tracks, which heavily relies on the identification of vegetation changes through observations at visible and near-infrared channels. During the deadly 10–11 December 2021 tornado outbreak, a series of violent tornadoes first touched down over northeastern Arkansas, an area dominated by cropland with rare vegetation coverage in winter. Through the examination of Moderate Resolution Imaging Spectroradiometer multi-spectral observations, this study reveals significant scars on shortwave infrared channels over this region, but none are captured by visible and near-infrared channels. The dominant soil type is aquert (one of vertisols), whose high clay content well preserves the severe changes in soil structure during the tornado passage, when the topmost soil layer was removed and underlying soil with higher moisture content was exposed to the air. This study suggests a quick post-tornado assessment method over less vegetated area by using shortwave infrared channels.173 157 - PublicationMetadata onlyA deep learning framework to map riverbed sand mining budgets in large tropical deltas(Taylor & Francis, 2024)
;Kumar, Sonu; ;Tran, Dung Duc ;Wang, Jinyu ;Ho, Huu Loc ;Feng, Lian ;Kantoush, Sameh ;Doan, Van Binh ;Li, DongfengSwitzer, 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 7 15 - PublicationMetadata onlySoil salinization in agriculture: Mitigation and adaptation strategies combining nature-based solutions and bioengineering
Soil salinization is among the most critical threats to agriculture and food security. Excess of salts adversely affects soil structure and fertility, plant growth, crop yield, and microorganisms. It is caused by natural processes, such as dry climates and low precipitations, high evaporation rate, poor waterlogging, and human factors, such as inappropriate irrigation practices, poor drainage systems, and excessive use of fertilizers. The growing extremization of climate with prolonged drought conditions is worsening the phenomenon. Nature-based solutions (NBS), combined with precision or conservation agriculture, represent a sustainable response, and offer benefits through revitalizing ecosystem services. This perspective explores NBS that can be adopted, along with their challenges and implementation limitations. We also argue that NBS could not be enough to combat hunger in the world’s most vulnerable regions and fully achieve the Sustainable Development Goal – Zero Hunger (SDG2). We therefore discuss their possible combination with salt-tolerant crops based on bioengineering.
Scopus© Citations 26 13 - PublicationMetadata onlyHeavy rains and hydrogeological disasters on February 18th–19th, 2023, in the city of São Sebastião, São Paulo, Brazil: From meteorological causes to early warnings(Springer, 2024)
;Marengo, Jose A. ;Cunha, Ana P. ;Seluchi, Marcelo E. ;Camarinha, Pedro I. ;Dolif, Giovanni ;Sperling, Vinicius B. ;Alcântara, Enner H. ;Ramos, Andrea M. ;Andrade, Marcio M. ;Stabile, Rodrigo A. ;Mantovani, José; ;Alvala, Regina C. ;Moraes, Osvaldo L.Goncalves, Demervalhis study provides a thorough analysis of the landslides that occurred in the city of São Sebastião, on the northern coast of São Paulo state, Brazil, in February 18th–19th, 2023. The meteorological condition during this event was characterized by a cold front crossing over a warmer-than-normal subtropical South Atlantic, off the coast of São Paulo. Combined with the orographic effect of the Serra do Mar Mountain, the front remained stationary over the northern coastal areas of the state of São Paulo, causing an extreme and historic heavy precipitation event. An unprecedented volume of rain, amounting to 683 mm in less than 15 h, triggered landslides that generated 65 casualties and damages. Although alerts were clearly issued in advance, response among the communities was minimal, indicating the ineffectiveness of current early warning system in place. This calls for improved public policies, communication and the possible adoption of multi-hazard early warning systems to reduce risk in vulnerable areas.
Scopus© Citations 8 25 - PublicationOpen Access
113 243 - PublicationMetadata onlyThe Ayeyarwady river (Myanmar): Washload transport and its global role among rivers in the AnthropoceneThe Ayeyarwady (Irrawaddy) is the second largest river of Southeast Asia and one of the rivers with the highest load of suspended sediment delivered to the sea in the world. The Ayeyarwady is the lifeline of Myanmar which concentrates the majority of the population and GDP of the country. It is the main way of transport, a source of fluvial aggregates for development projects, hydropower, and the basin plays a major role in food supply and irrigation. Despite the Ayeyarwady ranking amongst the world’s largest rivers and its vital importance to Myanmar, scarce research has been undertaken to understand its morphodynamics and sediment transport regime. Current load estimates still heavily rely on the only systematic study of sediment transport dating back to the 19th century. Here, we provide a novel estimate for the recent washload sediment transport based on a field calibrated remote sensing model of surface suspended sediments concentrations. We show that the Ayeyarwady has likely become the river with the second or third largest delivery of washload to the sea in the world since it has so far been much less affected by damming compared to the vast majority of other rivers.
WOS© Citations 7Scopus© Citations 11 55 - PublicationMetadata onlyMapping volumetric soil moisture in the Vietnamese Red River Delta using Landsat 8 imagesThis study estimates the surface soil moisture content in a case study situated in the Vietnamese Red River Delta, using the Landsat 8 satellite images. The trapezoidal relationship between land surface temperature and vegetation index was used to obtain soil wetness indexes. A split-window algorithm was developed to overcome the missing of atmospheric data. The method was validated with ground truth across different land covers. The RMSE between the calculated and measured SMC ranges between 0.556 and 0.971 and varies across different types of land covers. The method is important to monitor SMC across large areas with limited surveyed data.
WOS© Citations 1Scopus© Citations 2 269 - PublicationMetadata onlyDeforestation as the prominent driver of the intensifying wildfire in Cambodia, revealed through geospatial analysis
Cambodia has the most fires per area in Southeast Asia, with fire activity have significantly increased since the early 2000s. Wildfire occurrences are multi-factorial in nature, and isolating the relative contribution of each driver remains a challenge. In this study, we quantify the relative importance of each driver of fire by analyzing annual spatial regression models of fire occurrence across Cambodia from 2003 to 2020. Our models demonstrated satisfactory performance, explaining 69 to 81% of the variance in fire occurrence. We found that deforestation was consistently the dominant driver of fire across 48 to 70% of the country throughout the study period. Although the influence of low precipitation on fires has increased in 2019 and 2020, the period is not long enough to establish any significant trends. During the study period, wind speed, elevation, and soil moisture had a slight influence of 6–20% without any clear trend, indicating that deforestation continues to be the main driver of fire. Our study improves the current understanding of the drivers of biomass fires across Cambodia, and the methodological framework developed here (quantitative decoupling of the drivers) has strong potential to be applied to other fire-prone areas around the world.
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