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In this study, high spatial resolution (3 m) PlanetScope (PS) imagery was utilized to map burned areas caused by a wildfire occurring on January 10, 2024, on Co Tien Mountain in Nha Trang city, Khanh Hoa province, South Central Coast of Vietnam. A pre-fire image, acquired ten days earlier, on December 31, 2023, and a post-fire one, acquired nearly one month after, on February 04, 2024, were used to create pre- and post-fire Normalized Difference Vegetation Index (NDVI) maps of the study area, then the difference of NDVI (dNDVI). A threshold (T = 0.20), proposed by the author, was applied to the histogram of the dNDVI product to classify the study area into two clusters: burned pixels (dNDVI > T) and unburned pixels (dNDVI

Abstract Central Sahel is affected by a reinforcement of rainfall since the beginning of 1990s. This increase in rainfall is affected by high inter-annual variability and is characterized by extreme rain events causing floods of unprecedented magnitude. However, few studies have been carried out on these extreme events. Moreover, with current climate change expected to strengthen the hydrological cycle, we don’t know if these events could become more frequent. Here, we report the hydrological changes that currently occur in the Lake Chad basin. Based on ground observations and satellite data, we focused on the 2022 flood event, demonstrating that it was the most important event from the last 60 years, comparable to what occurred during the last wet period between the 1950s and the 1960s. We showed that under this precipitation regime and if warming is not regulated at a global scale, the return period of the 2022 major riverine flood is expected to be between 2 and 5 years. By using modelling experiments, our study also suggested that in the next decade, future flow rates of the main rivers draining the Lake Chad basin could reach the values observed in the 1950s. These results strongly suggest anticipating water management in a context of poor infrastructural development.

Soil Erosion Susceptibility Mapping (SESM) is one of the practical approaches for managing and mitigating soil erosion. This study applied four Machine Learning (ML) models, namely the Multilayer Perceptron (MLP) classifier, AdaBoost, Ridge classifier, and Gradient Boosting classifier to perform SESM in a region of Nghe An province, Vietnam. The development of these models incorporated seven factors influencing soil erosion: slope degree, slope aspect, curvature, elevation, Normalized Difference Vegetation Index (NDVI), rainfall, and soil type. These factors were determined based on 685 identified soil erosion locations. According to SHapley Additive exPlanations (SHAP) analysis, soil type emerged as the most significant factor influencing soil erosion. Among all the developed models, the Gradient Boosting classifier demonstrated the highest prediction power, followed by the MLP classifier, Ridge classifier, and AdaBoost, respectively. Therefore, the Gradient Boosting classifier is recommended for accurate SESM in other regions too, taking into account the local geo-environmental factors. HIGHLIGHTS Soil erosion has been modeled and a soil erosion susceptibility map was generated.; Several ML models, including the MLP classifier, Ada Boost, Ridge classifier, and Gradient Boosting classifier were implemented.; Developed models were tuned using the Grid Search CV technique.; The Gradient Boosting classifier performed the best.; About 33% of the study area has a high and very high susceptibility to soil erosion occurrence.;

This study compares the capability of Sentinel-1, Sentinel-2, and PlanetScope (PS) satellites in monitoring the variations of surface water of Dai Lai Lake, located in North Vietnam, for the 2018–2023 period. The analysis involves the utilization of Google Earth Engine to partially process Sentinel-1 and Sentinel-2 observations, while PS observations are processed using local computers, to generate VH-polarized backscatter coefficient, Normalized Difference Water Index (NDWI), and Modified of Normalized Difference Water Index (MNDWI) maps. The method for making binary water/non-water maps primarily employs the Otsu algorithm on each single map derived from the previous step. Findings reveal that the lake's water extent remains relatively stable over the 6-year period, and is not strongly affected by the seasonal cycle. Although the spatial distribution patterns of the lake exhibit significant similarity, average water extent of the lake derived from 3-m resolution PS imagery is about 2.17 and 5.60% more than that obtained from 10-m resolution Sentinel-2 and Sentinel-1 imagery, respectively. PS observations are effective for monitoring small lakes, but it is advised to check the quality of its NIR band. Sentinel-2 observations prove great effectiveness for lake monitoring, using both NDWI and MNDWI. For Sentinel-1 observations, potential misclassifications could arise due to similarities in VH-polarized backscatter coefficients between water surfaces and other flat surfaces. HIGHLIGHTS The lake's surface water extent maps derived from PlanetScope is about 5.60 and 2.17% more than that derived from Sentinel-1 and Sentinel-2.; NDWI and MNDWI provide similar results in small lake mapping and monitoring.; Quality of the PlanetScope NIR wavelength is not always as good as that from Sentinel-2 satellite.; Many similarities in Sentinel-1 backscatter coefficients between water surfaces and other flat surfaces.;

This study estimates monthly variation of surface water volume of Thac Mo hydroelectric reservoir (located in South Vietnam), during the 2016–2021 period. Variation of surface water volume is estimated based on variation of surface water extent, derived from Sentinel-1 observations, and variation of surface water level, derived from Jason-3 altimetry data. Except for drought years in 2019 and 2020, surface water extent of Thac Mo reservoir varies in the range 50–100 km2, while its water level varies in the range 202–217 m. Correlation between these two components is high (R = 0.948), as well as correlation between surface water maps derived from Sentinel-1 and free-cloud Sentinel-2 observations (R = 0.98), and correlation between surface water level derived from Jason-3 altimetry data and from in situ measurement (R = 0.99; RMSE = 0.86 m). We showed that water volume of Thac Mo reservoir varies between −0.3 and 0.4 km3 month−1, and it is in a very good agreement with in situ measurement (R = 0.95; RMSE = 0.0682 km3 month−1). This study highlights the advantages in using different types of satellite observations and data for monitoring variation of lakes’ water storage, which is very important for regional hydrological models. Similar research can be applied to monitor lakes in remote areas where in situ measurements are not available, or cannot be accessed freely.

Studying the spatial and temporal distribution of surface water resources is critical, especially in highly populated areas and in regions under climate change pressure. There is an increasing number of satellite Earth observations that can provide information to monitor surface water at global scale. However, mapping surface waters at local and regional scales is still a challenge for numerous reasons (insufficient spatial resolution, vegetation or cloud opacity, limited time-frequency or time-record, information content of the instrument, lack in global retrieval method, interpretability of results, etc.). In this paper, we use 17 years of the MODIS (MODerate-resolution Imaging Spectro-radiometer) observations at a 8-day resolution. This satellite dataset is combined with ground expertise to analyse the evolution of surface waters at the Cambodia/Vietnam border in the Upper Mekong Delta. The trends and evolution of surface waters are very significant and contrasted, illustrating the impact of agriculture practices and dykes construction. In most of the study area in Cambodia. surface water areas show a decreasing trend but with a strong inter-annual variability. In specific areas, an increase of the wet surfaces is even observed. Ground expertise and historical knowledge of the development of the territory enable to link the decrease to ongoing excavation of drainage canals and the increase of deforestation and land reclamation, exposing flooded surfaces previously hidden by vegetation cover. By contrast, in Vietnam, the decreasing trend in wet surfaces is very clear and can be explained by the development of dykes dating back to the 1990s with an acceleration in the late 2000s as part of a national strategy of agriculture intensification. This study shows that coupling satellite data with ground-expertise allows to monitor surface waters at mesoscale (2), demonstrating the potential of interdisciplinary approaches for water ressource management and planning.

The study was conducted from June to December 2021 to assess the technical – financial aspect and the existing advantages and difficulties of the giant freshwater prawn culture in coconut garden ditch culture by interviewing 32 farming households in Thanh Phu district, Ben Tre Province. The study results showed that the average area for each ditch was 0.38 ± 0.29 ha, with density stocking 4.15 ± 1.21 PL/m2. For prawns were harvested after over 8 months, the prawn yield was 421.08 ± 172.21 ton/ha/crop, the profit was 34.02 ± 14.02 million VND/ha/crop and the benefit ratio was 1.33 ± 0.56 times. The yield and the profits were affected by density stocking and nursing survival rate. Besides the advantages of labor resources, natural conditions, and ease and less risk of giant freshwater prawn culture; however, the system currently faces many difficulties, such as lower nursing survival rate, unguaranteed quality, and quantity of postlarvae, salinity intrusion, unstable product market. Therefore, in order to contribute to sustainable aquaculture development, the necessary solutions include (1) providing high quality and quantity of postlarvae; (2) using settling ponds to have active water; (3) building and improving infrastructure, and irrigation systems to prevent salinity intrusion; and (4) finding the product market.

Objective: Intraoperative neurophysiological monitoring in intramedullary spinal cord tumor removal surgery helps surgeons detect early warning signs of postoperative nerve damage, in order to reduce or prevent permanent neuron injury. We performed a study to evaluate the value of intraoperative neurophysiological monitoring techniques in intramedullary spinal cord tumor resection surgery. Methods: We performed a retrospective study of 29 patients undergoing surgery for intramedullary spinal cord tumors and intraoperative neurophysiological monitoring from 2017 to 2021 at the University Medical Center, Ho Chi Minh City. Clinical assessment before and after surgery, intraoperative neurophysiological monitoring to find out the sensitivity, specificity, positive predictive value, and negative predictive value of intraoperative neurophysiological monitoring techniques were performed. Results: Of the 29 patients, 4 patients had worse postoperative neurological symptoms (13.8%) at 1 day after surgery. The rate of postoperative worsening neurological symptoms decreased to 10.3% at the 1-month follow-up. SSEP (somatosensory evoked potential) had 75% sensitivity and 72% specificity in detecting postoperative nerve damage, while the sensitivity and specificity of MEP (motor evoked potential) were 100% and 80%, respectively. Conclusion: Both SSEP and MEP have a high sensitivity in detecting postoperative nerve damage, meanwhile, MEP is more sensitive than SSEP. These techniques help predict and possibly prevent timely neurological damage during intramedullary spinal cord resection surgery.

In this study, oil was converted to biodiesel via transesterification reaction under the presence of CaO at the laboratory. This aims to evaluate and compare the influence of Jatropha oil with commercial diesel (CD) fuel on the engine operating characteristics. Secondly, this study is to compare engine performance and temperature characteristics of cooling water and lubricant oil under various engine operating conditions of the test engine fueled by Jatropha oil and CD. The results indicated that the engine torque of the engine running with Jatropha oil dropped from 0.2 kW to 0.3 kW at all speeds and its brake specific fuel consumption (BSFC) increased at almost every speed due to the low heating value and high viscosity of the Jatropha fuel. The BTEs of the engines fuelled with Jatropha oil was 0.3%, 1.0%, 0.6%, 0.7%, 1.1%, 1.6%, and 1.0% smaller than the BTEs of the engine when varied speed from 1000 rpm to 2200 rpm. However, the difference was trivial. Also, Jatropha oil contributed to reducing the oil temperature of lubricant and cooling water.