Institute of Marine Geology and Geophysics

Rice is the most important food security crop in Asia. Information on its seasonal extent forms part of the national accounting of many Asian countries. Synthetic Aperture Radar (SAR) imagery is highly suitable for detecting lowland rice, especially in tropical and subtropical regions, where pervasive cloud cover in the rainy seasons precludes the use of optical imagery. Here, we present a simple, robust, rule-based classification for mapping rice area with regularly acquired, multi-temporal, X-band, HH-polarized SAR imagery and site-specific parameters for classification. The rules for rice detection are based on the well-studied temporal signature of rice from SAR backscatter and its relationship with crop stages. We also present a procedure for estimating the parameters based on “temporal feature descriptors” that concisely characterize the key information in the rice signatures in monitored field locations within each site. We demonstrate the robustness of the approach on a very large dataset. A total of 127 images across 13 footprints in six countries in Asia were obtained between October 2012, and April 2014, covering 4.78 m ha. More than 1900 in-season site visits were conducted across 228 monitoring locations in the footprints for classification purposes, and more than 1300 field observations were made for accuracy assessment. Some 1.6 m ha of rice were mapped with classification accuracies from 85% to 95% based on the parameters that were closely related to the observed temporal feature descriptors derived for each site. The 13 sites capture much of the diversity in water management, crop establishment and maturity in South and Southeast Asia. The study demonstrates the feasibility of rice detection at the national scale using multi-temporal SAR imagery with robust classification methods and parameters that are based on the knowledge of the temporal dynamics of the rice crop. We highlight the need for the development of an open-access library of temporal signatures, further investigation into temporal feature descriptors and better ancillary data to reduce the risk of misclassification with surfaces that have temporal backscatter dynamics similar to those of rice. We conclude with observations on the need to define appropriate SAR acquisition plans to support policies and decisions related to food security.

Lake sediments constitute natural archives of past environmental changes. Historically, research has focused mainly on generating regional climate records, but records of human impacts caused by land use and exploitation of freshwater resources are now attracting scientific and management interests. Long-term environmental records are useful to establish ecosystem reference conditions, enabling comparisons with current environments and potentially allowing future trajectories to be more tightly constrained. Here we review the timing and onset of human disturbance in and around inland water ecosystems as revealed through sedimentary archives from around the world. Palaeolimnology provides access to a wealth of information reflecting early human activities and their corresponding aquatic ecological shifts. First human impacts on aquatic systems and their watersheds are highly variable in time and space. Landscape disturbance often constitutes the first anthropogenic signal in palaeolimnological records. While the effects of humans at the landscape level are relatively easily demonstrated, the earliest signals of human-induced changes in the structure and functioning of aquatic ecosystems need very careful investigation using multiple proxies. Additional studies will improve our understanding of linkages between human settlements, their exploitation of land and water resources, and the downstream effects on continental waters.

For effective management of water quantity and quality, it is absolutely essential to estimate the pollution level of the existing surface water. This case study aims to evaluate the performance of twelve machine learning (ML) models, including five boosting-based algorithms (adaptive boosting, gradient boosting, histogram-based gradient boosting, light gradient boosting, and extreme gradient boosting), three decision tree-based algorithms (decision tree, extra trees, and random forest), and four ANN-based algorithms (multilayer perceptron, radial basis function, deep feed-forward neural network, and convolutional neural network), in estimating the surface water quality of the La Buong River in Vietnam. Water quality data at four monitoring stations alongside the La Buong River for the period 2010–2017 were utilized to calculate the water quality index (WQI). Prediction performance of the ML models was evaluated by using two efficiency statistics (i.e., R2 and RMSE). The results indicated that all twelve ML models have good performance in predicting the WQI but that extreme gradient boosting (XGBoost) has the best performance with the highest accuracy (R2 = 0.989 and RMSE = 0.107). The findings strengthen the argument that ML models, especially XGBoost, may be employed for WQI prediction with a high level of accuracy, which will further improve water quality management.

In aquatic environments, assessment of microplastic concentrations is increasing worldwide but environments from developing countries remain under-evaluated. Due to disparities of facilities, financial resources and human resources between countries, protocols of sampling, analysis and observations used in developed countries cannot be fully adapted in developing ones, and required specific adaptations. In Viet Nam, an adapted methodology was developed and commonly adopted by local researchers to implement a microplastic monitoring in sediments and surface waters of 21 environments (rivers, lakes, bays, beaches) of eight cities or provinces. Microplastic concentrations in surface waters varied from 0.35 to 2522 items m-3, with the lowest concentrations recorded in the bays and the highest in the rivers. Fibers dominated over fragments in most environments (from 47% to 97%). The microplastic concentrations were related to the anthropogenic pressure on the environment, pointing out the necessity in a near future to identify the local sources of microplastics.

CuO and ZnO NPs benefit ARG propagation by stimulating signal transduction in sludge bacteria.

<italic>Sargassum</italic>(F. Sargassaceae) is an important seaweed excessively distributed in tropical and subtropical regions.

The objective of this study is to attempt a new soft computing approach for assessment of landslide susceptibility in the Luc Yen district, Yen Bai province (Viet Nam) using a novel classifier ensemble model of Naïve Bayes and Rotation Forest. First, history of 95 landslide locations was identified byfield investigations and interpretation of aerial photos. Also, the total ten landslide causal factors were selected (slope, aspect, elevation, curvature, lithology, land use, distance to roads, distance to rivers, distance to faults, and rainfall) to evaluate the spatial relationship with landslide occurrences. Information Gain technique is carried out to quantify the predictive capability of these factors. Second, landslide susceptibility assessment was carried out utilizing the novel classifier ensemble model. Finally, the performance of landslide model was validated using receiver operating characteristic curve technique, and statistical index-based evaluations. The novel classifier ensemble model indicates high prediction capability (AUC = 0.846) and relatively high accuracy (ACC = 78.77%). The study reveals that this model performs well in comparison to the other landslide models such as AdaBoost, Bagging, MultiBoost, and Random Forest. Overall, the novel classifier ensemble model is a promising method that could be used for landslide susceptibility assessment.

The main objective of this study is to investigate potential application of an integrated evidential belief function (EBF)-based fuzzy logic model for spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam). First, a landslide inventory map was constructed from various sources. Then the landslide inventory map was randomly partitioned as a ratio of 70/30 for training and validation of the models, respectively. Second, six landslide conditioning factors (slope angle, slope aspect, lithology, distance to faults, soil type, land use) were prepared and fuzzy membership values for these factors classes were estimated using the EBF. Subsequently, fuzzy operators were used to generate landslide susceptibility maps. Finally, the susceptibility maps were validated and compared using the validation dataset. The results show that the lowest prediction capability is the fuzzy SUM (76.6%). The prediction capability is almost the same for the fuzzy PRODUCT and fuzzy GAMMA models (79.6%). Compared to the frequency-ratio based fuzzy logic models, the EBF-based fuzzy logic models showed better result in both the success rate and prediction rate. The results from this study may be useful for local planner in areas prone to landslides. The modelling approach can be applied for other areas.

This study is an attempt to produce an assessment of the impact of shrimp aquaculture in the Mekong Delta (Viet Nam) on mangrove ecosystems. For this exercise we selected two sub-areas (Ca Mau and Tra Vinh provinces) encompassing a variety of land uses and ecological conditions. Twenty stations in Tra Vinh and 15 stations in Ca Mau have been surveyed several times from September 2000 to March 2002. Field investigations included mangrove soils studies, measurements of pH and salinity of the water, analysis of mangrove flora, and density and structure of the vegetation. Four Syst@me Probatoire de l'Observation de la Terre (SPOT) scenes were used for the discrimination of mangrove types and for the delineation of landscape units. For the first time, five ecologically distinct landscape classes were identified and delineated. Their possible links with the farming and yields of high valued species of shrimps, especially the giant tiger shrimp (Penaeus monodon) destined for export markets, need further studies. Since 1965, about 30% of mangrove ecosystems have been lost in Ca Mau Province and more than 30% of present mangroves are replanted monospecific stands. To the best of our knowledge, this is the first study which demonstrates that, in spite of deep and ancient man interactions in the Mekong Delta, five ecologically distinct classes of land use can be defined. Satellite surveys confirm a clear distribution of landscape units with possible links with shrimp aquaculture potentialities.

Leg 83 of the Deep Sea Drilling Project has deepened Hole 504B to over 1 km into basement, 1350 m below the seafloor (BSF). The hole previously extended through 274.5 m of sediment and 561.5 m of pillow basalts altered at low temperature (< 100C), to 836 m BSF. Leg 83 drilling penetrated an additional 10 m of pillows, a 209-m transition zone, and 295 m into a sheeted dike complex. Leg 83 basalts (836-1350 m BSF) generally contain superimposed greenschist and zeolite-facies mineral parageneses.

BACKGROUND: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam. OBJECTIVE: This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change. METHODS: Convolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997-2013 were used to train models, which were then evaluated using data from 2014-2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). RESULTS AND DISCUSSION: LSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features. CONCLUSION: This study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years.

Abstract We develop a new finite-difference scheme that reduces the number of grid points per wavelength required in frequency-domain elastic modeling. Our approach computes weighted averages of the spatial second-order derivative and the mass acceleration terms using a 25-point computational stencil. By determining the weighting coefficients to minimize numerical dispersion and numerical anisotropy, we reduce the number of grid points to 3.3 per shear wavelength, with a resulting error in velocities smaller than 1%. Our choice of grid points reduces the computer memory needed to store the complex impedance matrix to 4% of that for a conventional second-order scheme and to 54% of that for a combined second-order scheme. The 25-point weighted averaging scheme of this paper makes it possible to accurately simulate realistic models. Numerical examples show that this technique can achieve the same accurate solutions with fewer grid points than those from previous frequency-domain second-order schemes. Our technique can be extended directly to 3-D elastic modeling; the computational efficiency will be even greater than that realized for 2-D models.

This study presents the first water quality indexes developed to evaluate surface water in Vietnam. The basic water quality index (WQIB) can be effectively used to evaluate the spatial and temporal variations of surface water quality as well as to identify water pollutants. The overall water quality index (WQIO) can provide additional information, particularly on toxic substances contributing to water pollution. The water quality indexes developed for this paper were applied to the national surface-water quality monitoring data taken from 1999 to 2007. Water pollutants were classified into three subcategories: organic and nutrients, particulates, and bacteria. Surface water in northern and central Vietnam was poor in quality and contained organic matter, nutrients, and bacteria. Water in the southern part was mainly polluted by bacteria. Trend analysis results reveal a deterioration in water quality in those provinces under pressure from rapid population growth, urbanization, and industrialization. Vietnam has established an official policy to ensure comprehensive nationwide water quality monitoring by 2020. The implementation of water quality indexes may provide the guiding data for sustainable water-resources management in Vietnam.

Seahorses (Hippocampus spp) are heavily exploited in Vietnam, but conservation and management measures are currently limited by the ambiguous taxonomic definitions of the genus in the region. Seven species of seahorse are identified in this paper as inhabiting the coastal waters of Vietnam. We used morphometric and DNA sequence data (from the cytochrome b region of the mitochondrial genome) to delimit the species. Species descriptions are put forward and we provide illustrations and an identification key to the species. The species are provisionally assigned to Hippocampus spinosissimus Weber 1913, H. comes Cantor 1850, H. trimaculatus Leach 1814, H. kuda Bleeker 1852, H. kelbggi Jordan and Snyder 1902, H. mohnikei Bleeker 1854 and H. histrix Kaup 1856. The current level of confusion in seahorse nomenclature means that some of these distinct species in Vietnam (in particular H. spinosissimus, H. kuda, H. kelloggi and H. mohnikei) may have to be renamed once a comprehensive revision of the genus has been completed.

Continental extrusion may take up much of the deformation involved in continental collisions. Major strike-slip zones accommodate the relative extrusion displacement and transfer deformation away from the collision front. The Red River fault zone (RRFZ) accommodated left- and right-lateral displacements when Indochina and South China were extruded during the Indian-Eurasian collision. The northern Song Hong basin onshore and offshore in the Gulf of Tonkin delineates the direct extension of the RRFZ and thus records detailed information on the collision-induced continental extrusion. We assess the rapidly evolving kinematics of the fault zone buried within the basin based on seismic analysis. Contrary to previous studies, we do not identify indications for latest Miocene left-lateral motion across the RRFZ. We tentatively consider the shift from left- to right-lateral motion to have occurred already during the middle Late Miocene as indicated by inversion of NE-SW-striking faults in the Bach Long Vi area. Right-lateral displacement terminated around the end of the Miocene in the Song Hong basin. However, continued inversion in the Bach Long Vi area and NNW-SSE-striking normal faulting suggests a stress regime compatible with right-lateral motion across the onshore part of the RRFZ continuing to the present. Inversion around the Bach Long Vi Island may have accommodated up to a few kilometers of right-lateral displacement between the Indochina and South China blocks. Comparable NE-SW-striking fault zones onshore may have accommodated a larger fraction of the right-lateral slip across the RRFZ, thus accounting for the restricted transfer of lateral displacement to the offshore basins.

Spherical harmonic models of the 1969, 1979 and 1992 geomagnetic jerks are computed using data from about 160 worldwide geomagnetic observatories. The dominance of the internal origin part with respect to the external one confirms again the internal origin of these events. A change of sign is observed between two successive jerks (1969–1979, 1979–1992). The acceleration jump of the fluid flow at the core mantle boundary (CMB) generating the three jerks is computed. Striking similarities between the three acceleration maps are observed (within the sign change mentioned above). These results suggest some long time scale memory in the processes that are responsible for the jerks. These processes remain to be elucidated.

BACKGROUND: The Indo-Pacific region has the largest number of seagrass species worldwide and this region is considered as the origin of the Hydrocharitaceae. Halophila ovalis and its closely-related species belonging to the Hydrocharitaceae are well-known as a complex taxonomic challenge mainly due to their high morphological plasticity. The relationship of genetic differentiation and geographic barriers of H. ovalis radiation was not much studied in this region. Are there misidentifications between H. ovalis and its closely related species? Does any taxonomic uncertainty among different populations of H. ovalis persist? Is there any genetic differentiation among populations in the Western Pacific and the Eastern Indian Ocean, which are separated by the Thai-Malay peninsula? Genetic markers can be used to characterize and identify individuals or species and will be used to answer these questions. RESULTS: Phylogenetic analyses of the nuclear ribosomal internal transcribed spacer region based on materials collected from 17 populations in the Western Pacific and the Eastern Indian Ocean showed that some specimens identified as H. ovalis belonged to the H. major clade, also supported by morphological data. Evolutionary divergence between the two clades is between 0.033 and 0.038, much higher than the evolutionary divergence among H. ovalis populations. Eight haplotypes were found; none of the haplotypes from the Western Pacific is found in India and vice versa. Analysis of genetic diversity based on microsatellite analysis revealed that the genetic diversity in the Western Pacific is higher than in the Eastern Indian Ocean. The unrooted neighbor-joining tree among 14 populations from the Western Pacific and the Eastern Indian Ocean showed six groups. The Mantel test results revealed a significant correlation between genetic and geographic distances among populations. Results from band-based and allele frequency-based approaches from Amplified Fragment Length Polymorphism showed that all samples collected from both sides of the Thai-Malay peninsula were clustered into two clades: Gulf of Thailand and Andaman Sea. CONCLUSIONS: Our study documented the new records of H. major for Malaysia and Myanmar. The study also revealed that the Thai-Malay peninsula is a geographic barrier between H. ovalis populations in the Western Pacific and the Eastern Indian Ocean.

The nearly continuous recovery of 0.5 km of generally fresh, layer 3 gabbroic rocks at Hole 735B, especially near the bottom of the section, presents scientists an unusual opportunity to study the detailed elastic properties of the lower oceanic crust. Extending compressional-wave and density shipboard measurements at room pressure, V p and V s were measured at pressures from 20 to 200 MPa using the pulse transmission method. All of the rocks exhibit significant increases in velocity with increasing pressure up to about 150 MPa, a feature attributed to the closing of microcrack porosity. Measured velocities reflect the mineralogical makeup and microstructures acquired during the tectonic history of Hole 735B. Most of the undeformed and unaltered gabbros are approximately 65:35 plagioclase/ clinopyroxene rocks plus olivine or oxide minerals, and the observed densities and velocities are fully consistent with the Voigt-Reuss-Hill (VRH) averages of the component minerals and their proportions. Depending on their olivine content, the predominant olivine gabbros at 200 MPa have average V p = 7.1 0.2 km/s, V s = 3.9 0.1 km/s, and grain densities of 2.95 0.5 g/cm 3 . The less abundant iron-titanium (Fe-Ti) oxide gabbros average V p = 6.75 0.15 km/s, V s = 3.70 0.1 km/s, and grain densities of 3.22 0.05 g/cm 3 , reflecting the higher densities and lower velocities of oxide minerals compared to olivine. About 30% of the core is plastically deformed, and the densities and directionally averaged velocities of these shear-zone tectonites are generally consistent with those of the gabbros, their protoliths. Three sets of observations indicate that the shear-zone metagabbros are elastically anisotropic: (1) directional variations in V p , both vertical and horizontal and with respect to foliation and lineation;

Climate change induced sea-level rise (SLR) is on its increase globally. Regionally the lowlands of China, Vietnam, Bangladesh, and islands of the Malaysian, Indonesian and Philippine archipelagos are among the world’s most threatened regions. Sea-level rise has major impacts on the ecosystems and society. It threatens coastal populations, economic activities, and fragile ecosystems as mangroves, coastal salt-marches and wetlands. This paper provides a summary of the current state of knowledge of sea level-rise and its effects on both human and natural ecosystems. The focus is on coastal urban areas and low lying deltas in South-East Asia and Vietnam, as one of the most threatened areas in the world. About 3 mm per year reflects the growing consensus on the average SLR worldwide. The trend speeds up during recent decades. The figures are subject to local, temporal and methodological variation. In Vietnam the average values of 3.3 mm per year during the 1993-2014 period are above the worldwide average. Although a basic conceptual understanding exists that the increasing global frequency of the strongest tropical cyclones is related with the increasing temperature and SLR, this relationship is insufficiently understood. Moreover the precise, complex environmental, economic, social, and health impacts are currently unclear. SLR, storms and changing precipitation patterns increase flood risks, in particular in urban areas. Part of the current scientific debate is on how urban agglomeration can be made more resilient to flood risks. Where originally mainly technical interventions dominated this discussion, it becomes increasingly clear that proactive special planning, flood defense, flood risk mitigation, flood preparation, and flood recovery are important, but costly instruments. Next to the main focus on SLR and its effects on resilience, the paper reviews main SLR associated impacts: Floods and inundation, salinization, shoreline change, and effects on mangroves and wetlands. The hazards of SLR related floods increase fastest in urban areas. This is related with both the increasing surface major cities are expected to occupy during the decades to come and the increasing coastal population. In particular Asia and its megacities in the southern part of the continent are increasingly at risk. The discussion points to complexity, inter-disciplinarity, and the related uncertainty, as core characteristics. An integrated combination of mitigation, adaptation and resilience measures is currently considered as the most indicated way to resist SLR today and in the near future.References Aerts J.C.J.H., Hassan A., Savenije H.H.G., Khan M.F., 2000. Using GIS tools and rapid assessment techniques for determining salt intrusion: Stream a river basin management instrument. 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Landslide susceptibility mapping of the city of Da Lat, which is located in the landslide prone area of Lam Dong province of Central Vietnam region, was carried out using GIS based frequency ratio (FR) method. There are number of methods available but FR method is simple and widely used method for landslide susceptibility mapping. In the present study, eight topographical and geo-environmental landslide-conditioning factors were used including slope, elevation, land use, weathering crust, soil, lithology, distance to geology features, and stream density in conjunction with 70 past landslide locations. The results show that 6.27% of the area is in the very low susceptibility area, 21.03% in the low susceptibility area, 27.09% in the moderate susceptibility area and 27.41% of the area is in the high susceptibility zone and 18.21% in the very high susceptibility zone. The landslide susceptibility map produced in this study helps to assist decision makers in proper land use management and planning.