Effects of RapidEye imagery’s red-edge band and vegetation indices on land cover classification in an arid region

Land cover classification (LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidEye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidEye images’ red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement (3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions.     

Spatial structural pattern and vulnerability of China-Japan-Korea shipping network

The economies of China-Japan-Korea(CJK) are complementary, with their proximity resulting in the three countries having a high degree of interdependence with respect to trade. Currently, trade among these countries relies mainly on port-centered shipping. The development of the shipping network is integral for in-depth integration of CJK trade. This paper analyzes the overall characteristics, centrality, spatial structure, and vulnerability of the CJK shipping network using the methods of complex network analysis, blocking flow theory, and interruption and deletion of hub ports. The main findings are as follows: 1) The CJK shipping network has a small average path length and clustering coefficient, and its degree distribution follows a power-law distribution, which make the network present obvious characteristics of a Barabási-Albert scale-free. 2) The characteristics of the multi-center point of the CJK shipping network can alleviate traffic pressure. At the same time, the network shows a clear hierarchy in the port transportation system, with cargo transport relying mainly on the ‘hub port-hub port' connection. 3) The CJK shipping network is relatively stable. Compared with ports in Japan and Korea, the main hub ports in China have a greater impact on the stability of the shipping network, in particular those ports of the central coastal region, including Shanghai, Ningbo, and Lianyungang.     

Climate projections of spatial variations in coastal storm surges along the Gulf of Mexico and U.S. east coast

Using statistically downscaled atmospheric forcing, we performed a numerical investigation to evaluate future climate's impact on storm surges along the Gulf of Mexico and U.S. east coast. The focus is on the impact of climatic changes in wind pattern and surface pressure while neglecting sea level rise and other factors. We adapted the regional ocean model system(ROMS) to the study region with a mesh grid size of 7–10 km in horizontal and 18 vertical layers. The model was validated by a hindcast of the coastal sea levels in the winter of 2008. Model's robustness was confirmed by the good agreement between model-simulated and observed sea levels at 37 tidal gages. Two 10-year forecasts, one for the IPCC Pre-Industry(PI) and the other for the A1 FI scenario, were conducted. The differences in model-simulated surge heights under the two climate scenarios were analyzed. We identified three types of responses in extreme surge heights to future climate: a clear decrease in Middle Atlantic Bight, an increase in the western Gulf of Mexico, and non-significant response for the remaining area. Such spatial pattern is also consistent with previous projections of sea surface winds and ocean wave heights.     

Numerical simulation of bubble plumes and an analysis of their seismic attributes

To study the bubble plume’s seismic response characteristics, the model of a plume water body has been built in this article using the bubble-contained medium acoustic velocity model and the stochastic medium theory based on an analysis of both the acoustic characteristics of a bubble-contained water body and the actual features of a plume. The finite difference method is used for forward modelling, and the single-shot seismic record exhibits the characteristics of a scattered wave field generated by a plume. A meaningful conclusion is obtained by extracting seismic attributes from the pre-stack shot gather record of a plume. The values of the amplitude-related seismic attributes increase greatly as the bubble content goes up, and changes in bubble radius will not cause seismic attributes to change, which is primarily observed because the bubble content has a strong impact on the plume’s acoustic velocity, while the bubble radius has a weak impact on the acoustic velocity. The above conclusion provides a theoretical reference for identifying hydrate plumes using seismic methods and contributes to further study on hydrate decomposition and migration, as well as on distribution of the methane bubble in seawater.     

The influence of key environmental variables on phytoplankton community structure in the estuary of tidal rivers around Luoyuan Bay,China

A total of 348 species belonging to 8 phyla and 125 genera were observed in seasonally sampled phytoplankton of tidal rivers from 13 sampling sites around Luoyuan Bay, and all field samplings were carried out in productive period(March/June/August/December) at ebb tide. Bacillariophyta species were the most abundant species, followed by Chlorophyta, Cyanophytes, Euglenophyta, Cryptophyta, Dinophyta, Xanthophyta and Chrysophytas. Seasonal distribution index(SDI) value ranged from 0.63 to 0.86, which meant that species found at those sites in 4 seasons tended to be largely different. Phytoplankton individuals ranged from 5.939×10~4 ind L~(-1) in winter to 75.31×10~4 ind L~(-1) in autumn. Phytoplankton biomass ranged from 0.620 mg L~(-1) in summer to 2.373 mg L~(-1) in autumn. The grey correlation analysis(GCA) showed that the nutrient variables played an important role in the influence on phytoplankton community in every season. The canonical correspondence analysis(CCA) revealed impact of environmental variables on the different species, most of Bacillariophyta species were negative correlation with nutrients(TP and NH_3-N) in the four seasons, Chlorophyta species and Cyanophyta species did not show obvious correlation with environment variables in every season. The combination of GRA analysis and CCA analysis provided a method to quantitatively reveal the correlation between phytoplankton community and environmental variables in water body of tidal rivers at this region.     

Long-term statistics of extreme tsunami height at Crescent City

Historically, Crescent City is one of the most vulnerable communities impacted by tsunamis along the west coast of the United States, largely attributed to its offshore geography. Trans-ocean tsunamis usually produce large wave runup at Crescent Harbor resulting in catastrophic damages, property loss and human death. How to determine the return values of tsunami height using relatively short-term observation data is of great significance to assess the tsunami hazards and improve engineering design along the coast of Crescent City. In the present study, the extreme tsunami heights observed along the coast of Crescent City from 1938 to 2015 are fitted using six different probabilistic distributions, namely, the Gumbel distribution, the Weibull distribution, the maximum entropy distribution, the lognormal distribution, the generalized extreme value distribution and the generalized Pareto distribution. The maximum likelihood method is applied to estimate the parameters of all above distributions. Both Kolmogorov-Smirnov test and root mean square error method are utilized for goodness-of-fit test and the better fitting distribution is selected. Assuming that the occurrence frequency of tsunami in each year follows the Poisson distribution, the Poisson compound extreme value distribution can be used to fit the annual maximum tsunami amplitude, and then the point and interval estimations of return tsunami heights are calculated for structural design. The results show that the Poisson compound extreme value distribution fits tsunami heights very well and is suitable to determine the return tsunami heights for coastal disaster prevention.     

Spatial distribution of nitrate and related factors in the High Plains Aquifer,Texas

Utilizing geographic information systems (GIS) and statistics, objectives of this study were to evaluate: (a) the spatial distribution of nitrate concentrations in groundwater, and (b) associations between nitrate concentrations and: proximity to playa lakes, hydraulic conductivity of soil, well depth, and land use in the High Plains Aquifer, Texas. Data were compiled from wells sampled during 2000–2008. Nitrate concentrations in approximately 9% of wells exceeded the maximum contaminant level for drinking water. Concentrations were generally higher beneath urban and agricultural land, under permeable soil, and in shallow wells (especially in the southern part of the study area). However, concentrations were lower near playa lakes. While playas focus recharge to groundwater, denitrification in reducing environments lower nitrate concentrations beneath them. This study identifies areas vulnerable to nitrate contamination that warrant continued monitoring and mitigation efforts.     

Variations in soil properties and their effect on subsurface biomass distribution in four alpine meadows of the hinterland of the Tibetan Plateau of China

To understand and predict the role of soils in changes in alpine meadow ecosystems during climate warming, soil monoliths, extending from the surface to the deepest roots, were collected from Carex moorcroftii, Kobresia humilis, mixed grass, and Kobresia pygmaea alpine meadows in the hinterland of the Tibetan Plateau, China. The monoliths were used to measure the distribution with depth of biomass, soil grain size, soil nutrient levels, and soil moisture. With the exception of the K. pygmaea meadow, the percentages of gravel and coarse sand in the soils were high, ranging from 37.7 to 57.8% for gravel, and from 18.7 to 27.9% for coarse sand. The texture was finest in the upper 10 cm soil layer, and generally became coarser with increasing depth. Soil nutrients were concentrated in the top 15 cm soil layer, especially in the top 10 cm. Soil water content was low, ranging from 3 to 28.4%. Most of the subsurface biomass was in the top 10 cm, with concentrations of 79.8% in the K. humilis meadow, 77.6% in the mixed grass meadow, and 62.3% in the C. moorcroftii meadow. Owing to deeper root penetration, the concentration of subsurface biomass in the upper 10 cm of K. pygmaea soil was only 41.7%. The subsurface biomass content decreased exponentially with depth; this is attributed to the increase in grain size and decrease in soil nutrient levels with depth. Soil water is not a primary factor influencing the vertical and spatial distribution of subsurface biomass in the study area. The lack of fine material and of soil nutrients resulted in low surficial and subsurface biomass everywhere.     

Effect of protection against wind according to the variation porosity of wind fence

This study examines shelter effect against the wind by using wind fence with various porosities and distance. The shelter effect of wind fence was investigated by a wind tunnel test. Flow characteristics of velocities and turbulences behind wind fence were measured using a hot-wire anemometer. This was done by varying the porosity by 0, 20, and 40% of the wind fence. The wind fence distance ranged from 1H to 9H. In addition, the overall characterization of the wind fence was investigated by measuring a total of 28 points on the wind fence, which forms a lattice structure on it with 7 points in the lateral direction and 4 points in the vertical direction. The results indicate that the degree of the turbulence is lowered and the velocity of the wind is decreased when porosity of 40% is used at a distance of 4H–7H. The effectiveness of the wind fence depends on the porosity and distance. Porosity of 20% proved to be effective for the protection area of 1H–3H, while that of 40% was effective for the protection area of 4H–6H.     

Non-minimal coupling of the phantom field and cosmic acceleration

Motivated by the recent interest in phantom fields as candidates for the dark energy component, we investigate the consequences of the phantom field when is minimally coupled to gravity. In particular, the necessary (but insufficient) conditions for the acceleration and superacceleration of the universe are obtained when the non-minimal coupling term is taken into account. Furthermore, the necessary condition for the cosmic acceleration is derived when the phantom field is non-minimally coupled to gravity and baryonic matter is included.