基于HJ卫星混合像元分解法的湖北省四湖地区夏收作物种植信息提取

混合像元是造成中低空间分辨率遥感数据计算机解译不准确的主要原因，通过收集2013年四湖地区夏收作物生长期内的不用生育时期的三景HJ卫星CCD数据，生成一个15波段的“类高光谱”数据；在采用阀门技术结合夏收作物NDVI指数变化特点，提取所有夏收作物（小麦与油菜）在四湖地区的空间分布的基础上，成功运用改进的逐步回归法计算出小麦与油菜在混合像元中的丰度值，高精度地取得了四湖地区小麦、油菜种植区的空间分布；将部分结果与同期资源三号卫星融合数据作为标准进行比较，证明基于改进的逐步回归法计算混合像元的丰度值是比较准确的，为运用HJ卫星CCD数据高精度提取农作物种植信息提供了一种可行的方法     

Effective cleanup of oil contamination on bio-inspired superhydrophobic surface

Environmental Science and Pollution Research - The oil-water separation is a popular issue and the removal of oil from bulk water is also meaningful especially in oil spill incident, which not only...     

Comparison of different sequential extraction procedures for mercury fractionation in polluted soils

Environmental Science and Pollution Research - Three sequential extraction procedures (SEPs), modified Tessier, modified BCR, and CIEMAT, were compared for mercury fractionation in polluted soils....     

基于改进粒子群算法和元胞自动机的城市扩张模拟——以南京为例

为合理利用多智能体算法解决城市扩张动态模拟问题,基于地理学理论和社会学规律对粒子群算法进行有针对性的改进,提出分段式粒子群算法(SPSO),并结合元胞自动机模拟复杂时空过程的能力,构建出适用于城市扩张模拟的地理元胞自动机SPSO-CA。在SPSO-CA中我们利用多时像的土地利用数据、交通路网数据和地形数据,挖掘出1995~2000年南京城市扩张的土地转换规则。再由此规则实现1995~2008年的南京市城市扩张过程的动态模拟。最后对比SPSO-CA、PSOCA及NULL模型结果得:SPSO-CA总精度86.3%,Kappa系数为0.792,Moran’s I为0.078,PSO-CA总精度83.6%,Kappa系数为0.755,Moran’s I为0.054,NULL模型总精度81.9%,Kappa系数为0.741,真实的Moran’s I为0.072。这表明无论是总精度还是空间一致性,SPSO-CA都优于PSO-CA和NULL模型,即用SPSO-CA模拟城市扩张是可行的。     

Quality assessment of groundwater from the south-eastern Arabian Peninsula

Assessment of groundwater quality plays a significant role in the utilization of the scarce water resources globally and especially in arid regions. The increasing abstraction together with man-made contamination and seawater intrusion have strongly affected groundwater quality in the Arabia Peninsula, exemplified by the investigation given here from the United Arab Emirates, where the groundwater is seldom reviewed and assessed. In the aim of assessing current groundwater quality, we here present a comparison of chemical data linked to aquifers types. The results reveal that most of the investigated groundwater is not suitable for drinking, household, and agricultural purposes following the WHO permissible limits. Aquifer composition and climate have vital control on the water quality, with the carbonate aquifers contain the least potable water compared to the ophiolites and Quaternary clastics. Seawater intrusion along coastal regions has deteriorated the water quality and the phenomenon may become more intensive with future warming climate and rising sea level.     

Accumulation of Cd,Cu and Zn in shoots of maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.) exposed to 0.8 or 20 nM Cd during vegetative growth and the relation with xylem sap composition

This work focuses on the exposure of maize plants to nanomolar concentrations of Cd, which is relevant for agricultural soils cropped with food and feed plants. Maize plants were cultivated in nutrient solution at 0.8 or 20 nM Cd during the vegetative growth stages. No significant hormesis or toxic effects of Cd were observed on maize growth, but a decrease in the allocation of Cd to shoots between the 0.8 and 20 nM Cd exposures revealed that the plants already responded to these low concentrations of Cd according to a shoot Cd excluder strategy. The Cd, Cu and Zn concentrations in shoots decreased with time as the result of an early decrease in the root/shoot ratio and of a decrease in the coefficient of allocation to aboveground for Zn and Cd at 20 nM. As a consequence, shoots of young plants were richer in micronutrients Cu and Zn but also in toxic Cd. The rate of delivery of Cd, Cu and Zn from xylem sap was successfully used to predict the time course of concentrations of Cd, Cu and Zn in the shoot. However, it overestimated the actual concentrations of Cd in the shoot, presumably because the reallocation of this trace element from shoots back to roots was not taken into account.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.     

High crosslinked sodium carboxyl methylstarch-g-poly (acrylic acid-co-acrylamide) resin for heavy metal adsorption: its characteristics and mechanisms

Environmental Science and Pollution Research - A lower expansive heavy metal adsorbent, high crosslinked sodium carboxyl methylstarch-g-poly (acrylic acid-co-acrylamide) resin (HCAA), has been...