A-FPN算法及其在遥感图像船舶检测中的应用

光学遥感图像船舶检测主要面临两个挑战:光学遥感图像背景复杂,船舶检测易受海浪、云雾及陆地建筑等多方面干扰;遥感图像分辨率低,船舶目标小,对于其分类与定位带来很大困难;针对上述问题,在FPN的基础上,提出一种融入显著性特征的卷积神经网络模型A-FPN (Attention-Based Feature Pyramid Networks)。首先,利用卷积提取图像特征金字塔;然后,利用顶层金字塔逐级构建显著特征层,抑制背景信息,通过金字塔顶层的细粒度特征提高浅层特征的表达能力,构建自上而下的多级显著特征映射结构;最后利用Softmax分类器进行多层级船舶检测。A-FPN模型利用显著性机制引导不同感受下的特征进行融合,提高了模型的分辨能力,对遥感图像处理领域具有重要应用价值。实验阶段,利用公开的遥感目标检测数据集NWPU VHR-10中的船舶样本进行测试,准确率为92.8%,表明A-FPN模型适用于遥感图像船舶检测。     

Retrieving volume FeO and TiO_2 abundances of lunar regolith with CE-2 CELMS data using BPNN method

The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs are retrieved with microwave sounder(CELMS) data from the Chang'E-2 satellite using the back propagation neural network(BPNN) method. Firstly, a three-layered BPNN network with five-dimensional input is constructed by taking nonlinearity into account. Then, the brightness temperature(TB) and surface slope are set as the inputs and the volume FTAs are set as the outputs of the BPNN network.Thereafter, the BPNN network is trained with the corresponding parameters collected from Apollo, Luna,and Surveyor missions. Finally, the volume FTAs are retrieved with the trained BPNN network using the four-channel TBderived from the CELMS data and the surface slope estimated from Lunar Orbiter Laser Altimeter(LOLA) data. The rationality of the retrieved FTAs is verified by comparing with the Clementine UV-VIS results and Lunar Prospector(LP) GRS results. The retrieved volume FTAs enable us to re-evaluate the geological features of the lunar surface. Several important results are as follows. Firstly, very-low-Ti(1.5 wt.%) basalts are the most spatially abundant, and the surfaces with TiO_2 5 wt.% constitute less than 10% of the maria. Also, two linear relationships occur between the FeO abundance(FA) and the TiO_2 abundance before and after the threshold, 16 wt.% for FA. Secondly, a new perspective on mare volcanism is derived with the volume FTAs in several important mare basins, although this conclusion should be verified with more sources of data. Thirdly, FTAs in the lunar regolith change with depth to the uppermost surface,and the change is complex over the lunar surface. Finally, the distribution of volume FTAs hints that the highlands crust is probably homogeneous, at least in terms of the microwave thermophysical parameters.     

A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements

Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.     

Implementation of a coupled plastic damage distinct lattice spring model for dynamic crack propagation in geomaterials

This paper studies dynamic crack propagation by employing the distinct lattice spring model (DLSM) and 3‐dimensional (3D) printing technique. A damage‐plasticity model was developed and implemented in a 2D DLSM. Applicability of the damage‐plasticity DLSM was verified against analytical elastic solutions and experimental results for crack propagation. As a physical analogy, dynamic fracturing tests were conducted on 3D printed specimens using the split Hopkinson pressure bar. The dynamic stress intensity factors were recorded, and crack paths were captured by a high‐speed camera. A parametric study was conducted to find the influences of the parameters on cracking behaviors, including initial and peak fracture toughness, crack speed, and crack patterns. Finally, selection of parameters for the damage‐plasticity model was determined through the comparison of numerical predictions and the experimentally observed cracking features.     

Predictability of Chinese Summer Extreme Rainfall Based on Arctic Sea Ice and Tropical Sea Surface Temperature

Chinese summer extreme rainfall often brings huge economic losses, so the prediction of summer extreme rainfall is necessary. This study focuses on the predictability of the leading mode of Chinese summer extreme rainfall from empirical orthogonal function(EOF) analysis. The predictors used in this study are Arctic sea ice concentration(ASIC) and regional sea surface temperature(SST) in selected optimal time periods. The most important role that Arctic sea ice(ASI) plays in the appearance of EOF1 may be strengthening the high pressure over North China, thereby preventing water vapor from going north. The contribution of SST is mainly at low latitudes and characterized by a significant cyclone anomaly over South China. The forecast models using predictor ASIC(PA), SST(PS), and the two together(PAS) are established by using data from 1980 to 2004. An independent forecast is made for the last 11 years(2005-2015). The correlation coefficient(COR) skills between the observed and cross-validation reforecast principal components(PC) of the PA, PS, and PAS models are 0.47, 0.66, and 0.76, respectively. These values indicate that SST is a major cause of Chinese summer extreme rainfall during 1980-2004. The COR skill of the PA model during the independent forecast period of 2004-2015 is 0.7, which is significantly higher than those of the PS and PAS models. Thus, the main factor influencing Chinese summer extreme rainfall in recent years has changed from low latitudes to high latitudes. The impact of ASI on Chinese summer extreme rainfall is becoming increasingly significant.     

Fast adsorption of microcystin-LR by Fe(III)-modified powdered activated carbon

Journal of Oceanology and Limnology - Microcystins (MCs) are cyclic hepatotoxic peptides produced by the bloom-forming cyanobacterium Microcystis and present a public health hazard to humans and...     

Assessment of alternative adsorption models and global sensitivity analysis to characterize hexavalent chromium loss from soil to surface runoff

We investigate our ability to assess transfer of hexavalent chromium, Cr(VI), from the soil to surface runoff by considering the effect of coupling diverse adsorption models with a two‐layer solute transfer model. Our analyses are grounded on a set of two experiments associated with soils characterized by diverse particle size distributions. Our study is motivated by the observation that Cr(VI) is receiving much attention for the assessment of environmental risks due to its high solubility, mobility, and toxicological significance. Adsorption of Cr(VI) is considered to be at equilibrium in the mixing layer under our experimental conditions. Four adsorption models, that is, the Langmuir, Freundlich, Temkin, and linear models, constitute our set of alternative (competing) mathematical formulations. Experimental results reveal that the soil samples characterized by the finest grain sizes are associated with the highest release of Cr(VI) to runoff. We compare the relative abilities of the four models to interpret experimental results through maximum likelihood model calibration and four model identification criteria (i.e., the Akaike information criteria [AIC and AIC_C] and the Bayesian and Kashyap information criteria). Our study results enable us to rank the tested models on the basis of a set of posterior weights assigned to each of them. A classical variance‐based global sensitivity analysis is then performed to assess the relative importance of the uncertain parameters associated with each of the models considered, within subregions of the parameter space. In this context, the modelling strategy resulting from coupling the Langmuir isotherm with a two‐layer solute transfer model is then evaluated as the most skilful for the overall interpretation of both sets of experiments. Our results document that (a) the depth of the mixing layer is the most influential factor for all models tested, with the exception of the Freundlich isotherm, and (b) the total sensitivity of the adsorption parameters varies in time, with a trend to increase as time progresses for all of the models. These results suggest that adsorption has a significant effect on the uncertainty associated with the release of Cr(VI) from the soil to the surface runoff component.     

Area usage estimation and spatiotemporal variability in distribution patterns of southern right whales,Eubalaena australis,of southern Brazil

Southern right whales—Eubalaena australis (Desmoulins, 1822)—migrate seasonally from high‐latitude feeding grounds to coastal breeding and calving grounds at lower latitudes such as the southern coast of Brazil. Understanding how these whales are distributed along the coast is important for monitoring their postwhaling recovery and defining management strategies. In this study, we applied Kernel density estimators to aerial survey data to determine main occurrence and concentration areas of right whales in southern Brazil and investigate inter‐ and intra‐annual distribution patterns between 2003 and 2012. Our results show considerable variation in area usage within and among years, and changes in the general distribution pattern of right whales in the last years of the study. Intra‐annually, higher concentration area tended to expand from July to September and decrease in November. Some areas stood out as high‐density areas for right whales: Ribanceira/Ibiraquera, Itapirubá Sul/Sol, and from Arroio to Gaivota. Some evidences also suggest preferential areas for mother–calf pairs. The higher concentration area of right whales in southern Brazil was estimated at 52,541 km² and the occurrence area was 682.69 km², which is the whole study area. As right whale distribution in the region is likely expanding due to this population's current recovery, our study provides essential information for management plan of the Right Whale Environmental Protection Area.     

浙南近海虾类群落结构及其多样性分析

作者根据2015年11月(秋季)、2016年2月(冬季)、2016年5月(春季)和2016年8月(夏季)对浙南近海进行的渔业资源调查数据,用生物量作为虾类资源分布的数量指标,对该海域虾类的组成、数量分布以及季节变化进行分析。结果显示:该区域共鉴定出虾类30种,隶属于10科21属,以对虾科(Penaeidae)虾类最多,其次为管鞭虾科(Solenoceridae),长臂虾科(Palaemonida)位居第3位。按季节来看,秋季共鉴定虾类27种,各站位平均生物量为6.97 kg/km2,优势种为凹陷管鞭虾(Solenocera koelbeli)、中国毛虾(Acetes chinensis)和中华管鞭虾(Solenocera crassicornis)等3种;冬季鉴定出虾类25种,平均生物量为1.65 kg/km2,优势种为凹陷管鞭虾、扁足异对虾(Atypopenaeus stenodactylus)、日本鼓虾(Alpheus japonicus)、鲜明鼓虾(Alpheus digitalis)、中国毛虾、中华管鞭虾和周氏新对虾(Metapenaeus joyneri)等7种;春季20种,平均生物量为2.22 kg/km2,优势种为戴氏赤虾(Metapenaeopsis dalei)、东海红虾(Metapenaeopsis dalei)和中华管鞭虾等3种;夏季16种,平均生物量为10.36 kg/km2,优势种有鹰爪虾(Trachysalambria curvirostris)和中华管鞭虾等2种。Margalef丰富度指数(D)、Shannon-Wiener多样性指数(H′)和Pielou均匀度指数(J′)秋季均低于冬季。秋冬季受到浙闽沿岸流影响,温度、盐度相对较低,夏季受到台湾暖流外侧影响,温度、盐度相对较高,且各季节间由于瓯江、椒江、飞云江、鳌江等陆源性冲淡水的影响,盐度、温度变化相对较大,使得该区域的物种不得不适应一个跨度较大的温盐范围,广温广盐性种类为主。