禹门口南黄河东岸沙丘初步研究

在禹门口南山西省河津、万荣县境内黄河阶地上发育了一些固定、半固定沙丘,注入黄河的汾河将这些沙丘分成了南北两部分。北部的沙丘多在海拔400m左右,高出现代黄河约35m,位于黄河的第二级阶地上,由两条南北向的沙垄和两垄之间分布的抛物线形沙丘构成特殊的景观。这些抛物线形沙丘一般高度约7~8m,背风面突出,迎风坡坡度一般为15°~20°,背风坡坡度一般大于40°。风沙堆积下伏的河流堆积物的¹⁴C年龄为26.40±0.8kaBP,表明沙丘形成于距今26ka以来。南部沙丘海拔高度近500m,高出现代黄河水面150m,覆盖于黄河第三级阶地之上。一个天然剖面揭示,第三阶地的底部为黄色中粗砂与灰绿色粉砂粘土互层,中部为灰黄色黄土,顶部为黄色风沙层。在黄土地层中可以识别出S₁古土壤和位于风沙堆积下面的可能为L₁SS₁的弱成土层。由此推断风沙堆积于距今3万a以来。黄河阶地上的沙丘是在特殊的地区和特定的时期;强大的风力、丰富的沙源和气候变干条件下形成的。虽然东岸沙丘已是固定、半固定沙丘,但沙化仍然是该地区的一个问题。由于3~4a前开始在丘前洼地栽种苹果树,破坏了下风向沙丘迎风面的植被,造成了原来已固定沙丘的活化,在沙丘顶部生成了新的小抛物线形沙丘,高度大于1 m。沙丘上裸露的树根指示表土已被侵蚀0.3 m。南部沙丘区的风蚀作用也很强,例如,万荣县裴庄乡西范村北一片柿树林的树根由于风蚀已经裸露1.2 m。     

基于空间信息源的多尺度地形图智能化缩编体系研究与实践

各种比例尺地形图担负着不同的社会、经济职能,多尺度地形图生产和建库,是基础地理信息系统建设的重要内容,也是信息库建设的重点和难点。以往获得较小比例尺地形图成果,一是按照尺度划分规则分别测绘,二是采用制图综合软件逐级梯度缩编,无论哪种方法都存在着效率低、时间长、更新困难、质量因人而异的缺陷。研究采用新的技术方法,基于空间信息源的多尺度地形图智能化缩编,借助空间信息数据库的整体性、适应性、拓展性、算法先进性和超强分析能力,运用空间信息拓扑关系,建立基本比例尺图形数据库,在信息数据库中智能化完成梯级比例尺缩编、跨比例尺缩编及任意比例尺缩编,自动建立相应比例尺图形数据库,同时保障多尺度图形数据库及时更新和维护,克服传统方法测制与缩编各级比例尺地形图的弊端,保障系列比例尺地形图与基本比例尺图形数据库的一致性、实时性,满足各层次、各行业用图需求,方便快速建立城市DSM地表模型和空间真三维地理模型。该方法具有成本低、速度快、精度高、通用性强、按需供图的特点和优势。湘潭市数字城市工程实践证明:基于基础信息源数据进行地形图智能化缩编的体系、架构、理论和方法是可行的,且具有广泛的社会推广应用价值。     

Changes in the methodology used in the production of the Spanish CORINE: Uncertainty analysis of the new maps

Since 2012 CORINE has been obtained in Spain from the generalization of a more detailed land cover map (SIOSE). This methodological change has meant the production of a new CORINE map, which is different from the existing ones. To analyze how different the new maps are from the previous ones, as well as the advantages and disadvantages of the new methodology, we carried out a comparison of the CORINE obtained from both methods (traditional and generalization) for the year 2006. The new CORINE is more detailed and it is more coherent with the rest of Spanish Land Use Land Cover (LULC) maps. However, problems have been encountered with regard to the meaning of its classes, the fragmentation of patches and the complexity of its perimeters.     

特征点与骨架线约束的DEM简化

针对基于特征的地形简化方法不能很好的同时顾及特征点和骨架线的问题,提出了一种特征点与骨架线约束下的数字高程模型简化方法,在选取重要的地形特征点构建简化不规则三角网的同时,利用地形骨架线对简化过程中不规则三角网的生长实施约束。从等高线生成、高程精度、地形形态描述指标和地形骨架线保持程度4个方面,与广受关注的特征点方法、新近提出的复合方法进行对比。实验结果表明,本文提出的方法在各个方面均较显著地优于前两种方法,能够在地形简化过程中更全面、更大程度的保留初始地形的形态。     

Examining evidence for the Finite Pool of Worry and Finite Pool of Attention hypotheses

The Finite Pool of Worry (FPW) hypothesis states that humans have finite emotional resources for worry, so that when we become more worried about one threat, worry about other threats decreases. Despite its relevance, no conclusive empirical evidence for the hypothesis exists. We leverage the sudden onset of new worries introduced by the COVID-19 pandemic as a natural experiment to test the FPW hypothesis and a related hypothesis, the Finite Pool of Attention (FPA) hypothesis. The FPA hypothesis proposes that when we pay more attention to one threat, our attention to other threats decreases. To test these two hypotheses, we assessed self-reported attention, self-reported worries, and Twitter/news attention to various threats (climate change, terrorism, economic problems, and others) throughout the pandemic in three countries (USA, Italy, and China). We find that as attention to and worry about COVID-19 increases, attention to climate change decreases, but worry does not. Our results are confirmed by further analysis of a large, longitudinal U.S. sample. We find that public perceptions that COVID-19 and climate change are related do not fully explain the positive relationship in worry between the two hazards. In summary, our findings suggest that while there may be a Finite Pool of Attention to threats, there is limited evidence for a Finite Pool of Worry.     

可控式海底取样器的结构及工作原理--海底取样技术介绍之三

介绍了多种型号的冲击打入式和振动式海底取器的结构、工作原理和性能参数,并阐述了远距离空联样器、自动化联样器和水下微型取样器等３种回转式海底取样器的控制方式,结构形成和性能参数。     

基于深度学习的地震检测模型在区域台网的泛化性研究

将识别地震的深度学习算法PhaseNet应用于四川台网和首都圈台网,对该模型的泛化能力进行了测试和评估。首先利用2010年1月至2018年10月首都圈台网199个地震台站记录的29328个事件(M_L0～M_L4)所对应的126761段事件波形,以及2019年4—9月四川及邻省部分台网227个地震台站记录的16595个事件(M_L0～M_L6.0)所对应的120233段事件波形分别建立了SC和CA测试数据集,并用预训练好的PhaseNet模型进行P、 S震相自动识别和到时拾取,并将拾取结果与人工拾取结果在不同误差阈值下进行对比。测试结果表明, PhaseNet在两个数据集上具有良好的震相检测能力(误差阈值为0.5 s),其P、 S震相检测的F₁值都超过0.75,具有比较稳定的准确拾取P波到时能力(误差阈值0.1 s),其检测F₁值均超过0.6,而S波到时拾取的F₁值分别为0.33(SC)和0.53(CA)。进一步分析了测试结果与震中距、震级、...     

Aggregation of LoD 1 building models as an optimization problem

3D city models offered by digital map providers typically consist of several thousands or even millions of individual buildings. Those buildings are usually generated in an automated fashion from high resolution cadastral and remote sensing data and can be very detailed. However, not in every application such a high degree of detail is desirable. One way to remove complexity is to aggregate individual buildings, simplify the ground plan and assign an appropriate average building height. This task is computationally complex because it includes the combinatorial optimization problem of determining which subset of the original set of buildings should best be aggregated to meet the demands of an application.In this article, we introduce approaches to express different aspects of the aggregation of LoD 1 building models in the form of Mixed Integer Programming (MIP) problems. The advantage of this approach is that for linear (and some quadratic) MIP problems, sophisticated software exists to find exact solutions (global optima) with reasonable effort. We also propose two different heuristic approaches based on the region growing strategy and evaluate their potential for optimization by comparing their performance to a MIP-based approach.     

Purification and photodynamic bioactivity of phycoerythrin and phycocyanin from Porphyra yezoensis Ueda

Phycoerythrin and phycocyanin were purified from Porphyra yezoensis Ueda with their bioactivity determined in this study. Continuous precipitation with ammonium sulfate at different concentrations （10%, 20%, 40%and 50%） increased the purity （A564：A280） of phycoerythrin to 1.49, 3.92 fold of the raw extract （0.38） and the purity （A615：A280） of phycocyanin to 0.70, 3.33 fold of the raw extract （0.21）. Two more times of chromatography with hydroxylapatites finally made the purity of phycoerythrin and phy-cocyanin reach 5.50, 14.47 fold of the raw extract, and 5.10, 24.29 fold of the raw extract, respectviely. The yield of high purity phycoerythrin and phycocyanin were 0.21%and 0.09%of dried P. yezoensis blade, respectively. The photodynamic cytotoxic ex-periment showed that both phycoerythrin and phycocyanin inhibited the growth of liver tumor cells significantly. It was found that 250 mg L-1 purified phycoerythrin and phycocyanin inhibited the growth of hepatocellular carcinoma cells 24 h after laser-irradiation by 80%and 59%, respectively, and 100 mg L-1 purified phycoerythrin and phycocyanin induced the apoptosis of 31.54%and 32.54%of the cells, respectively, 8 h after photodynamic therapy. Oue findings demonstrated that P. yezoensis can serve as photosensitizer （phycoerythrin and phycocyanin） producer.     

Automatic representation and reconstruction of DBM from LiDAR data using Recursive Minimum Bounding Rectangle

Three-dimensional building models are important for various applications, such as disaster management and urban planning. The development of laser scanning sensor technologies has resulted in many different approaches for efficient building model generation using LiDAR data. Despite this effort, generation of these models lacks economical and reliable techniques that fully exploit the advantage of LiDAR data. Therefore, this research aims to develop a framework for fully-automated building model generation by integrating data-driven and model-driven methods using LiDAR datasets.The building model generation starts by employing LiDAR data for building detection and approximate boundary determination. The generated building boundaries are then integrated into a model-based processing strategy because LiDAR derived planes show irregular boundaries due to the nature of LiDAR point acquisition. The focus of the research is generating models for the buildings with right-angled-corners, which can be described with a collection of rectangles under the assumption that the majority of the buildings in urban areas belong to this category. Therefore, by applying the Minimum Bounding Rectangle (MBR) algorithm recursively, the LiDAR boundaries are decomposed into sets of rectangles for further processing. At the same time, the quality of the MBRs is examined to verify that the buildings, from which the boundaries are generated, are buildings with right-angled-corners. The parameters that define the model primitives are adjusted through a model-based boundary fitting procedure using LiDAR boundaries. The level of details in the final Digital Building Model is based on the number of recursions during the MBR processing, which in turn are determined by the LiDAR point density. The model-based boundary fitting improves the quality of the generated boundaries and as seen in experimental results, the quality depends on the average LiDAR point spacing. This research thus develops an approach which not only automates the building model generation, but also achieves the best accuracy of the model while utilizing only LiDAR data.