我国七、八月等压面位势高度准两周振荡特点及其与夏季风强度和北方降水的关系

本文用功率谱分析和频带滤波等方法对1981年7、8月我国46个高空观测站的08h 850hPa到200hPa等压面的位势高度进行了分析,指出了等压面位势高度准两周振荡强度、垂直结构和移动特点,以及它与夏季风强度和北方地区降水的关系。     

基于正交多项式的平原城区机载LiDAR数据滤波算法

从机载LiDAR点云数据中分离地面点与非地面点生成城区DEM,是构建数字城市的首要工作。该文对机载LiDAR数据处理中的滤波关键算法进行了研究。首先,利用常用的区域增长方法对机载LiDAR点云数据进行了滤波处理,然后基于正交多项式分带滤波方法进行了点云滤波,比较了两种算法的运行效率,分析了二者的特点,并通过试验对比进行了阈值参数优选,试验表明该算法具有较好的滤波效果,在平原城区的数字城市三维建模中具有很好的应用价值。     

核桃壳滤料的油田水处理应用

本文从核桃壳性能出发,总结其在油田水处理中的应用,重点阐述了核桃壳作为滤料在过滤罐中的利用以及过滤罐的相关改造。旨在提高核桃壳作为滤料在油田中的利用率,改善油田水处理的效果。     

中国省际人口迁移短期预测分析

人口迁移是一个时空路径依赖过程,同时受迁移存量和周边迁移状况影响。当前人口迁移预测大多建立在时间序列模型之上,重点考虑迁移流在时间维度上的联系,忽视了其中的时空关联。该文将特征向量时空滤波方法与普通泊松模型相结合,考虑迁移流中可能存在的时空滞后和同期两种结构,对1985-2015年不同时段的中国省际人口迁移流数据进行建模和估计,并利用拟合程度较优的模型预测2015-2025年省际人口迁移的发展趋势。结果表明:1)特征向量时空滞后和同期滤波泊松模型均能较好地模拟研究时段省际人口迁移过程,自1985年以来我国省际人口迁移流不仅受迁出地和迁入地经济、社会等因素影响,也与过去迁移存量及周边迁移流密切相关;2)区域人口规模和GDP对迁移流的“推—拉”作用符合预期,地区人口规模较高和经济发展水平较低会促进人口外迁,反之则有利于吸引外来人口;3)与特征向量时空滞后滤波泊松模型相比,时空同期模型更便于捕捉省际人口迁移过程中的时空路径依赖特性,意味着当前人口迁移流的发展更易受到同时期周边迁移流的影响,表现出明显的羊群效应;4)预计2015-2025年我国省际迁移总量持续增加,呈现更集聚的空间模式,高迁入与高迁出区域在空间上相连,形成一条南北贯通的“高密度迁移地带”。将特征向量时空滤波模型拓展到人口迁移这一空间相互作用领域,可为当前构建更加完善的要素市场化配置体制机制等提供科学参考。     

基于机载激光点云数据的电力线自动提取算法

设计并开发了一种从机载激光扫描的三维点云数据中自动提取电力线的算法,采用局部高程分布直方图模式分类滤波、Hough特征空间中全局方向特征优先的线特征提取、悬挂点位置数学推算和局部分段多项式拟合的方法,有效解决了电力线提取过程中电力线点云与电塔点云的自动分类、电力线平面位置提取、电力线悬挂点提取、电力线拟合问题。最后通过实际的工程数据验证了该算法的实用性。     

城市湿地公园人工过滤系统的构建——以长广溪湿地公园为例

城市化进程的加快,大面积不透水铺装的应用,导致城市水环境受到严重冲击,降雨径流成为水体恶化的主要污染源。湿地公园作为城市景观生态规划的绿色网络构建设施之一,能够提高城市透水面积,引入控制降雨径流的BMPs设施,消减城市非点源污染物,保护河流、湖泊等城市敏感区域。重点介绍了长广溪湿地公园的建设中,融入的4种水质过滤净水系统的设计和施工,包括沉淀过滤系统、平行过滤系统、生物过滤系统和重力过滤系统等。长广溪湿地有效地降低了流入长广溪的悬浮物(SS)和COD负荷,发挥了湿地公园净化过滤水体的功能的同时,营造景观多样性,改善长广溪生态环境。     

基于卡尔曼滤波算法的焦炭价格预测

焦炭价格预测研究具有重要的理论和实践意义,本文利用卡尔曼滤波算法对焦炭价格进行预测研究。建立状态空间模型时,选取焦炭价格作为唯一的状态变量,通过每一时刻变量观测值与预测值形成的新息,不断更新和迭代,以寻求最优估测值。实证分析表明,该算法对焦炭价格的跟踪和预测效果较好。     

Structural Analysis for Gold Mineralization Using Remote Sensing and Geochemical Techniques in a GIS Environment: Island of Lesvos,Hellas

Exploration for epithermal Au has been active lately in the Aegean Sea of the eastern Mediterranean Basin, both in the islands of the Quaternary arc and in those of the back-arc region. The purpose of this study was the structural mapping and analysis for a preliminary investigation of possible epithermal gold mineralization, using remotely sensed data and techniques, structural and field data, and geochemical information, for a specific area on the Island of Lesvos. Therefore, Landsat-TM and SPOT-Pan satellite images and the Digital Elevation Model (DEM) of the study area were processed digitally using spatial filtering techniques for the enhancement and recognition of the geologically significant lineaments, as well as algebraic operations with band ratios and Principal Component Analysis (PCA), for the identification of alteration zones. Statistical rose diagrams and a SCHMIDT projection Stereo Net were generated from the lineament maps and the collected field data (dip and strike measurements of faults, joints, and veins), respectively. The derived lineament map and the band ratio images were manipulated in a GIS environment, in order to study the relation of the tectonic pattern to both the alteration zoning and the geomorphology of the volcanic field of the study area. Target areas of high interest for possible mineralization also were specified using geochemical techniques, such as X-Ray Diffraction (XRD) analysis, trace-element, and fluid-inclusion analysis. Finally, preliminary conclusions were derived about possible mineralization, the type (high or low sulfidation), and the extent of mineralization, by combining the structural information with geochemical information.     

基于混合过滤的地学数据个性化推荐方法设计与实现

推荐系统是帮助互联网用户克服信息过剩的有效工具。在地学数据共享领域,较其他物品的内容属性,地学数据具有更加丰富的时空属性,这也给地学数据推荐带来挑战。针对地学数据的特点,为地学数据共享推荐服务开发了一种动态加权的混合过滤方法。该方法分别采用协同过滤和基于内容过滤算法预测用户对数据的兴趣度,再以训练模型计算最优加权权重,计算最终预测评分。在数据获取阶段,通过用户访问日志数据,采用Jenks Natural Break算法分析用户访问记录获取用户的数据兴趣度。在基于内容过滤部分,通过数据的空间、时间及内容属性计算数据相似度,并以用户历史行为为依据计算用户兴趣。在协同过滤和基于内容过滤中分别采用k-NN算法计算用户对未访问数据的预测评分,并进行加权求和。通过训练集,对理想权重值及用户的共同评价度（co-rating level）进行建模,拟合二者的关系。该模型被应用于混合过滤的权重调整,以获得最优的加权方程。测试结果显示,结合数据时空属性的混合过滤方法的准确度和召回率,较单一的协同过滤或基于内容过滤方法有显著提高。     

Combining airborne and terrestrial laser scanning for quantifying erosion and deposition by a debris flow event

We quantified the sediment volume transported by a major debris flow event in the Halltal, Austrian Alps, using a combination of terrestrial (TLS) and airborne laser scanning (ALS) which has rarely been carried out before. A digital terrain model (DTM) derived from ALS data (pre-event surface) was combined with a DTM derived from TLS data (post-event surface). Both datasets were aligned and compared in a cut and fill analysis estimating differential volumes.The main focus lay on the evaluation and accuracy assessment of the applied method. Tie-point based registration of both datasets proved to be insufficient; additional alignment by Multi Station Adjustment was necessary to minimise the averaged height error between both datasets, amounting for a volumetric error of less than 10% which is comparable to pure ALS-campaigns. Larger errors were estimated for complex terrain with low scanning resolutions. A particular problem in data processing was the low and dense shrub vegetation in the study area which required a specifically adapted filter algorithm. An insufficient ground representation was observed for the ALS-data overestimating ground heights for averaged 70 cm. Despite these limitations, the approach proved to be suitable for accurate extreme event quantification.The starting zones of the debris flows lie at the bedrock-debris interface where runoff is concentrated. Volumes of 5000 to 12,000 m³ were assessed. Volume estimation worked better for the erosional than for the depositional features; this is because the erosional gullies are relatively deep and the calculation is not affected by pre-event vegetation. While erosion and sedimentation are balanced for one of the three catchments investigated, the deposited volumes are higher than the detected eroded volumes for the other two. The reasons are not fully understood. The magnitude of the flows was determined by catchment size, topographical characteristics and deforestation by a major wildfire in 1946.     

中国省际流动人口户籍迁移意愿的空间格局及影响机制分析

构建中国省际流动人口户籍迁移网络,运用探索性空间分析及空间滤波等方法分析该网络的空间格局和驱动力。主要发现：① 户籍迁移意愿网络呈现出集聚的空间格局,排序较高的户籍迁移意愿流主要从欠发达地区指向发达地区。② 户籍吸引力及户籍流出分别呈现出随机及集聚的空间格局,户籍流出热点区为西部及东北地区,冷点区为中东部地区。③ 迁入地人口、FDI、迁入地及迁出地人均GDP、平均工资等因素均显著影响户籍迁移意愿。流动人口个体、家庭因素、住房条件及迁移原因等同样与户籍迁移意愿的关系紧密。     

A fast candidate viewpoints filtering algorithm for multiple viewshed site planning

ABSTRACT

The aim of site planning based on multiple viewshed analysis is to select the minimum number of viewpoints that maximize visual coverage over a given terrain. However, increasingly high-resolution terrain data means that the number of terrain points will increase rapidly, which will lead to rapid increases in computational requirements for multiple viewshed site planning. In this article, we propose a fast Candidate Viewpoints Filtering (CVF) algorithm for multiple viewshed site planning to lay a foundation for viewpoint optimization selection. Firstly, terrain feature points are selected as candidate viewpoints. Then, these candidate viewpoints are clustered and those belonging to each cluster are sorted according to the index of viewshed contribution (IVC). Finally, the candidate viewpoints with relatively low viewshed contribution rate are removed gradually using the CVF algorithm, through which, the viewpoints with high viewshed contribution are preserved and the number of viewpoints to be preserved can be controlled by the number of clusters. To evaluate the effectiveness of our CVF algorithm, we compare it with the Region Partitioning for Filtering (RPF) and Simulated Annealing (SA) algorithms. Experimental results show that our CVF algorithm is a substantial improvement in both computational efficiency and total viewshed coverage rate.     

Implementing Moran eigenvector spatial filtering for massively large georeferenced datasets

Moran eigenvector spatial filtering (MESF) furnishes an alternative method to account for spatial autocorrelation in linear regression specifications describing georeferenced data, although spatial auto-models also are widely used. The utility of this MESF methodology is even more impressive for the non-Gaussian models because its flexible structure enables it to be easily applied to generalized linear models, which include Poisson, binomial, and negative binomial regression. However, the implementation of MESF can be computationally challenging, especially when the number of geographic units, n, is large, or massive, such as with a remotely sensed image. This intensive computation aspect has been a drawback to the use of MESF, particularly for analyzing a remotely sensed image, which can easily contain millions of pixels. Motivated by Curry, this paper proposes an approximation approach to constructing eigenvector spatial filters (ESFs) for a large spatial tessellation. This approximation is based on a divide-and-conquer approach. That is, it constructs ESFs separately for each sub-region, and then combines the resulting ESFs across an entire remotely sensed image. This paper, employing selected specimen remotely sensed images, demonstrates that the proposed technique provides a computationally efficient and successful approach to implement MESF for large or massive spatial tessellations.     

重大事故影响下的工人社区衰退机制与韧性——基于过滤理论的分析

本研究基于社区衰退的过滤理论,建立重大事故影响下的社区衰退过滤机制概念模型,以南京市N社区为例,运用问卷调查、访谈、文本分析以及结构方程模型等方法,证明了社区衰退与过滤之间存在的自我强化以及相互强化的螺旋式反馈作用。内部机制上,社区衰退、邻里过滤既是环境感知的原因,又是行动决策的结果,满意度、忠诚度在环境感知和行动决策之间起中介作用;风险感知越强烈,社区依恋越低,迁居意愿更强,重大事故经历加深了事故背景内化程度。外部机制上,社区衰退与邻里过滤建立在低收入群体与住房市场变化的基础之上;重大事故对地区房价带来直接冲击。本研究综合考虑经济社会慢性压力和生产事故突发性冲击对社区的影响,从影响居民决策的微观视角出发,剖析了重大事故影响下社区衰退的过滤机制,是对社区衰退研究的新探索。同时,从激发“呼吁”这一行动决策角度,提出社区忠诚度培育有助于工人社区抵抗多重压力扰动、提升社区韧性。