A model for integrated spatial land use characteristics linking to surface nutrient concentration

Quantifying land use heterogeneity helps better understand how it influences biophysical systems. Land use area proportions have been used conventionally to predict water quality variables. Lacking an insight into the combined effect of various spatial characteristics could lead to the statistical bias and confused understanding in previous studies. In this study, using spatial techniques and mathematical models, a diagnostic model was developed and applied for quantifying and incorporating three spatial components, namely, slope, distance to sampling spots, and arrangement. The upper catchment of Miyun Reservoir was studied as the test area. Total nitrogen, total phosphorus, and chemical oxygen demand of water samples from field measurements were used to characterize the surface water quality in 52 sub-watersheds. Using parameter calibrations and determinations, combined spatial characteristics were explored and detected. Adjusted land use proportions were calculated by spatial weights of discriminating the relative contribution of each location to water quality and used to build the integrated models. Compared with traditional methods only using area proportions, our model increased the explanatory power of land use and quantified the effects of spatial information on water quality. This can guide the optimization of land use configuration to control water eutrophication.     

中尺度降水集合预报随机参数扰动方法敏感性试验

中尺度降水模式预报具有很大的不确定性,为更好地描述与模式降水预报密切相关的物理过程关键参数的不确定性,基于中国气象局GRAPES（Global/Regional Assimilation and Prediction System）中尺度区域集合预报模式,从对模式降水预报不确定性有较大影响的积云对流、云微物理、边界层及近地面层等4个参数化方案中选取了18个关键参数,设计了一种随机参数扰动方案（Stochastically Perturbed Parameterization,SPP）,并通过2015年6—7月总计10 d的随机扰动集合预报试验,对比分析了SPP方案对不同物理过程参数扰动敏感性、随机场时、空尺度敏感性、能量变化特征及其集合预报效果。结果显示,对所选择的任一物理过程参数化方案增加SPP扰动后,降水及等压面要素的概率预报技巧优于无SPP扰动的预报,而扰动积云对流和边界层过程中的参数较扰动云微物理过程中的参数影响更显著,且同时扰动积云对流、云微物理、边界层及近地面层参数化方案中的18个参数的集合预报效果优于扰动任何单一物理过程中的部分参数,表明SPP方案能够有效地提高中尺度降水概率预报技巧;从能量变化特征可知,不同物理过程的参数扰动对动能、内能和总能量的影响层次和特征有所不同,但总体而言,扰动前后各项能量基本相同;随机场时、空尺度敏感性试验发现,SPP扰动随机场时间、空间相关尺度对集合预报效果有明显影响,当扰动随机场选用12 h抗相关时间及截断波数20时,集合预报结果最优。上述结果表明,SPP随机参数扰动方案不仅能够有效提高集合概率预报效果,还能够提高集合降水概率预报技巧,具有良好的业务应用与发展前景。      

福建省晋江市城市热岛强度时空变化特征分析

利用传统的气象站法, 结合空间统计学方法(普通克里金插值法), 对福建省晋江市2010—2014年40个自动气象站逐小时温度资料加以计算处理, 分析了晋江市年、季、昼夜热岛强度时空变化规律。(1)晋江市年、季、昼夜热岛强度都呈带状分布, 等值线呈西南-东北走向, 年、季、昼夜变化趋势显著, 北部热岛强度高于南部。五年间热岛强度持续增强, 但增幅不大, 增速放缓。(2)城市化水平的提高, 会导致热岛强度高值出现季节提前, 故旅游区秋冬季热岛强度高于春夏季, 中心城区和产业经济区夏秋季热岛强度高于冬春季。(3)晋江市热岛效应昼夜空间分布格局差异性大, 夜间热岛强度显著高于白天, 最低值出现在14—16时, 中心城区和产业经济区最低值出现时间较旅游区略推迟, 三个功能区的最高值均出现在凌晨。      

基于MapX和Oracle Spatial建立矿区土地复垦信息系统探讨

煤炭资源的开采破坏了大量的土地,加剧了人地矛盾,土地复垦是矿区可持续发展的重要内容之一.矿区土地复垦是一个边缘交叉学科,所需处理的数据涉及采矿、地质、地理、土壤、农林、生物、社会经济等众多领域,具有数据信息量大、相互关系复杂等特点.传统的数据处理方法已难以适应土地复垦发展的要求.主要研究了矿区土地复垦信息系统的主要功能,并分析了基于MapX和Oracle Spatial进行系统开发的关键技术.     

师宗县高良码头公路西侧古滑坡成因与防治措施

云南师宗县高良码头公路西侧古滑坡为一中型推移式土质滑坡,滑坡体规模30.8万m3.该古滑坡曾造成南盘江短期堵塞,之后古滑坡堆积体处在临界稳定状态.由于修建的省道S207公路从滑坡下部通过,古滑坡堆积体开始蠕动,2013年8月滑坡堆积体加剧蠕动变形,后缘弧状拉张裂缝及错台变形强烈.通过多次实地调查,激发古滑坡堆积体蠕动因...     

Developing a building policy for the erosion zone: Solutions to some key (Dutch) questions

In those coastal communities where the most seaward strip of mainland consists of dunes, these dunes often serve as a flexible sea defence. In addition, this strip offers large potential for housing and commercial enterprises. Unfortunately, due to severe storm surges part of this strip (the erosion zone) is subject to erosion, and as a result of which any buildings or infrastructure located here, are destroyed. Therefore, as we will illustrate in this paper, a building policy for this zone should reflect a compromise between two opposite interests: exploitation of the existing potential and, prevention of an unacceptable high risk due to erosion. Accordingly, the authors have developed a framework for such a building policy on the basis of which the desirability of various different types of investments and the location within the erosion zone of such investments can be determined. The examples that are used to illustrate this framework in this paper are limited to experiences in The Netherlands as relevant data and experiences are available and relatively easy accessible here. Nevertheless, the approach as is described is generic and applicable worldwide suggesting that the discovered unused potential for exploitation is not just limited to The Netherlands.     

基于机理的合成孔径雷达系统成像误差理论分析

目前在遥感和GIS中,关于误差和不确定性研究的主要方法有两种: 概率统计和机理模拟。本文论述了二者的特点,详细讨论了影响合成孔径雷达成像的诸多因素,提出利用机理的方法分析SAR系统成像误差。本方法是从合成孔径雷达成像机理的研究出发,利用控制论的观点来解释、分析影响合成孔径雷达成像的诸多误差因素并建立误差传播模型。这不仅对研制合成孔径雷达的设计具有指导意义,而且对遥感数据的质量控制也有重要意义。     

6 kV电缆中间接头故障原因分析及制作工艺改进

6k V电缆中间接头的爆炸是工厂配电设备的常见故障。本文从电缆的绝缘结构方面入手 ,以绝缘热击穿理论分析了湛江电厂 # 3循环水泵电机电缆中间接头爆炸原因 ,查找导致电缆头热击穿的关键因素并进行排除 ,运用新的材料与方法重新制作 # 3循环水泵电机电缆中间接头 ,运行可靠性大有提高。改进的结果表明 ,减少缆芯的接触电阻和环境温度与绝缘结构的适当选取是杜绝高压电缆中间接头爆炸的关键。     

A density-based approach for detecting network-constrained clusters in spatial point events

Existing spatial clustering methods primarily focus on points distributed in planar space. However, occurrence locations and background processes of most human mobility events within cities are constrained by the road network space. Here we describe a density-based clustering approach for objectively detecting clusters in network-constrained point events. First, the network-constrained Delaunay triangulation is constructed to facilitate the measurement of network distances between points. Then, a combination of network kernel density estimation and potential entropy is executed to determine the optimal neighbourhood size. Furthermore, all network-constrained events are tested under a null hypothesis to statistically identify core points with significantly high densities. Finally, spatial clusters can be formed by expanding from the identified core points. Experimental comparisons performed on the origin and destination points of taxis in Beijing demonstrate that the proposed method can ascertain network-constrained clusters precisely and significantly. The resulting time-dependent patterns of clusters will be informative for taxi route selections in the future.     

Two-stage permutation tests for determining homogeneity within a spatial cluster

The discovery of spatial clusters formed by proximal spatial units with similar non-spatial attribute values plays an important role in spatial data analysis. Although several spatial contiguity-constrained clustering methods are currently available, almost all of them discover clusters in a geographical dataset, even though the dataset has no natural clustering structure. Statistically evaluating the significance of the degree of homogeneity within a single spatial cluster is difficult. To overcome this limitation, this study develops a permutation test approach Specifically, the homogeneity of a spatial cluster is measured based on the local variance and cluster member permutation, and two-stage permutation tests are developed to determine the significance of the degree of homogeneity within each spatial cluster. The proposed permutation tests can be integrated into the existing spatial clustering algorithms to detect homogeneous spatial clusters. The proposed tests are compared with four existing tests (i.e., Park’s test, the contiguity-constrained nonparametric analysis of variance (COCOPAN) method, spatial scan statistic, and q-statistic) using two simulated and two meteorological datasets. The comparison shows that the proposed two-stage permutation tests are more effective to identify homogeneous spatial clusters and to determine homogeneous clustering structures in practical applications.