An expanded surface-water palaeotemperature inference model for use with fossil midges from eastern Canada

Using an expanded surface sample data set, representing lakes distributed across a transect from southernmost Canada to the Canadian High Arctic, a revised midge-palaeotemperature inference model was developed for eastern Canada. Modelling trials with weighted averaging (with classical and inverse deshrinking; with and without tolerance downweighting) and weighted averaging partial least squares (WA-PLS) regression, with and without square-root transformation of the species data, were used to identify the best model. Comparison of measured and predicted temperatures revealed that a 2 component WA-PLS model for square-root transformed percentage species data provided the model with the highest explained variance (r =0.88) and the lowest error estimate (RMSEP _jack =2.26 °C). Comparison of temperature inferences based on the new and old models indicates that the original model may have seriously under-estimated the magnitude of late-glacial temperature oscillations in Atlantic Canada. The new inferences suggest that summer surface water temperatures in Splan Pond, New Brunswick were approximately 10 to 12 °C immediately following deglaciation and during the Younger Dryas. During the Allerod and early Holocene, surface water temperatures of 20 to 24 °C were attained. The new model thus provides the basis for more accurate palaeotemperature reconstructions throughout easternmost Canada.     

Population landscape: a geometric approach to studying spatial patterns of the US urban hierarchy

We present a geometric and graphic approach to studying spatial patterns of urban hierarchy in the US. The multiplicatively weighted Voronoi diagram is found to be effective for visualizing theoretical regions delineated by socio‐economic variables. The population landscape of the continental US demonstrates overall and stepwise patterns reflecting population, neighborhood and distance, with overwhelming influence from huge metropolitan areas. Stepwise exploration and cluster analysis of the spatial pattern reveal an urban hierarchy. Attributes and arrangement are the two important factors of urban hierarchy, with attribute having a stronger local influence and arrangement having a stronger global influence. The study also presents a variation of Zipf's law to visualize the rank‐size distribution from tabular and statistical space to map space.     

基于GWR模型的中国区域旅行社业效率空间分异及动力机制分析

基于DEA模型对中国31个省域的旅行社业效率空间分异特征进行了分析,首次运用GWR模型探索交通、资本、人才、信息化和经济动力对区域旅行社业效率影响的空间差异。结果表明：旅行社业效率在空间上具有正相关性和集聚特征,空间格局从“川”字型向“山”字型转变。各动力因子的系数均存在空间非平稳性。资本和人才动力的回归系数在空间分布上从南向北依次递减;经济动力的分布趋势为从北向南依次递减;交通动力对中西部地区旅行社效率提升的促进作用显著于东部地区;信息化动力则在东部地区表现出较强的促进作用。     

Multicollinearity and correlation among local regression coefficients in geographically weighted regression

Present methodological research on geographically weighted regression (GWR) focuses primarily on extensions of the basic GWR model, while ignoring well-established diagnostics tests commonly used in standard global regression analysis. This paper investigates multicollinearity issues surrounding the local GWR coefficients at a single location and the overall correlation between GWR coefficients associated with two different exogenous variables. Results indicate that the local regression coefficients are potentially collinear even if the underlying exogenous variables in the data generating process are uncorrelated. Based on these findings, applied GWR research should practice caution in substantively interpreting the spatial patterns of local GWR coefficients. An empirical disease-mapping example is used to motivate the GWR multicollinearity problem. Controlled experiments are performed to systematically explore coefficient dependency issues in GWR. These experiments specify global models that use eigenvectors from a spatial link matrix as exogenous variables.This study was supported by grant number 1 R1 CA95982-01, Geographic-Based Research in Cancer Control and Epidermiology, from the National Cancer Institute. The author thank the anonymous reviewers and the editor for their helpful comments.     

Surface sediment Chironomidae (Insecta: Diptera) distributions along an ecotonal transect in subarctic Fennoscandia: developing a tool for palaeotemperature reconstructions

We used multivariate statistical techniques to analyse the distributions of surface sediment chironomid assemblages with respect to surface-water temperature, and an additional set of 27 environmental variables, in 30 freshwater lakes of northern Fennoscandia. Our study transect spans boreal coniferous forest to subarctic tundra and includes a steep temperature gradient. Canonical correspondence analysis (CCA) with forward selection and associated Monte Carlo permutation tests revealed that there were statistically significant (P<0.05) relationships between chironomid distributions and two environmental variables, namely lakewater temperature and maximum lake depth. A constrained CCA with temperature as the only predictor variable suggested that the relationship between lakewater temperature and chironomid composition was sufficiently robust for developing a weighted-averaging (WA) based quantitative inference model that will allow palaeotemperature reconstructions using subfossil chironomid remains preserved in lake sediments.     

邻避设施空间分布特征及其与周边住宅价格的关系——广州案例

随着中国城镇的快速发展以及市民环境意识的提高,由邻避设施引发的矛盾日益增多。合理规划邻避设施,是促进环境正义、推动社会和谐的重要课题。论文从“规划云平台”获取广州主城区邻避设施的地理信息数据,通过Python语句编码收集广州主城区小区平均房价数据,运用克里金插值法分析邻避设施的空间分布特征,构建多元线性回归模型和地理加权回归模型研究邻避设施与周边住宅价格的关系。研究发现,广州主城区邻避设施的布局与低收入住宅区的分布在空间上具有一致性,邻避设施主要分布在房价较低的住宅区周边;邻避设施对周边小区房价的影响与邻避设施的类型和所在区位相关,城市边缘区的邻避设施对房价造成了显著的负面影响,而城市中心良好的区位条件、基础设施与公共服务配套一定程度上抵消了邻避设施的负外部性;污名化类的邻避设施对房价的影响程度明显小于污染类、风险聚集类和心理不悦类邻避设施。本研究对有关城市邻避设施的科学规划布点具有一定的借鉴和指导意义。     

基于GWR模型的中国城市雾霾污染影响因素的空间异质性研究

基于全国城市的PM_2.5监测数据,识别PM_2.5的时空分布特征,并着重利用地理加权回归模型分析自然和社会经济因素对PM_2.5影响的空间异质性。结果显示：2015年全国PM_2.5的年均浓度为50.3 μg/m3,浓度变化呈现冬高夏低,春秋居中的“U型”特征;PM_2.5的空间集聚状态明显,其中京津冀城市群是全国PM_2.5的污染重心。地理加权回归结果显示：影响因素除高程外,其余指标均呈现正负两种效应,且影响程度具有显著的空间差异性特征。从回归系数的贡献均值来看,自然因素对城市PM_2.5浓度影响强度由高到低依次是高程、相对湿度、温度、降雨量、风速、植被覆盖指数;各类社会经济指标对城市PM_2.5浓度影响强度排名依次是人口密度、研发经费、建设用地比例、产业结构、外商直接投资、人均GDP。由于各指标对城市PM_2.5浓度变化的影响程度存在着空间异质性,因此在制定大气治理对策时可以考虑不同指标影响程度的空间差异,从而使得治霾对策更具针对性。     

甘肃省“五化”协同发展时空演变格局及影响因素分析

以2005年、2010年和2015年甘肃省87个县区、县级市及自治县的工业化、城镇化、信息化、农业现代化与绿色化（简称“五化”）为研究对象,利用空间自相关分析、地理加权回归分析等空间分析方法,结合构建的“五化”协同发展模型,对甘肃省“五化”协同发展的时空分异格局、时空演变趋势和影响因素进行研究分析,以期为甘肃省各市州科学的制定发展政策提供参考。结果表明：甘肃省“五化”协同发展格局具有明显的空间相关性且空间差异显著,协同水平呈现出明显的西北高、东南低分布格局;“五化”发展水平和综合水平较低,协同水平总体不高,以轻度失调、濒临失调和勉强协同为主,但总体上升幅度较大;“五化”协同发展的影响因素,按其影响力大小依次为：农村居民人均可支配收入 > 城乡居民可支配收入差 > 固定资产投资总额 > 财政支出 > 地形起伏度 > 城乡居民消费差 > 降水量。     

县域农村贫困化空间分异及其影响因素——以陕西山阳县为例

以国家扶贫开发重点县山阳县为研究区,通过空间自相关分析和分组分析方法探究山阳县农村贫困化的空间格局和类型;利用逐步回归、地理加权回归和地理探测器模型对山阳县农村贫困化影响因素进行分析,讨论影响因素效应水平的空间异质性及其交互作用。研究表明：① 山阳县农村贫困发生率具有较强的空间集聚性,形成6个热点集聚区和4个冷点集聚区;综合考虑农村贫困程度和空间连接性,将山阳县划分为低度贫困区、中度贫困区和高度贫困区。② 水网密度、到最近公路的距离、危房比例、农民人均可支配收入、外出务工人数比例、农户入社比例6个因素是山阳县农村贫困化的主要影响因素,各因素的影响效应具有空间异质性。③ 两因素交互作用要比单因素作用于贫困发生率时影响力更显著,各主要影响因素的交互作用类型有双因子增强型和非线性增强型两种。     

中国省际边界区县域经济格局及影响因素的空间异质性

通过构建省际边界区经济发展差异指数,结合空间自相关模型对省际边界区县域经济发展差异格局进行分析,并利用全局回归（OLS）模型和地理加权回归模型（GWR）对省际边界县域经济发展差异影响因素的空间异质性进行研究。结果表明,中国省际边界区县域经济发展具有显著的空间集聚性,边界经济发展差异较大的地区集中在蒙甘边界,蒙宁边界和陕蒙边界地区。政府宏观调控因子与西部地区县域经济发展差异呈负相关趋势,教育发展水平对县域经济发展差异影响呈现出贫困与发达地区二元分异,边界的紧凑度、地形起伏度、交通优势度与产业结构因子对县域经济发展差异指数呈现出正相关趋势。本文具体分析了在不同省际边界县域内,各影响因素对县域经济发展差异指数的影响程度差异和作用方向差异,为合理调控不同地区发展要素、缩小省际边界地区经济发展差异、制定不同省际边界县域发展策略提供科学依据。