新疆农村贫困化空间分布及影响因素探究——以荒地镇为例

在国家大力推进精准扶贫的政策背景下,分析不同地区贫困成因的差异性具有重要意义。本文以新疆维吾尔自治区莎车县荒地镇为研究区,通过地理探测器和地理加权回归模型探究该区贫困人口和状态的空间分布及其影响因素,研究结果表明：1)荒地镇农村贫困化呈现一定范围内集聚分布的特征,镇域中部和北部地区的贫困发生率明显高于其周边地区,中部的贫困地区由中心向四周扩散,北部的贫困发生率低于中部。2)导致贫困的主要因素包括距主干道距离、人口密度和男性人口所占比例。3)距离主干道的距离与贫困发生率呈现出明显的正向相关的关系,距离镇中心的距离与贫困发生率呈现出一定的负相关关系,人口密度与贫困发生率呈现出明显的负相关关系。4)依据不同地区贫困形成的主导因素,贫困地区可以划分为道路制约型和人口制约型,其中道路制约性主要分布在荒地镇的东南地区,而人口制约性主要分布在北部地区。针对不同成因的农村贫困,本文提出应该采用不同策略的扶贫措施。     

河南省县域粮食生产格局演化及影响因素

优化粮食生产布局、探讨粮食发展规律是有效调整农业空间结构、最大限度地提高土地生产效率的有效途径.以县域为单元,借用OpenGeoDa中空间自相关和ArcGIS 10.2中地理加权回归探究了1995-2014年河南省县域粮食生产格局演化及影响因素.结果表明:① 河南省粮食产量在全国粮食总产量中的比重总体呈现增长趋势;② 县域粮食生产现状显示"东部多西部少"的分布格局,其粮食生产多集中分布在中东部平原区的产粮大县,县域粮食生产空间集聚性逐渐增强;③ 粮食生产的影响因素在不同的空间上具有不同的影响程度,且粮食生产朝低碳有机和规模化方向发展.     

高质量发展耦合协调时空格局演化及影响因素——以浙江省县域为例

综合运用耦合协调、空间关联分析和地理加权回归模型,对浙江省县域高质量发展耦合协调水平进行测度,进一步分析其空间演化特征及影响因素.结果 表明:①浙江省县域高质量发展整体上呈现出“东高西低、北高南低”的空间分异特征,高质量发展耦合空间格局以良好耦合为主,高质量发展协调水平以中级协调为主.②高质量发展耦合协调空间结构呈现出...     

京津冀文化艺术产业空间格局演变及其影响因素

基于2007—2017年文化艺术企业数据,采用核密度估计和空间自相关检验分析京津冀县域尺度的文化艺术产业的空间格局演变,并运用岭回归和地理加权回归对其影响因素效应及空间分异性进行探索,最后讨论其影响机制。研究发现：① 京津冀文化艺术产业空间集聚范围不断扩大,河北与京津的断崖式差距正在逐步缩减,“两核一轴带”格局逐渐形成;② 京津冀文化艺术产业具有显著的空间依赖性,全局依赖性有所减弱但局部依赖性逐渐增强;H-H型集聚主要在京津分布蔓延,京津之间的廊坊市显现出L-H型集聚;L-L型集聚主要位于河北各地市的边缘地带,个别区县呈现H-L型孤岛集聚形态;③ 市场需求、关联产业及人才技术是影响当前京津冀文化艺术产业发展的主要因素,文化资源影响稳定而政策环境效应空间分异性大,未来应结合地区发展空间关联性和影响因素空间分异性针对性地实现京津冀文化艺术产业协同发展。     

Modelling spatial heterogeneity and anisotropy: child anaemia,sanitation and basic infrastructure in sub-Saharan Africa

Public interventions in support of public health and housing in developing countries could benefit from better understanding of spatial heterogeneity and anisotropy. Estimation of directional variation within geographically weighted regression (GWR) faces problems of local parameter instability, border effects and, if extended to non- spatial attributes, potential endogeneity. This study formulates a GWR model where anisotropy is filtered out based on information from directional variograms. Along with classical regressions, the approach is applied to investigate child anaemia and its associations with household characteristics, sanitation and basic infrastructure in 173 regions of sub-Saharan Africa. Based on ordinary least squares (OLS) results, anaemia prevalence rates are up to three times more responsive to child morbidity (related to malaria and other diseases) than to other covariates. GWR estimates provide similar indications, but also point to poor sanitation facilities as a cofactor of severe anaemia particularly in east and southern Africa. The anisotropy-adjusted GWR is spatially stationary in residuals, and its estimated local parameters are less collinear than GWR with no adjustment. However, similar explanatory power and lack of significant bias in parameters estimated by the latter suggest that directional variation is largely captured by modelled co-movements among the variables.     

基于空间统计理论的新疆各地州经济林营养物质积累空间关系特征分析及应用

积累营养物质是森林生态服务功能中的重要组成部分,它反映了林木生长情况和生产投入情况。基于2014年新疆七种主要经济林木积累营养物质调查数据,核算了2014年全疆经济林木氮、磷和钾的物质积累总量,折合当年化肥价值3.14×10⁸元。并利用全局空间自相关模型和地理加权模型（GWR）对该结果进行了分析。结果表明：（1）全疆不同经济林品种积累营养物质价值量的空间分布符合空间集聚理论,呈现某种经济林木在某个地区具有高度集中的种植现象;（2）GWR模型分析结果表明经济林在南疆林业中占有重要地位;（3）南疆各地州经济林发展存在明显差异,其中克孜勒苏柯尔克孜自治州、和田地区和喀什地区处在经济林发展期;阿克苏地区和巴音郭楞蒙古自治州则处在经济林衰产期。上述结果表明通过深入挖掘新疆生态服务功能价值信息,能够提取对新疆经济林产业发展规划具有重要参考价值的信息。研究所使用的思路和方法对其他类似研究具有重要的借鉴意义。     

基于NPP/VIIRS夜间灯光数据的湘鄂赣省际交界区县域经济空间格局及影响因素

采用NPP/VIIRS夜间灯光数据表征经济发展水平,结合空间自相关分析方法对湘、鄂、赣省际交界区县域经济空间格局进行可视化分析,利用地理加权回归模型(GWR)分析相关影响因素的空间异质性。结果表明:湘鄂赣交界区县域经济存在明显的"金字塔"型等级特征,且低水平县(市)相对其他地区更靠近省界,边界效应特征表现突出;空间集聚性层次较低,具有"连片贫困"特征;热点地区大都位于湘、鄂、赣交界区外围地区,冷点地区位于广大的内部腹部地区,"内冷外热"两极分化的不平衡格局仍未能有效化解;劳动、资本、政府作用均具有积极作用,其中劳动投入与资本投入回归系数高值易集中于热点地区,低值则集中于冷点地区。政府作用影响效应一方面随着地区到中心城区距离的增加而依次递减,另一方面表现为省份间影响差异。交通水平与教育发展水平对经济发展差异影响呈现出正负两极分化特征。     

中国高新技术企业分布影响因素的空间异质性与尺度效应

影响高新技术企业分布的因素往往具有空间非平稳性,然而既有研究对其关注尚少。基于2017—2019年间认定的215791家高新技术企业数据,运用多尺度地理加权回归模型（MGWR）,刻画了中国高新技术企业的空间分布格局,识别了其影响因素的空间异质性与尺度效应,结果表明：① 2019年中国高新技术企业的空间分布呈现出在以“北上广深”为首位中心,以成渝与区域性中心城市为次位中心的高度集聚特征。② 企业内部因素、城市知识创造水平、技术创新水平、创新环境水平和外部连通水平共同影响了高新技术企业的空间分布。③ 影响高新技术企业分布的因素存在空间异质性,公司年龄、高校学生数量、互联网的影响呈现出“东-西”向空间分异格局,专利申请数、高新区、生活设施的正向影响呈现出“南-北”向空间分异格局,高铁的正向影响呈现出“东南-西北”向空间分异格局,研发费用投入对东北地区影响最大,市场化水平对京津冀和珠三角城市群地区影响最大。④ 影响因素存在尺度效应,靠近创新末端的变量具有更大的作用空间尺度。最后,本研究提出相关的政策建议,以期为高新技术产业的发展提供借鉴与参考。     

Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices

By incorporating temporal effects into the geographically weighted regression (GWR) model, an extended GWR model, geographically and temporally weighted regression (GTWR), has been developed to deal with both spatial and temporal nonstationarity simultaneously in real estate market data. Unlike the standard GWR model, GTWR integrates both temporal and spatial information in the weighting matrices to capture spatial and temporal heterogeneity. The GTWR design embodies a local weighting scheme wherein GWR and temporally weighted regression (TWR) become special cases of GTWR. In order to test its improved performance, GTWR was compared with global ordinary least squares, TWR, and GWR in terms of goodness-of-fit and other statistical measures using a case study of residential housing sales in the city of Calgary, Canada, from 2002 to 2004. The results showed that there were substantial benefits in modeling both spatial and temporal nonstationarity simultaneously. In the test sample, the TWR, GWR, and GTWR models, respectively, reduced absolute errors by 3.5%, 31.5%, and 46.4% relative to a global ordinary least squares model. More impressively, the GTWR model demonstrated a better goodness-of-fit (0.9282) than the TWR model (0.7794) and the GWR model (0.8897). McNamara's test supported the hypothesis that the improvements made by GTWR over the TWR and GWR models are statistically significant for the sample data.     

广州市社区出行低碳指数格局及其影响因素的空间异质性

通过构建社区出行低碳指数（CTLCI）模型,对广州市社区出行低碳指数的空间格局及其差异特征进行了分析,并利用全局回归（OLS）模型和地理加权回归（GWR）模型对社区出行低碳指数的影响因素以及其间关系的空间异质性进行了研究。结果表明,广州市社区出行低碳指数由中心城区向外逐渐递增,呈明显的圈层结构。内圈层的社区出行低碳指数内部差异最小,中间过渡圈层的最大。社区人口密度对社区出行低碳指数的影响以正向作用为主,公共交通供给水平和路网密集程度对社区出行低碳指数的影响以负向作用为主,且它们的影响作用具有空间异质性。具体指出了在不同地域空间内社区人口密度、公共交通供给水平和路网密集程度对社区出行低碳指数在影响程度和作用方向上的差异,为减少广州城市交通碳排放、针对不同空间制定有效的低碳政策和构建低碳城市空间结构提供了科学依据。     

面向转型升级发展的开发区主导产业分布及其空间集聚研究

国际与国内发展环境双重变革下,开发区“二次创业”乃至“三次创业”的呼声不断高涨。为此,有必要重新审视开发区的主导产业分布、集聚及其影响因素,以促进其转型升级发展。以国家级经济产业开发区为例,在系统梳理中国219家国家级经开区主导产业基础上,采用核密度分析法与Ripley's K函数可视化其空间分布格局与空间集聚状态;并面向转型发展与产业升级,采用GWR方法探讨影响技术密集型产业分布与集聚的主要因素及其空间异质性。研究表明：① 国家级经开区主导产业以制造业为主,产业空间集聚存在尺度分异与空间衰减特征。② 从产业组织来看,以单一/双要素密集的主导产业组织模式为主。③ 开发区自身条件对技术密集型产业集聚的促进效果相对有限;城市对开发区产业集聚的支撑作用与城市固定资产投资强度存在一定的反向联系;开发区参与全球化的深度,尤其是利用国际资本的能力与技术密集型产业集聚具有较强关联性。面向转型升级发展,开发区自身应持续改革,主动探索;同时要处理好两个“资本关系”,即开发区与所在城市固定资产投资以及与国际资本的关系。     

Exploring population spatial concentrations in Northern Ireland by community background and other characteristics: an application of geographically weighted spatial statistics

Information on how populations are spatially concentrated by different characteristics is a key means of guiding government policies in a variety of contexts, in addition to being of substantial academic interest. In particular, to reduce inequalities between groups, it is necessary to understand the characteristics of these groups in terms of their composition and their geographical structure. This article explores the degree to which the population of Northern Ireland is spatially concentrated by a range of characteristics. There is a long history of interest in residential segregation by religion in Northern Ireland; this article assesses population concentration not only by community background (‘religion or religion brought up in’) but also by housing tenure, employment and other socioeconomic and demographic characteristics. The spatial structure of geographical variables can be captured by a range of spatial statistics including Moran's I. Such approaches utilise information on connections between observations or the distances between them. While such approaches are conceptually an improvement on standard aspatial statistics, a logical further step is to compute statistics on a local basis on the grounds that most real-world properties are not spatially homogenous and, therefore, global measures may mask much variation. In population geography, which provides the substantive focus for this article, there are still relatively few studies that assess in depth the application of geographically weighted statistics for exploring population characteristics individually and for exploring relations between variables. This article demonstrates the value of such approaches by using a variety of geographically weighted statistical measures to explore outputs from the 2001 Census of Population of Northern Ireland. A key objective is to assess the degree to which the population is spatially divided, as judged by the selected variables. In other words, do people cluster more strongly with others who share their community background or others who have a similar socioeconomic status in some respect? The analysis demonstrates how geographically weighted statistics can be used to explore the degree to which single socioeconomic and demographic variables and relations between such variables differ at different spatial scales and at different geographical locations. For example, the results show that there are regions comprising neighbouring areas with large proportions of people from the same community background, but with variable unemployment levels, while in other areas the first case holds true but unemployment levels are consistently low. The analysis supports the contention that geographical variations in population characteristics are the norm, and these cannot be captured without using local methods. An additional methodological contribution relates to the treatment of counts expressed as percentages.     

美国俄亥俄州土壤有机碳密度空间分布(英文)

Historical database of National Soil Survey Center containing 1424 geo-referenced soil profiles was used in this study for estimating the organic carbon(SOC) for the soils of Ohio,USA.Specific objective of the study was to estimate the spatial distribution of SOC density(C stock per unit area) to 1.0-m depth for soils of Ohio using geographically weighted regression(GWR),and compare the results with that obtained from multiple linear regression(MLR).About 80% of the analytical data were used for calibration and 20% for validation.A total of 20 variables including terrain attributes,climate data,bedrock geology,and land use data were used for mapping the SOC density.Results showed that the GWR provided better estimations with the lowest(3.81 kg m 2) root mean square error(RMSE) than MLR approach.Total estimated SOC pool for soils in Ohio ranged from 727 to 742 Tg.This study demonstrates that,the local spatial statistical technique,the GWR can perform better in capturing the spatial distribution of SOC across the study region as compared to other global spatial statistical techniques such as MLR.Thus,GWR enhances the accuracy for mapping SOC density.     

2000-2010年广州市居住空间结构演变及机制分析

首先运用因子生态分析方法对广州市2010年的居住空间结构与居住人口特征进行分析,提取出6个主因子并划分为9类居住区,得出广州市居住空间具有明显的分异性。然后与2000年的居住空间结构进行比较,归纳出广州市居住空间演变具有历史延续性、市场及政策因素影响突出、空间拓展与城市发展同步、整体居住空间呈现“圈层+扇形”融合发展等特征。根据不同的空间层次特征,概括出四种演变模式：中心区稳定发展模式、近郊区商品房拓展模式、远郊区糅合发展模式和特定区保障房镶嵌模式。探讨了广州市居住空间结构的演变机制,包括历史发展惯性、房地产发展带动、住房保障影响、城市规划引导等四个方面。最后结合国内其他大城市相关研究推导出转型期中国大城市的居住空间结构。     

Modelling spatial patterns of urban growth in Africa

The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers.     

城市迁移人口居住空间分异——对深圳市的实证研究

基于深圳市第六次人口普查数据,将迁移人口按照户籍地划分为市内迁移、省内迁移和省际迁移3种类型。通过计算区位熵分析街道迁移人口比重在全市中的水平,并用空间自相关来识别其空间集聚状况,以揭示迁移人口的空间分异格局,进而用分异指数刻画迁移人口的分异程度。然后以街道迁移人口比重为因变量,住房因素和就业因素为自变量,采用OLS模型、空间滞后模型和空间误差模型来分析和解释迁移人口居住空间分异的影响因素。结果表明：①迁移人口区位熵呈现出较为明显的圈层结构分布特征,以南山区和福田区为中心向外依次为市内、省内和省外迁移人口;②迁移人口的居住分布存在空间集聚,市内迁移人口集聚分布在行政中心周围,省内迁移人口集中分布在商业中心周围,省外迁移人口集中分布在工业园区较多的关外街道;③省外迁移人口与本地人口之间的居住分异程度最高;④省外迁移人口的居住空间分布显著地受住房因素的影响,省内迁移人口的居住空间分布则受就业因素的影响,住房和就业因素对市内迁移人口的居住空间分布的影响不显著。     

Spatial heterogeneity of the economic growth pattern and influencing factors in formerly destitute areas of China

Journal of Geographical Sciences - Accelerating economic growth in formerly destitute areas and narrowing the economic gap with other regions are essential tasks for poverty alleviation in China...     

黄河流域城乡融合发展时空演变和动力机制

以黄河流域79个地市为研究对象,构建城乡融合发展评价指标体系,使用熵值法、标准差和变差系数、ESDA空间探索性数据分析方法和地理加权回归分析法（GWR）,分析了2005—2018年黄河流域城乡融合发展的时空演变特征和动力机制。结果表明：（1）时序演变特征方面,城乡融合系数均值由2005年的0.208提高到2018年的0.416,表明城乡融合水平持续提升,但下游地区均值一直高于中游、上游地区。标准差测度的城乡融合绝对差异由0.073升为0.103,不断缓慢上升;变差系数衡量的相对差异由0.350降为0.248,呈下降趋势。全局莫兰指数表明高于流域城乡融合系数均值的地市倾向于在空间上集聚。（2）空间演变特征方面,黄河流域东部、北部形成高于流域城乡融合系数均值的集中分布区。低于流域城乡融合系数均值的地市呈地域锁定分布。黄河流域地市城乡融合发展水平形成3层次的“核心-边缘”空间结构。（3）地势起伏度、经济发展水平、城市空间扩张、交通通达性、人口城市化、居民消费水平为黄河流域城乡融合发展时空演变主要动力因子。     

基于3种地理加权回归方法的安徽省土壤pH空间预测制图对比研究

基于安徽省140个采样点的土壤pH数据,综合考虑土壤、地形、气候、生物等因子对土壤pH的影响,采用地理加权回归(Geographically Weighted Regression, GWR)、主成分地理加权回归(Principal Component Geographically Weighted Regression, PCA-GWR)和混合地理加权回归(Mixed Geographically Weighted Regression, M-GWR)3种模型对安徽省土壤pH空间分布进行建模预测,揭示环境因子对土壤pH的影响在空间上的差异,最后以多元线性回归模型(Multiple Linear Regression, MLR)为基准比较3种GWR模型的精度。研究表明：(1)安徽省土壤pH具有空间异质性,且集聚特征明显。(2) 3种GWR模型中M-GWR模型略优,GWR、PCA-GWR和M-GWR的建模集调整后决定系数(R_adj²)分别为0.59、0.62和0.63;对比MLR模型,3种GWR模型的R_adj^2<...