北京宜居城市满意度空间特征

利用近万份的实地调查问卷,采用空间插值、空间相关性分析等空间分析方法,研究了北京市区宜居城市满意度的总体特征和空间自相关特性。结果表明,北京市区宜居城市满意度总体水平尚可,存在明显的空间自相关特性,并且空间自相关性表现出较强的尺度变化特点,而反映满意度的不同子指标的尺度也各有特点。对宜居城市满意度的空间差异性研究表明,满意度总体由城市中心向郊区递减,在交通节点附近存在满意度的"洼地"区域,同时,一些特殊区域的存在,也使北京宜居城市满意度的空间分布更加复杂。     

Spatial and Longitudinal Patterns in County Age-Specific Net Migration in the United States 1950–2010

Many migration studies describe various counties by adopting a priori county typologies, such as the U.S. Department of Agriculture Economic Research Service county typology, which might not be suitable for identifying different age migration patterns of the U.S. counties. This study employs a spatial clustering method that exhaustively compares all U.S. counties on their age migration similarity and spatial proximity to investigate signature age-specific net migration profiles across six decades of U.S. county age-specific net migration data from 1950 to 2010. All of the six-decade data are integrated into a common spatial county boundary on which counties below a population threshold are merged with the nearest county to mitigate the small population problem in net migration rates. As counties are merged by increasing large population thresholds, the Getis-Ord Gi* spatial autocorrelation statistic is applied to examine how the spatial migration patterns are affected. It is found that U.S. county age-specific net migration profiles exhibit four signature patterns. Although these patterns are persistent across the past six decades, their spatial distributions have experienced dramatic variation. The small population problem in net migration rates affects the extent and location of the significant spatial migration patterns.     

黄河流域县域碳排放的时空格局演变及空间效应机制

利用空间面板模型、空间自相关分析和以区域背景与最近邻状况为空间滞后的空间马尔科夫链对2000—2017年黄河流域县域碳排放时空格局与空间效应进行分析,结果表明：① 2000年以来黄河流域碳排放量激增,由山东全域和陕甘宁蒙交界的高值区向外圈层与轴向扩张,形成东高西低碳排放格局;② 存在“俱乐部趋同”现象,高碳排放县集聚于山东全域和陕甘宁蒙交界,低碳排放县集聚于西南部;2000年与2017年对比发现县域碳排放类型稳定性强,较高碳排放变为较低碳排放的县集中在东南部区域,而相反方向转变的县集中在内蒙古;③ 高碳溢出效应与低碳锁定效应是塑造时空格局的重要作用力,前者作用力更强;区域背景增强了“俱乐部趋同”与被包围异常值趋同,作用力强于最近邻状况,不显著区域内碳排放类型转变概率提高。④ 空间面板模型结果显示年轻人口结构、大经济规模、二产为主产业结构、高生活水平和高公共支出促进了碳排放量增加与空间效应作用,其中经济规模与产业结构是重要驱动因素。     

川滇黔接壤地区城镇化空间特征及驱动力分析

川滇黔接壤地区经济落后,整体城镇化水平较低,采用川滇黔接壤地区2008年各区县(市)的城镇化率作为测度指标,运用探索性空间数据分析(ESDA)方法,分析了本区域的城镇化水平的空间分布特征。通过对城镇化率的空间自相关系数Moran’s I的计算,发现各区县城镇化率的空间分布并非表现出完全随机性,而是具有明显的空间自相关性,具体表现为低值空间聚集。利用空间计量模型研究了城镇化水平的驱动机制。结果表明:空间误差模型优于空间滞后模型和OLS模型;相邻地区各因素的空间扩散效应对城镇化水平存在显著的影响,其弹性系数为0.416 1;第三产业增加值是城镇化率的最主要驱动因子,其弹性系数为0.777 7。因此,未来川滇黔接壤地区在推进城镇化时,应考虑城镇化水平的空间相关性,建立区域一体化开发政策,并积极发展第三产业,提高第三产业在国民经济中的比重。     

山东省农村居民点转型的空间特征及其经济梯度分异

为探究农村居民点转型的空间结构及其与经济发展的关联性,以山东省为例,基于农村宅基地转型的理论假设与测度方法,运用空间关联分析方法研究农村居民点转型的空间布局和集聚特征,并以人均GDP作为特征指标划分各县级行政区的经济发展梯度,从省级全域层面和“点、线、面”特征单元综合的角度,揭示农村居民点转型与经济发展的相关性及其耦合关系。结果显示,在空间分布上,2005-2014年山东省农村居民点转型指数呈现西高东低和南高北低的态势;在全局趋势上,Moran's I指数达到0.6317,说明农村居民点转型存在显著的空间集聚现象;在局部趋势上,农村居民点转型的热点区和次热点区集中分布在鲁西黄泛平原、鲁西南淮河平原以及鲁中沂蒙山区,次冷点区分布在次热点区外围,冷点区分布在胶东丘陵地区和鲁北黄河三角洲地带;在相关性分析上,农村居民点转型与经济发展水平具有明显的数理统计相关性和空间耦合性,无论是全域层面还是特征单元,农村居民点转型均表现出从低级到高级经济梯度的递减规律、且乘幂变化趋势显著。本文探索了农村居民点转型的空间特征,弥补了土地利用转型空间性分析的不足;同时研究结果也较好地验证了前人提出的理论假设。     

云南沿边地区县域经济的空间格局演化分析

基于云南沿边地区56个县域单元1993,2002,2009,2015年人均GDP数据,运用ESDA-GIS方法分析沿边地区县域经济的空间演化格局,并探讨其驱动因素。结果表明:云南沿边地区县域经济发展和区域经济增长存在正的空间自相关,但相关性相对较弱。1993年以来,县域经济整体格局变动不大,经济热点区域始终处于弥勒、建水、蒙自等县市,冷点区域则始终处于广南、麻栗坡、绿春等县域;而经济增长格局则表现出明显的空间演化和跃迁特征。整体上看,云南沿边县域经济的空间差异较大,由随机成分造成空间异质性也逐渐增强,且东—西方向上县域经济差异有进一步扩大趋势。资源禀赋、地理区位以及区域发展政策是县域经济空间格局演化的主要驱动力。     

中国城市居民生活用电碳排放差异及时空演变

以地级市为研究单元,以人均生活用电碳排放为测度指标,借助经典统计学中的各类不平衡指数,对2002―2011年间中国城市居民生活用电碳排放的差异程度进行动态时序分析。同时,运用ESDA方法,从静态的碳排放量和动态的碳排放增长率2个角度,定量描述了2002年以来中国城市生活用电碳排放的时空演化特征。结果表明：中国城市居民人均生活用电碳排放差异逐渐缩小;就人均碳排放量来说,总体上表现为空间正相关,且集聚程度逐渐增强,冷热点格局基本稳定,高值区域从广东省逐渐向北延伸至其他东南沿海地区;就碳排放增长率来说,碳排放增长在总体上无显著的空间相关性,地理集中现象不明显,冷热点区域转换迅速,高值区域数目显著增加且表现出向北转移的趋势。     

河南省县域就地城镇化时空演变与影响机理研究

中国的就地城镇化被视为城乡界限淡化条件下人类聚落系统发生重大改变的证据之一。已有文献大多局限在城乡二元分析框架内,本文基于城乡界限淡化的背景建立县域就地城镇化模型,对河南省108个县市2006—2016年就地城镇化水平的整体格局、空间聚类和热点区域演化进行分析。研究结果显示：① 河南省大多数县市就地城镇化水平有了明显提升,但大部分县市仍处低水平发展阶段,就地城镇化水平相对差异呈扩大趋势。② 河南省就地城镇化空间演化特征明显,“L”形豫北-豫东板块就地城镇化先行区凸显,豫西整体城镇化水平虽低但发展后劲足,连片发展态势明显。③ 河南省县域就地城镇化全局自相关性十分显著,空间聚集倾向和空间近邻效应日益显现,但仅出现了小范围的高聚类区和低聚类区。④ 河南省县域就地城镇化的热点区、冷点区分布格局变化较大,但次冷区和次热区基本保持稳定状态。⑤ 基于极大似然估计的实证检验结果表明,基础设施建设水平、城镇就业规模、人口规模和财政支出水平等是影响河南省县域就地城镇化水平的重要因素。基于上述研究结论,本文提出应从加快推进户籍制度和就业创业制度改革、完善农业土地流转和征地补偿制度、加快城乡结合部新型农村社区建设等方面提升就地城镇化建设质量和水平。     

新疆县域农林牧渔业空间差异分析——基于ESDA与GIS方法

应用ESDA并结合标准差指数(S)、变异系数(V)等方法,从空间相关的视角分析新疆各县市农林牧渔业人均产值的空间差异。结果显示:以农林牧渔业人均产值来计算的新疆县域间的农林牧渔业人均产值呈现北疆高于东疆、南疆的空间差异。2003-2012年间:新疆县域农林牧渔业人均产值的空间自相关测度Moran's I呈曲线性增减态势,表明农林牧渔业人均产值的空间集聚性呈曲线性波动,但农林牧渔业人均产值的年增长率逐年上升。从局部自相关分析来看,区域间呈现两个极端化较为明显,说明新疆农林牧渔业人均产值在空间分布上具有不均衡性。     

基于空间自相关的闽台城镇建设用地分布研究

空间自相关是一种重要的空间统计方法, 用来检验某种地理现象或某一属性值的整体分 布状况, 判断此现象或属性值在空间上是否有聚集特性存在。本文利用2002 年ASTER 影像数据 作为遥感数据源提取闽台建设用地信息, 闽台建设用地密度的分布呈现出沿台湾海峡呈对称集 聚分布的态势。通过建设用地密度的空间自相关分析, 显示闽台建设用地空间分布整体上呈显著 的空间正相关, 集聚现象明显; 而在局部上则呈现出不同的空间结构形态, 建设用地高密度区主 要集聚分布在闽东南沿海的闽江口、厦门湾和泉州湾三大城镇密集区及台湾西部的台北、台中和 高雄三大都会区。这种空间相关关系的探讨对于认识闽台人口和社会经济的空间分布及福建省 建设用地未来的发展具有重要的意义, 也对福建省社会经济发展政策的制定提供重要参考依据。     

黄土高原地区乡村性空间特征及其与可达性格局关系

在乡村转型重构的关键时期以及城乡融合背景下,可达性作为驱动乡村地域特征改变的直接媒介,对乡村减贫及可持续发展产生重要影响。以县域为基本空间单元,构建了刻画乡村性和可达性的指标体系,定量测度了1990年、2000年、2010年、2015年黄土高原地区243个县域乡村性与可达性指数,探索黄土高原地区县域乡村性和可达性的时空演变特征,采用探索性空间数据方法,引入空间计量经济模型,对乡村性与可达性的集聚特征及关系进行计量分析。结果显示:①研究区乡村性整体呈减弱态势、差异不断增大,呈现"西高东低"分布格局;可达性整体呈增强趋势、差异不断缩小,"东高西低"的分布格局基本不变。②乡村性与可达性空间分布均呈较强的正空间自相关,以"榆林-庆阳"一线为界分布,但集聚态势总体不断减弱;其次,可达性的提升对乡村性呈负向影响且波动增强,低可达性-高乡村性类型主要分布在西北的青海、甘肃、宁夏境内,高可达性-低乡村性类型主要分布在东部经济发展水平较高的地级市周边县市。③乡村性的空间溢出效应显著,表现出显著的空间滞后和空间误差溢出效应,区域乡村性会受到周边地区乡村性的显著影响;可达性的提升会使得乡村人口变化率、一产产...     

南疆三地州贫困与旅游资源优势空间关联研究

2020年全面建成小康社会的目标对贫困治理更具现实意义。本文通过构建SOFM神经网络评估模型,聚类分析南疆三地州24个县市的经济--社会--自然多维度贫困。在评价县域旅游资源优势度的基础上,运用空间数据分析方法(ESDA)分析研究区县域贫困度和旅游资源优势度的空间分布格局,将两者在空间匹配后发现：①致贫因子集合向量的Matlab分类显示,南疆三地州各县市贫困类型可划分为经济型贫困、社会型贫困和生态型贫困,并且贫困空间聚合分布态势显著。②旅游资源优势区集中在地理环境结构复杂和多民族聚居的地区,如喀什市、塔县、阿克陶县、和田市;旅游资源优势区局域空间自相关呈现集群分布特征。③贫困类型与旅游资源优势在县域存在显著的空间关联,出现3类拟合性较好的区域。建议采取“旅游+旧城改造”和“旅游+商品基地”、“领头雁”旅游扶贫等旅游扶贫模式。     

东北地区建设用地开发强度格局演变的空间分异机制

建设用地开发强度是区域建设用地开发利用程度及其对区域人口和经济社会承载强度的综合反映。本文以东北地区179个县域空间为基本研究单元,应用冷热点、空间变差函数、GWR模型等定量方法对建设用地开发强度的时空分异格局演变及分异机制进行了探讨,得出以下结论：① 2000-2015年东北地区建设用地开发强度总体呈现出增长态势,但空间分异显著,各单元间建设用地开发强度高低的相互作用及联动效应较为明显,但建设用地开发强度的空间分布逐渐趋于非均衡,建设用地开发强度的冷热点分布格局与全局分异变化及空间异质性态势基本吻合;② 2000年东北地区开发强度格局分异由政府财政投入力度、用地投资强度和产业结构水平共同影响,到2005-2015年发展演化为政府财政投入力度、用地投资强度、经济发展水平和产业结构水平共同影响;③ 2000-2015年政府财政投入力度、用地投资强度、经济发展水平和产业结构水平与东北地区建设用地开发强度格局分布态势具有一定的关联性,但在不同区域呈现出影响程度的差异性。     

河南省县域农民人均纯收入时空演变分析

以县级区域为研究单元,采用空间自相关分析方法,利用1999-2007年时间序列数据,对河南省农民人均纯收入的时空演变过程进行分析,结果表明:1)收入相似的县域空间集聚始终非常显著,总体空间相关程度基本呈增加趋势;2)农村经济高收入核心区分布较稳定,以焦作、郑州、许昌为中心集中分布,在全省农村经济发展势能最高;3)农村经济塌陷核心区在空间上从豫西中部迁移到了豫东中部;4)呈现显著空间异质性的县域主要位于高收入核心区和低收入核心区的边缘,一直未形成明显的空间集聚;5)高收入核心区和低收入核心区始终呈现明显的空间分异,宏观空间分异表现为北高南低、中部高东西部低的总体空间分布特征。     

A geospatial analysis of multi-scalar regional inequality in China and in metropolitan regions

This paper provides a geospatial analysis of regional inequality across provinces, prefectures and counties in China from 1997 to 2010 under a comparative spatiotemporal conceptual framework. Despite significant spatial agglomeration at all spatial scales, the extent of agglomeration shows an obviously downward trend from 2003 to 2006. Substantially stronger agglomeration of economic development is demonstrated at county scales. Local indicators of spatial autocorrelation (LISA) are employed to visualize the local spatial characteristics of economic growth. Four snapshots (in the years 1997, 2001, 2005, and 2010) of LISA indicate a dramatic north-shifting of hot spots of economic growth in response to the northward movement of foreign investors and spatial agglomeration besides institutional forces in China. Furthermore, local spatial agglomeration demonstrates a heterogeneous process: hot spots of economic development along the coast, cold spots in western China and no significant spatial clusters in central China. As the major carries of scale economies, metropolitan regions see decreasing internal agglomeration during this period with the exception of the Yangtze River Delta area, which shows a strong spatial spillover into its neighbourhood. Finally, LISA Markov and geovisualization methods are employed to predict the long-run properties of spatial distribution in multi-scalar China. The results show that downward co-movements of a county with its neighbours are more frequently encountered, perhaps resulting in the continuous concentration of poor areas in the long run.     

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。     

不同地貌区耕地集约利用水平空间分异及驱动机制——以江西省为例

在构建衡量耕地集约利用水平的P-S-R模式指标体系基础上,以县域为基本空间单元,借助GIS空间分析软件,利用ESDA等方法,对江西省各地貌区耕地集约利用水平空间差异及其驱动机制进行了研究,针对各地貌区制约耕地集约利用因素,分别提出了今后耕地利用过程中应注意的问题。结果表明:两时段基于综合度的Global Moran’s I分别为0.16和0.30,在显著性水平α=0.05下呈空间正相关,耕地集约利用水平在地域上呈现出较明显的空间集聚特征与区域差异性,且有不断加强趋势。总体上平原区的集约水平高于丘陵与山区的,经济发展较快地区的相对较高;各研究实体Local Moran’s I及Grid图,反映了耕地集约利用水平在局域空间上的均质性,即水平高、低区域各自集聚;LISA显著集聚四种类型中,正空间自相关的"H-H"、"L-L"占主体部分,时段Ⅰ二者约占总数的73.33%,时段Ⅱ则提高到80.95%。其中,"H-H"关联的区域主要分布在北部平原区、经济实力较强的县(市),而赣东北、西北及南部的丘陵山区则表现出明显的"L-L"关联特征;平原、丘陵、山区三大地貌区影响耕地集约利用水平的因素各异。     

Estimating the spatial pattern of human-caused forest fires using a generalized linear mixed model with spatial autocorrelation in South Korea

Most forest fires in Korea are spatially concentrated in certain areas and are highly related to human activities. These site-specific characteristics of forest fires are analyzed by spatial regression analysis using the R-module generalized linear mixed model (GLMM), which can consider spatial autocorrelation. We examined the quantitative effect of topology, human accessibility, and forest cover without and with spatial autocorrelation. Under the assumption that slope, elevation, aspect, population density, distance from road, and forest cover are related to forest fire occurrence, the explanatory variables of each of these factors were prepared using a Geographic Information System-based process. First, we tried to test the influence of fixed effects on the occurrence of forest fires using a generalized linear model (GLM) with Poisson distribution. In addition, the overdispersion of the response data was also detected, and variogram analysis was performed using the standardized residuals of GLM. Second, GLMM was applied to consider the obvious residual autocorrelation structure. The fitted models were validated and compared using the multiple correlation and root mean square error (RMSE). Results showed that slope, elevation, aspect index, population density, and distance from road were significant factors capable of explaining the forest fire occurrence. Positive spatial autocorrelation was estimated up to a distance of 32 km. The kriging predictions based on GLMM were smoother than those of the GLM. Finally, a forest fire occurrence map was prepared using the results from both models. The fire risk decreases with increasing distance to areas with high population densities, and increasing elevation showed a suppressing effect on fire occurrence. Both variables are in accordance with the significance tests.     

Using autologistic spatial models to simulate the distribution of land-use patterns in Zhangjiajie, Hunan Province

Nowadays, spatial simulation on land use patterns is one of the key contents of LUCC. Modeling is an important tool for simulating land use patterns due to its ability to integrate measurements of changes in land cover and the associated drivers. The conventional regression model can only analyze the correlation between land use types and driving factors, but cannot depict the spatial autocorrelation characteristics. Land uses in Yongding County, which is located in the typical karst mountain areas in northwestern Hunan province, were investigated by means of modeling the spatial autocorrelation of land use types with the purpose of deriving better spatial land use patterns on the basis of terrain characteristics and infrastructural conditions. Through incorporating components describing the spatial autocorrelation into a conventional logistic model, we constructed a regression model (Autologistic model), and used this model to simulate and analyze the spatial land use patterns in Yongding County. According to the comparison with the conventional logistic model without considering the spatial autocorrelation, this model showed better goodness and higher accuracy of fitting. The distribution of arable land, wood land, built-up land and unused land yielded areas under the ROC curves (AUC) was improved to 0.893, 0.940, 0.907 and 0.863 respectively with the autologistic model. It is argued that the improved model based on autologistic method was reasonable to a certain extent. Meanwhile, these analysis results could provide valuable information for modeling future land use change scenarios with actual conditions of local and regional land use, and the probability maps of land use types obtained from this study could also support government decision-making on land use management for Yongding County and other similar areas.     

Impacts of traffic accessibility on ecosystem services: An integrated spatial approach

The continuous degradation of ecosystem services is an important challenge faced by the world.Improvements in transportation infrastructure have had substantial impacts on economic development and ecosystem services.Exploring the influence of traffic accessibility on ecosystem services can delay or stop their deterioration;however,studies on its impact are lacking.This study addresses this gap by analysing the impact of traffic accessibility on ecosystem services using an integrated spatial regression approach based on an evaluation of the ecosystem services value (ESV) and traffic accessibility in the Middle Reaches of the Yangtze River Urban Agglomeration (MRYRUA) in China.The results indicated that the ESV in the MRYRUA continuously decreased during the study period,and the average ESV in plain areas,areas surrounding the core cities,and areas along the main traffic routes was significantly lower than that in areas along the Yangtze River and the surrounding moun-tainous areas.Traffic accessibility continued to increase during the study period,and the high-value areas centred on Wuhan,Changsha,Nanchang,and Yichang were radially dis-tributed.The global bivariate spatial autocorrelation coefficient between the average ESV and traffic accessibility was negative.The average ESV and traffic accessibility exhibited signifi-cant spatial dependence and spatial heterogeneity.Spatial regression also proved that there was a negative association between the average ESV and traffic accessibility,and scale ef-fects were evident.The findings of this study have important policy implications for future ecological protection and transportation planning.