基于空间扩展模型和地理加权回归模型的城市住房价格空间分异比较

鉴于已有研究主要集中探讨住房价格的空间依赖性,较少涉及空间异质性对住房特征价格的影响,也很少尝试构建不同计量模型来比较模型间刻画住房价格影响因素空间分异的准确性,以长沙市中心城区为研究区,采用空间扩展模型和地理加权回归模型比较分析城市住房价格影响因素的空间分异,结果表明：① 空间扩展模型和地理加权回归模型都表明,长沙市中心城区的住房属性边际价格随着区位的变化而变化,揭示住房价格影响因素具有显著的空间异质性;小区环境、交通条件、教育配套、生活设施等因素对住房价格的影响强度存在明显的空间分异。② 地理加权回归模型和空间扩展模型都能对传统特征价格模型进行改进,但地理加权回归模型在解释能力和精度方面都超过空间扩展模型;对属性系数估计空间模式的分析,地理加权回归模型形成的结果比采用坐标多义扩展的空间扩展模型更为复杂和直观。     

中国区域创新来源的空间异质性研究

基于经济普查数据,应用地理加权回归模型实证研究了中国区域创新来源因素对创新绩效影响的空间异质特征。结果发现当前中国区域创新主要来源是自主研发,国内技术引进和技术吸收对区域创新有正向作用,外国技术引进、出口、外国直接投资存在一定负效应。不同的省域,创新来源因素对创新绩效的影响存在空间异质。创新来源因素对区域创新的影响大体呈现从东部发达地区向西部后发地区梯度递减特征。在东、中部地区,自主研发成为主要创新来源因素,正效应显著;西部地区的创新来源除自主研发,国内技术转移和吸收仍发挥重要作用,地理加权回归较好揭示了创新影响的空间异质特点。     

中国高技术产业集聚的就业效应研究——基于空间面板的实证分析

产业集聚的就业效应既是一个复杂的理论问题,也是一个不可回避的现实问题。该文基于中国2004-2011年高技术产业的省级面板数据,应用空间计量模型探讨了高技术产业集聚与就业水平之间的关系。研究结果表明,高技术产业就业水平与产业集聚之间存在着倒U形关系,即产业集聚达到门槛值之前,集聚对就业水平具有正效应,但跨越门槛值之后,随着集聚程度的不断提高,就业水平会呈现下降的趋势。此外,分行业高技术产业的门槛值不尽相同,相同集聚程度下,不同产业可容纳的就业量也存在着很大的差异。     

中国高技术产业创新空间分布及其影响因素——基于面板数据的空间计量分析

本文基于2003-2012年省域面板数据,采用地统计方法分析中国高技术产业创新的空间分布,并运用空间计量模型对其影响因素进行探讨。研究发现：中国高技术产业创新存在明显的空间差异,其中东部地区的创新水平明显高于中部和西部地区;2003-2012年间,高技术产业创新整体空间差异表现出先扩大后缩小的趋势,空间分布呈现出先集聚后扩散的变化特征;相邻省域间的创新水平存在明显溢出现象,研发资金投入、研发人员投入、高校研发水平、企业规模和市场开放度均对高技术产业创新起到促进作用,且研发人员投入和市场开放度还能进一步促进相邻地区的创新发展,而企业规模则对相邻地区的创新存在负面影响。因此,加大对中西部地区研发资金和研发人员投入,重视高校在创新发展中的作用,破除区域壁垒促进技术流动以及加大市场开放度,都有利于提高整体创新水平和缩小创新空间差异。     

基于地理加权回归的中国灰水足迹人文驱动因素分析

根据Hoekstra和Chapgain提出的污染物吸纳理论,估算了2012年全国31个省（区、市）的灰水足迹,采用空间自相关分析方法探讨了2012年中国灰水足迹的空间分布特征,通过构建基于地理加权回归的STIRPAT模型,测算了人口和富裕等人文因素对灰水足迹的影响。结果表明：中国灰水足迹存在较强的空间正相关性和空间分布不均衡性;人文因素对水资源环境的威胁大小排序,依次为城市化率、人口数量、产业结构和富裕程度,其中,城市化率、人口数量、农业比重和人均GDP每提高1%,分别引起灰水足迹增加1.03%、0.85%、0.63%和0.52%;人文因素对灰水足迹的影响存在空间差异,人口对灰水足迹的影响由北向南逐步加大,富裕对灰水足迹的影响由西向东逐渐减小,农业和城市化对灰水足迹的影响由南向北逐步增大;在现有样本范围内,计算结果有条件地支持环境Kuznets曲线。     

地区间贸易流量的产业—空间模型构建与应用

通过深入剖析区域间经济联系的经济地理学理论基础,考虑到同业影响因子,重新构建引力模型,并引入空间滞后因子,利用地理加权回归方法建立了估算区域间贸易流量的产业—空间统计模型,并在中国30 个省区投入产出表的基础上,以省区间农业、化工、通信电子3 个产业贸易流量的估算为例对上述方法进行了说明。结果表明：① 空间统计模型的应用可以显著提高区域间贸易流量的估算可靠性;② 随着空间权函数中带宽的缩小,贸易流量显得更加集中。因此,带宽在一定程度上反映了地理活动的空间集聚程度,不同行业应选取不同带宽;③ 不同行业有不同的同业影响机制和贸易特征,农业输出地以中部地区为主,目的地以沿海地区为主,具有一定的同业竞争关系,而化工、通信行业的产业流动主要发生在东部地区内部,具有很强的同业合作关系。     

基于多光谱和地理加权回归模型的石嘴山城市土壤有机碳空间分布研究

城市土壤有机碳(SOC)分布受城市建设、工业发展等人为因素的影响表现出明显的空间差异。为揭示石嘴山市SOC受城市化、工业化等人类活动的影响,分别利用普通克里格法(OK)、多元线性回归克里格法(RK)、遥感反演方法(RS)和遥感-地理加权回归克里格法(RGWRK)预测石嘴山市SOC空间分布。结果表明:石嘴山市SOC含量在1.31～66.92 g·kg^-1之间变化,其平均值为17.61 g·kg^-1。石嘴山市不同功能区SOC含量存在显著差异(p<0.05),具体表现为工业区>医疗区>商业区>道路>住宅区>公园>农田>科教区;SOC含量变异系数为66.27%,呈中等程度变异;其最佳拟合模型为高斯模型,C₀/(C₀+C)为0.02,属于强空间自相关。SOC与遥感影像波段DN值的差值(B1-B7、B3-B7、B4-B7)和地形因子(高程、坡度、起伏度)之间存在着极显著的相关性(p<0.01);通过对4种方法的结果进行对比可知以各波段DN值差值与地形因子为输...     

中国城市创新能力及其影响因素的空间分异——基于GWR模型的实证

基于城市发明专利授权数,利用克里金插值法、空间自相关方法分析了中国城市创新能力的空间分异特征;并运用地理加权回归（GWR）模型探讨了289个地级及以上城市创新能力影响因素的空间异质性,揭示主导因素的空间分异。结果表明：1）中国城市创新能力呈现由东南向西部递减的趋势,创新能力最强的城市主要集中在东南部沿海地区,而以西藏各市及青海、新疆部分城市为主的西部城市创新能力最弱,空间集聚性显著;创新能力高-高集聚的地区为京津冀、长三角、珠三角地区,低-低集聚的地区为西部及东北地区。2）影响因素方面,各自变量的显著性水平较好,显著区域占比由大到小依次为财政投入、人才要素、经济基础、经济外向度、金融环境、信息化水平,除财政投入对城市创新能力具有显著的正相关性之外,其他因素皆同时存在正负相关效应;各自变量指标回归系数区间范围较大,具有明显的空间分异特征。3）主导因素方面,东南部城市创新能力受经济基础影响较大,而东北以及西部城市受金融环境影响较大。中国城市创新能力影响因素存在空间分异,政府及相关部门在制定创新政策时需要考虑不同城市的特点,采取针对性措施,促进中国城市创新健康协调发展。     

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。     

中国东部沿海五大城市群创新效率、影响因素及空间溢出效应

作为经济发展的战略核心区域,东部沿海城市群的创新效率关系到创新驱动发展战略的实施和创新型国家建设。基于东部沿海五大城市群创新投入和产出面板数据,引入随机前沿生产函数测度2001—2015年五大城市群的创新效率,并利用空间Durbin模型定量分析创新效率的空间溢出效应。结果表明：① 2001年以来,五大城市群的创新效率均呈现稳定增长的趋势;② 京津冀创新效率增长缓慢,山东半岛城市群创新效率的提升幅度最大,长三角创新效率的提升幅度和均值仅次于山东半岛和京津冀城市群,而城市群核心城市虽然创新资源投入较多,但创新效率偏低;③ 经济发展水平、集聚经济、外商投资、劳动力素质、政府资助、基础设施、产业结构和高新技术产业对城市群创新效率有直接作用和溢出效应。     

A comment on geographically weighted regression with parameter-specific distance metrics

A recent paper in this journal proposed a form of geographically weighted regression (GWR) that is termed parameter-specific distance metric geographically weighted regression (PSDM GWR). The central focus of the PSDM generalization of the GWR framework is that it allows the kernel function that weights nearby data to be specified with a distinct distance metric. As with the recent paper on Multiscale GWR (MGWR), the PSDM framework presents a form of GWR that also allows for parameter-specific bandwidths to be computed. As a result, a secondary focus of the PSDM GWR framework is to reduce the computational overhead associated with searching a massive parameter space to find a set of optimal parameter-specific bandwidths and parameter-specific distance metrics. In this comment, we discuss several concerns with the PSDM GWR framework in terms of model interpretability, complexity, and computational efficiency. We also recommend some best practices when using these models, suggest how to more holistically assess model variations, and set out an agenda to constructively focus future research endeavors.     

Spatial non-stationary characteristics between grass yield and its influencing factors in the Ningxia temperate grasslands based on a mixed geographically weighted regression model

Spatial models are effective in obtaining local details on grassland biomass, and their accuracy has important practical significance for the stable management of grasses and livestock. To this end, the present study utilized measured quadrat data of grass yield across different regions in the main growing season of temperate grasslands in Ningxia of China (August 2020), combined with hydrometeorology, elevation, net primary productivity (NPP), and other auxiliary data over the same period. Accordingly, non-stationary characteristics of the spatial scale, and the effects of influencing factors on grass yield were analyzed using a mixed geographically weighted regression (MGWR) model. The results showed that the model was suitable for correlation analysis. The spatial scale of ratio resident-area index (PRI) was the largest, followed by the digital elevation model, NPP, distance from gully, distance from river, average July rainfall, and daily temperature range; whereas the spatial scales of night light, distance from roads, and relative humidity (RH) were the most limited. All influencing factors maintained positive and negative effects on grass yield, save for the strictly negative effect of RH. The regression results revealed a multiscale differential spatial response regularity of different influencing factors on grass yield. Regression parameters revealed that the results of Ordinary least squares (OLS) (Adjusted R² = 0.642) and geographically weighted regression (GWR) (Adjusted R² = 0.797) models were worse than those of MGWR (Adjusted R² = 0.889) models. Based on the results of the RMSE and radius index, the simulation effect also was MGWR > GWR > OLS models. Ultimately, the MGWR model held the strongest prediction performance (R² = 0.8306). Spatially, the grass yield was high in the south and west, and low in the north and east of the study area. The results of this study provide a new technical support for rapid and accurate estimation of grassland yield to dynamically adjust grazing decision in the semi-arid loess hilly region.     

基于地理探测器和GWR模型的中国重点镇布局定量归因

重点镇是小城镇发展的龙头,形成科学合理的重点镇布局对优化中国城市化战略格局有重要意义。论文以2004年和2014年分别公布的1887个和3675个全国重点镇为样本,对其分布及效应的变动特征进行探究,进而在地级尺度对重点镇布局的影响因子及其作用进行地理探测和局部空间回归。结果表明：① 经增补调整,中国重点镇布局及建设效应的均衡性增强,主要集聚区西移北扩,冷热点的分布突破“胡焕庸线”,经济辐射效应的分化程度减弱,体现出政策因素的有力影响。除县际均衡和区域倾斜政策外,重点镇的分布还受到海拔高度、公路网密度、常住人口城镇化率等因子的显著作用。② 因子探测器、GWR模型和交互作用探测器的结合能更精准地刻画影响因子的作用方式、方向、路径和强度。中国重点镇的布局不是5个显著性因子均匀、独立、直接作用的结果,而是影响均具空间异质性的各因子两两交互作用后增效的产物。③ 县际均衡政策与其他因子的协同作用是形成现有重点镇分布格局的主导力量;区域倾斜政策的效果总体较好,但目标区域还需更准确。     

基于千强高新技术企业的中国城市创新网络研究

在我国创新驱动发展战略的背景下,城市发展中的创新要素变得空前重要,基于创新型企业联系数据研究城市创新网络成为当今城市发展的重要议题。选取2018年中国创新能力1000强的高新技术企业总部和分支机构信息,基于核密度分析法和连锁网络模型,对企业布局和城市创新网络结构进行研究。研究表明：（1）高新技术企业主要聚集于中国三大沿海城市群及部分中西部中心城市;（2）中国城市创新网络大致呈现出菱形结构,城市创新能力差异显著且具有等级性,城市间的创新联系主要通过等级扩散形成;（3）不同行业视角下的城市创新网络结构差异性显著,依据行业属性可将创新型城市划分为科技创新型城市、工业创新型城市和服务创新型城市。研究以期推动传统产业转型升级,实现城市创新发展,为创新型城市制定针对性发展模式提供科学参考。     

Application of geographically weighted regression model in the estimation of surface air temperature lapse rate

The surface air temperature lapse rate(SATLR)plays a key role in the hydrological,glacial and ecological modeling,the regional downscaling,and the reconstruction of high-resolution surface air temperature.However,how to accurately estimate the SATLR in the regions with complex terrain and climatic condition has been a great challenge for re-searchers.The geographically weighted regression(GWR)model was applied in this paper to estimate the SATLR in China's mainland,and then the assessment and validation for the GWR model were made.The spatial pattern of regression residuals which was identified by Moran's Index indicated that the GWR model was broadly reasonable for the estimation of SATLR.The small mean absolute error(MAE)in all months indicated that the GWR model had a strong predictive ability for the surface air temperature.The comparison with previous studies for the seasonal mean SATLR further evidenced the accuracy of the estimation.Therefore,the GWR method has potential application for estimating the SATLR in a large region with complex terrain and climatic condition.     

Using multilevel modeling and geographically weighted regression to identify spatial variations in the relationship between place-level disadvantages and obesity in Taiwan

Objectives

We examined whether and to what extent the relationship between township disadvantages and obesity varied across geographical areas.

Methods

A cross-sectional analysis of a population-based sample of Taiwanese adults (N = 25,985) from the 2005 Social Development Trend Survey on Health and Safety was performed. Multilevel models integrated with geographically weighted regressions were employed to analyze the spatially varying association between area disadvantages and obesity. The dependent variable was body mass index calculated from respondents’ self-reported weight and height. The key explanatory variable was a township disadvantage index made of poverty level, minority composition, and social disorder. Other individual socio-demographic characteristics were included to account for the compositional effect.

Results

The association between township disadvantages and elevated obesity risk in Taiwan was found to be area-specific. In contrast to results from the commonly used global regression, geographically weighted regression model showed that township disadvantages elevated obesity level only in certain areas.

Conclusions

We found heterogeneity of place-level determinants of obesity across geographical areas. Adoption of population approach to curb obesity would require area-specific strategies for most needed areas.     

Local least absolute deviation estimation of spatially varying coefficient models: robust geographically weighted regression approaches

The geographically weighted regression (GWR) has been widely applied to many practical fields for exploring spatial non-stationarity of a regression relationship. However, this method is inherently not robust to outliers due to the least squares criterion in the process of estimation. Outliers commonly exist in data sets and may lead to a distorted estimate of the underlying regression relationship. Using the least absolute deviation criterion, we propose two robust scenarios of the GWR approaches to handle outliers. One is based on the basic GWR and the other is based on the local linear GWR (LGWR). The proposed methods can automatically reduce the impact of outliers on the estimates of the regression coefficients and can be easily implemented with modern computer software for dealing with the linear programming problems. We then conduct simulations to assess the performance of the proposed methods and the results demonstrate that the methods are quite robust to outliers and can retrieve the underlying coefficient surfaces satisfactorily even though the data are seriously contaminated or contain severe outliers.