共查询到20条相似文献，搜索用时 31 毫秒
1.
Binbin Lu Chris Brunsdon Martin Charlton Paul Harris 《International journal of geographical information science》2017,31(5):982-998
Geographically weighted regression (GWR) is an important local technique to model spatially varying relationships. A single distance metric (Euclidean or non-Euclidean) is generally used to calibrate a standard GWR model. However, variations in spatial relationships within a GWR model might also vary in intensity with respect to location and direction. This assertion has led to extensions of the standard GWR model to mixed (or semiparametric) GWR and to flexible bandwidth GWR models. In this article, we present a strongly related extension in fitting a GWR model with parameter-specific distance metrics (PSDM GWR). As with mixed and flexible bandwidth GWR models, a back-fitting algorithm is used for the calibration of the PSDM GWR model. The value of this new GWR model is demonstrated using a London house price data set as a case study. The results indicate that the PSDM GWR model can clearly improve the model calibration in terms of both goodness of fit and prediction accuracy, in contrast to the model fits when only one metric is singly used. Moreover, the PSDM GWR model provides added value in understanding how a regression model’s relationships may vary at different spatial scales, according to the bandwidths and distance metrics selected. PSDM GWR deals with spatial heterogeneities in data relationships in a general way, although questions remain on its model diagnostics, distance metric specification, and computational efficiency, providing options for further research. 相似文献
2.
Taylor Oshan Levi John Wolf Wei Kang Ziqi Li Hanchen Yu 《International journal of geographical information science》2019,33(7):1289-1299
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. 相似文献
3.
Scientific interpretation of the relationships between agricultural landscape patterns and urbanization is important for ecological planning and management. Ordinary least squares (OLS) regression is the primary statistical method in previous studies. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between several urbanization indicators (urbanization intensity index, distance to urban centers and distance to road) and changes in metrics describing agricultural landscape patterns (total area, patch density, perimeter area ratio distribution and aggregation index) at two block scales (5 km and 10 km). Results denoted that GWR was more powerful than OLS in interpreting relationships between agricultural landscape patterns and urbanization, since GWR was characterized by higher adjust R2, lower Akaike Information Criterion values and reduced spatial autocorrelations in model residuals. Character and strength of the relationships identified by GWR varied spatially. In addition, GWR results were scale-dependent and scale effects were particularly significant in three aspects: kernel bandwidth of weight determination, block scale of pattern analysis, and window size of local variance analysis. Homogeneity and heterogeneity in the relationships between agricultural landscape patterns and urbanization were subject to the coupled influences of the three scale effects. We argue that the spatially varying relationships between agricultural landscape patterns and urbanization are not accidental but nearly universal. This study demonstrated that GWR has the potential to provide references for ecological planners and managers to address agricultural landscapes issues at all scales. 相似文献
4.
Land price plays an important role in guiding land resource allocation for urban planning and development, particularly in big cities of fast developing countries where infrastructures and populations change frequently. Therefore, detecting spatially implicit information in the spatial pattern of relationships between land price and related impact factors is critical. Geographically weighted regression (GWR) analysis was conducted in this study for the purpose in Wuhan, China, by using a 10-year panel data set of residential land price. Based on twelve factors in three aspects (land attributes, location factors and neighborhood attributes), an evaluation index system of resident land price was established. The spatial distributions of estimated coefficients and pseudo t-values of three major explanatory variables (floor area ratio, distance to nearest center business district (CBD) and distance to nearest lake), obtained from GWR analysis, indicated that their relationships of the impact factors with land price are spatially non-stationary. The positive impact of floor area ratio on land price is more significant in highly developed areas than in less developed areas. Conversely, the negative impact of distance to nearest CBD on land price is larger in highly developed areas than in less developed areas. Moreover, wealthier dwellers may be willing to pay a higher price for a good lake view (especially views of small lakes), but infrastructure barriers (near some large lakes) cause negative effect. The outputs of this study, which provide detailed information on the relationships between land price and impact factors in local areas, are promising for urban planners to scientifically evaluate land price and make area-specific strategies. 相似文献
5.
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 总被引：4，自引：3，他引：1
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。 相似文献
6.
The real estate market has long provided an active application area for spatial–temporal modeling and analysis and it is well known that house prices tend to be not only spatially but also temporally correlated. In the spatial dimension, nearby properties tend to have similar values because they share similar characteristics, but house prices tend to vary over space due to differences in these characteristics. In the temporal dimension, current house prices tend to be based on property values from previous years and in the spatial–temporal dimension, the properties on which current prices are based tend to be in close spatial proximity. To date, however, most research on house prices has adopted either a spatial perspective or a temporal one; relatively little effort has been devoted to situations where both spatial and temporal effects coexist. Using ten years of house price data in Fife, Scotland (2003–2012), this research applies a mixed model approach, semiparametric geographically weighted regression (GWR), to explore, model, and analyze the spatiotemporal variations in the relationships between house prices and associated determinants. The study demonstrates that the mixed modeling technique provides better results than standard approaches to predicting house prices by accounting for spatiotemporal relationships at both global and local scales. 相似文献
7.
都市新区住宅地价空间异质性驱动因素研究 ——基于空间扩展模型和GWR模型的对比 总被引：2，自引：2，他引：0
以南京市江宁区为例,基于2004~2011年住宅用地出让数据,利用空间扩展模型和GWR模型对都市新区住宅地价空间异质性及其驱动因素进行研究。结果表明：① 空间扩展模型与GWR模型分别可解释采样区63%、61%的住宅地价变化,较全局回归模型(47%)有显著提升,更有利于研究土地市场的空间异质性。② 空间扩展模型可有效表征各解释变量及其交互项对住宅地价作用的空间结构总体趋势,其拟合效果相对较优。GWR模型则在局部参数估计方面存在优势,借助GIS可将各变量的地价作用模式可视化,从而比空间扩展模型更能有效刻画住宅地价影响因素的空间非平稳性特征,各因素对地价的平均边际贡献排序为水域> 地铁> 大学园区> CBD> 商业网点> 医院,且商业网点、 医院系数值具有方向差异性。③ 距地铁站点、水域、大学园区以及CBD的距离是研究区住宅地价的关键驱动因素,各自存在特有的地价空间作用模式,可为研究区住宅土地市场细分提供科学依据。 相似文献
8.
Binbin Lu Chris Brunsdon Martin Charlton Paul Harris 《International journal of geographical information science》2019,33(7):1300-1312
In this article, we respond to ‘A comment on geographically weighted regression with parameter-specific distance metrics’ by Oshan et al. (2019), published in this journal, where several concerns on the parameter-specific distance metric geographically weighted regression (PSDM GWR) technique are raised. In doing so, we review the developmental timeline of the multiscale geographically weighed regression modelling framework with related and equivalent models, including flexible bandwidth GWR, conditional GWR and PSDM GWR. In our response, we have tried to answer all the concerns raised in terms of applicability, veracity, interpretability and computational efficiency of the PSDM GWR model. 相似文献
9.
Ziqi Li A. Stewart Fotheringham Wenwen Li Taylor Oshan 《International journal of geographical information science》2019,33(1):155-175
Geographically Weighted Regression (GWR) is a widely used tool for exploring spatial heterogeneity of processes over geographic space. GWR computes location-specific parameter estimates, which makes its calibration process computationally intensive. The maximum number of data points that can be handled by current open-source GWR software is approximately 15,000 observations on a standard desktop. In the era of big data, this places a severe limitation on the use of GWR. To overcome this limitation, we propose a highly scalable, open-source FastGWR implementation based on Python and the Message Passing Interface (MPI) that scales to the order of millions of observations. FastGWR optimizes memory usage along with parallelization to boost performance significantly. To illustrate the performance of FastGWR, a hedonic house price model is calibrated on approximately 1.3 million single-family residential properties from a Zillow dataset for the city of Los Angeles, which is the first effort to apply GWR to a dataset of this size. The results show that FastGWR scales linearly as the number of cores within the High-Performance Computing (HPC) environment increases. It also outperforms currently available open-sourced GWR software packages with drastic speed reductions – up to thousands of times faster – on a standard desktop. 相似文献
10.
Binbin Lu Martin Charlton Chris Brunsdon Paul Harris 《International journal of geographical information science》2016,30(2):351-368
In this study, the geographically weighted regression (GWR) model is adapted to benefit from a broad range of distance metrics, where it is demonstrated that a well-chosen distance metric can improve model performance. How to choose or define such a distance metric is key, and in this respect, a ‘Minkowski approach’ is proposed that enables the selection of an optimum distance metric for a given GWR model. This approach is evaluated within a simulation experiment consisting of three scenarios. The results are twofold: (1) a well-chosen distance metric can significantly improve the predictive accuracy of a GWR model; and (2) the approach allows a good approximation of the underlying ‘optimal distance metric’, which is considered useful when the ‘true’ distance metric is unknown. 相似文献
11.
中国省域犯罪率影响因素的空间非平稳性分析 总被引：4，自引：2，他引：2
收入差距和流动人口是影响犯罪率的两个重要因素, 以往研究基于OLS模型, 在假设地域空间为均质的前提下分析其对犯罪率的影响, 但现实世界的空间单元往往难以满足“均质”的假设, 多数表现为“空间异质”。以OLS计量空间异质会造成计量结果出现偏差, 同时无法了解不同空间单元的不同影响。而地理加权回归模型通过将空间结构嵌入线性回归模型中, 很好的解决了空间异质的计量问题。利用地理加权回归模型研究2008 年中国大陆省域单元犯罪率的影响因素, 结果表明:① 犯罪率的影响因素表现出空间非平稳性, 流动人口与犯罪率显著相关, 但各个省份相关程度并不相同, 影响关系随空间位置变化而变化;② 地理加权回归模型的计量精度和拟合度比OLS模型有大幅提高 相似文献
12.
Accurately mapping the spatial distribution of soil total nitrogen is important to precision agriculture and environmental management. Geostatistical methods have been frequently used for predictive mapping of soil properties. Recently, a local regression method, geographically weighted regression (GWR), got the attention of environmentalists as an alternative in spatial modeling of environmental attributes, due to its capability of incorporating various auxiliary variables with spatially varied correlation coefficients. The objective of this study is to compare GWR and ordinary cokriging (OCK) in predictive mapping of soil total nitrogen (TN) using multiple environmental variables. 353 soil Samples within the surface horizon of 0–20 cm in a study area were collected, and their TN contents were measured for calibrating and validating the GWR and OCK interpolations. The environmental variables finally chosen as auxiliary data include elevation, land use types, and soil types. Results indicate that, although OCK is slightly better than GWR in global accuracy of soil TN prediction (the adjusted R2 for GWR and OCK are 0.5746 and 0.6858, respectively), the soil TN map interpolated by GWR shows many details reflecting the spatial variations of major auxiliary variables while OCK smoothes out almost all local details. Geographically weighted regression could account for both the spatial trend and local variations, whilst OCK had difficulties to capture local variations. It is concluded that GWR is a more promising spatial interpolation method compared to OCK in predicting soil TN and potentially other soil properties, if a suitable set of auxiliary variables are available and selected. 相似文献
13.
基于时空窗口改进的时空加权回归分析——以湖北省黄石市住房价格为例 总被引：3，自引：3，他引：0
针对地理加权回归(GWR)模型不能有效处理样本数据空间自相关性这一问题,构造局部时空窗口统计量,尝试改进时空加权回归(GTWR)模型。定义多时空窗口的概念,给出其选取、计算和验证方法;计算时空窗口包含的各样本点的被解释变量平均值,与样本拟合点的被解释变量值的比值,作为新的解释变量,构建改进的时空加权回归(IGTWR)模型。以土地稀缺、多中心、资源型城市——湖北省黄石市为例,收集2007~2012年商品住宅成交价格1.93万个数据和398个楼栋样本点,选取小区等级、绿化率、楼栋总层数、容积率、距区域中心距离和销售年份6个解释变量,分别利用常规线性回归(OLS)、GWR、GTWR和IGTWR方法进行回归分析。模型结果表明：计算Moran’s I指数和分析时间序列的自相关性,能确定时空窗口的大小和数量的选取;IGTWR模型和各变量的回归统计均通过0.05的显著性水平检验,有关解释变量的系数估计值在空间分布上能合理解释;GWR拟合结果优于OLS,GTWR优于GWR,而IGTWR拟合精度最好。与GTWR模型分析相比, IGTWR模型R2从0.877提升到0.919,而AICc、残差方(RSS)和均方差(MSE)分别从6 226、49 996 201和354.427下降到6 206、32 327 472和284.969。案例研究表明：IGTWR能够表达一定时空范围的时空自相关特征,减小了估计误差,提高了回归拟合精度。 相似文献
14.
Quanhua Dong 《International journal of geographical information science》2018,32(2):302-323
Geometric buffers are important for spatial analysis in many applications of geographic information systems (GISs), such as environmental measurement and management, human health, urban planning, etc. Geometric buffer generation algorithms are well studied in the Euclidean space where the buffer distance is measured by Euclidean metrics; however, very few algorithms are available for generating geometric buffers on the terrain surface in a virtual globe where the buffer distance is measured by geodesic metrics. This paper proposes a tile-based method for geodesic buffer generation according to the characteristics of a virtual globe. It extends the vector tile model (VTM) to organize terrain and vector data, and the XYH algorithm is improved to build geodesic distance fields for terrain meshes. Based on the data organization and the improved XYH algorithm, a geodesic buffer is generated via three main steps: selecting and assembling tiles, updating geodesic distance fields and tracing the boundaries of buffer zones. This method is implemented with multi-scale terrain and vector data, and the experimental results show that it is valid and exact and can be applied in practical applications. 相似文献
15.
The main aim of this article is to analyze the relationships between the spatial patterns of residential burglaries and the socioeconomic characteristics of neighborhoods in London, Ontario. Relative risk ratios are applied as a measure of the intensity of residential burglary. The variation in the risks of burglary is modeled as a function of contextual neighborhood variables. Following a conventional (global) regression analysis, spatial variations in the relationships are examined using geographically weighted regression (GWR). The GWR results show that there are significant local variations in the relationships between the risk of residential burglary victimization and the average value of dwellings and percentage of the population in multifamily housing. The results are discussed in the context of four hypotheses, which may explain geographical variations in residential burglary. The practical implication of the GWR analysis is that different crime prevention policies should be implemented in different neighborhoods of the city. 相似文献
16.
Dipto Sarkar Clio Andris Colin A. Chapman Raja Sengupta 《International journal of geographical information science》2019,33(5):1017-1039
Social Network Analysis offers powerful tools to analyze the structure of relationships between a set of people. However, the addition of spatial information poses new challenges, as nodes are embedded simultaneously in network space and Euclidean space. While nearby nodes may not form social ties, ties may exist at a distance, a configuration ill-suited for traditional spatial metrics that assume adjacent objects are related. As such, there are relatively few metrics to describe these nuanced situations. We advance the burgeoning field of spatial social network analysis by introducing a set of new metrics. Specifically, we introduce the spatial social network schema, tuning parameter and the flattening ratio, each of which leverages the notion of ‘distance’ to augment insights obtained by relying on topology alone. These methods are used to answer the questions: What is the social and spatial structure of the network? Who are the key individuals at different spatial scales? We use two synthetic networks with properties mimicking the ones reported in the literature as validation datasets and a case study of employer–employee network. The methods characterize the employer–employee as spatially loose with predominantly local connections and identify key individuals responsible for keeping the network connected at different spatial scales. 相似文献
17.
Bo Huang Bo Wu Michael Barry 《International journal of geographical information science》2013,27(3):383-401
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. 相似文献
18.
大连城市绿地可达性对房价影响的差异性分析 总被引：6，自引：5，他引：1
研究房价、遥感影像等多源数据,采用邻域分析法和地理加权回归模型分析大连市中山区绿地可达性及其与房价之间的空间相关性。结果表明：① 房价均价14 745.35元/m2,呈环状分布,由沿海向内陆衰减、桂林街道起中心向外围递减;② 研究区内可达性最好的绿地类型是街旁绿地,绿地可达性总体水平最高街道是桂林街道;公园绿地可达性最好的住宅区分布在昆明街道和桃源街道,街旁绿地可达性最好的住宅区分布在桂林街道,附属绿地可达性最好的分布在老虎滩街道,其他绿地可达性最好的分布在桃源街道。③ 不同类型绿地可达性对房价影响作用程度递减排序为：附属绿地、街旁绿地、公园绿地和其他绿地;附属绿地、街旁绿地和其他绿地与房价呈现空间正相关,随着到达绿地距离降低,房价呈现增长趋势;公园绿地与房价呈现负相关,随着到达公园绿地的距离降低,房价呈现衰减趋势。 相似文献
19.
北京市出租车运量分布的时空格局及生成机制 总被引：1，自引：0，他引：1
出租车是城市交通的重要组成部分,对其精细化的管控需要理解运量分布的时空特征和生成机制。通过北京市出租车大数据,采用系统聚类法将其15分钟时间片段归并为空间分布相似的时段,刻画出运量分布的时空格局,进而采用地理加权回归模型分析了生成机制。本研究揭示的出租车运量分布变化的时间点并不完全对应传统的整时点;各时段运量均呈现空间集聚的特征,但集聚的位置、面积明显不同,工作日不同时段运量集聚程度的差异较周末更大;不同时段出租车运量的影响因子有所差异,其中商业设施、房价、地铁和公交站密度、道路密度等因子通常较为显著。研究结果对时空上更精细的出租车运量预测、出租车分区分时段的政策管制和规划管理具有启示意义。 相似文献
20.
Location factors are vital elements for describing housing price variation. However, limited studies have explicitly illustrated the relationship between urban design and the heterogeneity of housing price patterns. This article specifically evaluates how the interactions between the spatial layouts and land-use system at various scales through street network affect the valuation of the residential properties and the segmentation of housing markets in a network-based Mixed-scale Hedonic Model (MHM) where the submarkets pattern are determined and annotated by the spatially varying estimates on streets. The application of the delivered method in the case of Shanghai City, China, confirms the necessity of using the non-Euclidean distance metric and represent the coexistence between the stationarity and the non-stationarity of the introduced street accessibility variables. The results provide evidence that the impacts of street accessibility measures on the local levels showcase significant spatial variation. It is common for all the places that the properties located on the streets with the higher levels of angular closeness, smaller values of angular betweenness and longer angular distance to the nearby land-uses at the larger scales will be bided higher. It is proven that our delineation of submarket performs better in prediction accuracy than the traditional submarket specifications. The detected submarkets pattern yields that reachable land-use diversity at the pedestrian level is not a preferred factor in the housing submarkets located in the developed city centres. The signs of the price effects of the angular distance to local land-uses distinguish the developing submarkets as two main groups with different degrees of geometrical walkability. It is suggestive that continuously developing pedestrian-oriented neighbours in the walkable areas could contribute to decelerating the growth of house price in Chinese cities. The productions of this study can enrich the understanding of the socioeconomic effects of urban design with greater spatial precision across submarkets. 相似文献