Spatial crime distribution and prediction for sporting events using social media     

Alina Ristea  Mohammad Al Boni  Bernd Resch  Matthew S. Gerber  Michael Leitner 《International journal of geographical information science》2020,34(9):1708-1739

ABSTRACT

Sporting events attract high volumes of people, which in turn leads to increased use of social media. In addition, research shows that sporting events may trigger violent behavior that can lead to crime. This study analyses the spatial relationships between crime occurrences, demographic, socio-economic and environmental variables, together with geo-located Twitter messages and their ‘violent’ subsets. The analysis compares basketball and hockey game days and non-game days. Moreover, this research aims to analyze crime prediction models using historical crime data as a basis and then introducing tweets and additional variables in their role as covariates of crime. First, this study investigates the spatial distribution of and correlation between crime and tweets during the same temporal periods. Feature selection models are applied in order to identify the best explanatory variables. Then, we apply localized kernel density estimation model for crime prediction during basketball and hockey games, and on non-game days. Findings from this study show that Twitter data, and a subset of violent tweets, are useful in building prediction models for the seven investigated crime types for home and away sporting events, and non-game days, with different levels of improvement.  相似文献   

u‐p semi‐Lagrangian reproducing kernel formulation for landslide modeling          下载免费PDF全文

Thanakorn Siriaksorn  Sheng‐Wei Chi  Craig Foster  Ashkan Mahdavi 《国际地质力学数值与分析法杂志》2018,42(2):231-255

This paper presents a u‐p (displacement‐pressure) semi‐Lagrangian reproducing kernel (RK) formulation to effectively analyze landslide processes. The semi‐Lagrangian RK approximation is constructed based on Lagrangian discretization points with fixed kernel supports in the current configuration. As a result, it tracks state variables at discretization points while allowing extreme deformation and material separation that is beyond the capability of Lagrangian formulations. The u‐p formulation following Biot theory is incorporated into the formulation to describe poromechanics of saturated geomaterials. In addition, a stabilized nodal integration method to ensure stability of the domain integration and kernel contact algorithms to model contact between bodies are introduced in the u‐p semi‐Lagrangian RK formulation. The proposed method is verified with several numerical examples and validated with an experimental result and the field data of an actual landslide.  相似文献   

基于半参数最小二乘核估计的卫星精密钟差预报方法     

徐长海  许东升 《测绘工程》2017,26(1)

研究半参数最小二乘核估计模型在精密钟差预报中的应用问题,提出一种基于时间自变量差值累加的窗宽参数计算模型,并通过实验验证该模型的有效性,讨论在不同预报时间长度和已知数据量的情况下模型预报精度。实验表明,与常规模型相比,半参数最小二乘核估计模型在预报精度与稳定性方面都取得较好的效果,可以满足精密单点定位对于精密钟差预报的精度要求。研究成果对于精密单点定位技术的推广普及具有一定的促进作用。  相似文献   

A new kernel method for hyperspectral image feature extraction     

Bin Zhao  Wenzhi Liao  Bing Zhang 《地球空间信息科学学报》2017,20(4):309-318

Abstract

Hyperspectral image provides abundant spectral information for remote discrimination of subtle differences in ground covers. However, the increasing spectral dimensions, as well as the information redundancy, make the analysis and interpretation of hyperspectral images a challenge. Feature extraction is a very important step for hyperspectral image processing. Feature extraction methods aim at reducing the dimension of data, while preserving as much information as possible. Particularly, nonlinear feature extraction methods (e.g. kernel minimum noise fraction (KMNF) transformation) have been reported to benefit many applications of hyperspectral remote sensing, due to their good preservation of high-order structures of the original data. However, conventional KMNF or its extensions have some limitations on noise fraction estimation during the feature extraction, and this leads to poor performances for post-applications. This paper proposes a novel nonlinear feature extraction method for hyperspectral images. Instead of estimating noise fraction by the nearest neighborhood information (within a sliding window), the proposed method explores the use of image segmentation. The approach benefits both noise fraction estimation and information preservation, and enables a significant improvement for classification. Experimental results on two real hyperspectral images demonstrate the efficiency of the proposed method. Compared to conventional KMNF, the improvements of the method on two hyperspectral image classification are 8 and 11%. This nonlinear feature extraction method can be also applied to other disciplines where high-dimensional data analysis is required.  相似文献   

径向基核函数在DEM内插中的适用性分析     

和娴  董有福  王玉成 《测绘科学》2017,42(2)

针对空间插值中不同核函数在不同地形条件下的适用性问题,该文选取了平原、丘陵和山地3种地貌类型区,采用5种常用的径向基核函数分别生成若干分辨率的DEM,通过高程统计参数、空间自相关特性和等高线套合分析DEM的精度差异。综合而言,平原地区中多重对数函数、多重二次曲面函数、反多重二次曲面函数和自然三次样条曲面函数插值效果没有显著差别,薄板样条曲面函数相对略差;丘陵地区选择多重二次曲面函数和薄板样条曲面函数插值效果最好,多重对数函数和自然三次样条曲面函数次之,反多重二次曲面函数最差;山地地区采用多重二次曲面函数插值能取得较为满意的效果,其他4种核函数逊之。  相似文献   

武汉市城市空间集聚要素的分布特征与模式   总被引：12，自引：3，他引：9  

焦利民  李泽慧  许刚  张博恩  董婷  谷岩岩 《地理学报》2017,72(8):1432-1443

不同城市要素的集聚现象具有不同的空间模式,定量化研究城市要素集聚模式的差异和联系对于理解城市发展机理、合理制定城市规划具有重要意义。本文以武汉市为例,获取不透水表面、商业服务业网点（POI）、人口、容积率、城市道路等城市要素数据;采用核密度估计法识别城市主次中心,从城市要素的分布形态、集聚程度、集聚模式等来研究城市要素的空间分布格局特征。研究发现,武汉市呈现“一主七副”的多中心结构,各城市要素从城市中心向外呈反S型的圈层递减。采用集聚度指数衡量城市要素的集聚水平,结果显示商业POI、人口密度的集聚程度最大,其次是容积率、道路密度、不透水表面占比。高度集聚的商业POI、人口密度呈现出点状模式与带状模式相结合的分布模式,中度集聚的道路密度、容积率呈现点状模式、环状模式与轴状模式相结合的分布模式,低度集聚的不透水表面密度主要表现为环状模式。城市中心的吸引、立体空间开发等促进了城市要素的向心集聚,交通干线、稀缺景观资源的廊道效应等重塑了城市要素的空间分布形态。  相似文献   

Testing spatial heterogeneity in geographically weighted principal components analysis     

Javier Roca-Pardiñas  Tomás R. Cotos-Yáñez  Rubén Pérez-Álvarez 《International journal of geographical information science》2017,31(4):676-693

We propose a method to evaluate the existence of spatial variability in the covariance structure in a geographically weighted principal components analysis (GWPCA). The method, that is extensive to locally weighted principal components analysis, is based on performing a statistical hypothesis test using the eigenvectors of the PCA scores covariance matrix. The application of the method to simulated data shows that it has a greater statistical power than the current statistical test that uses the eigenvalues of the raw data covariance matrix. Finally, the method was applied to a real problem whose objective is to find spatial distribution patterns in a set of soil pollutants. The results show the utility of GWPCA versus PCA.  相似文献   

武汉市道路结构与商业集聚空间关联分析   总被引：1，自引：0，他引：1  

韩宇瑶  焦利民  许刚 《地理科学进展》2017,36(11):1349-1358

城市道路结构是影响城市商业集聚的重要因素,研究二者之间的关联对于商业布局和道路规划具有重要支撑作用。本文以武汉市都市发展区为例,运用空间句法模型计算道路结构指标,采用GIS核密度法计算2014年商业兴趣点(C-POI)密度以分析商业集聚的空间结构,通过双变量相关分析道路结构变量与商业集聚程度的关联关系。结果显示：①道路结构指标中,与商业集聚关联最强的是道路全局集成度。在各商业类型中,与道路结构相关程度最大的是金融保险服务集聚。②道路连接值和全局集成度值分别与商业POI密度呈显著正相关,呈现“高—高”集聚的空间关联模式;总深度值与商业POI密度呈现显著负相关,呈现“高—低”集聚的空间关联模式;商业POI密度随控制值升高呈现先升高后降低的趋势。③商业集聚分布呈现为“核心—过渡区—边缘区”的多核心多层次结构,“高—高”集聚与“高—低”集聚模式集中分布于“核心”及其附近的“过渡区”。  相似文献   

辽宁省水足迹强度差异及空间关联格局分析     

盖美  吴慧歌  曲本亮 《地域研究与开发》2017,36(1)

基于辽宁省14个城市的水足迹面板数据,计算2004—2013年辽宁各城市的水足迹和水足迹强度,辽宁省水足迹强度明显下降,各城市间水足迹强度存在很大差异。采用核密度估计模型、基尼系数、锡尔指数分析人均水足迹和水足迹强度的动态演变规律,辽宁省水足迹强度差异在不断缩小且有收敛趋势。空间自相关检验发现,辽宁省水足迹强度存在显著空间自相关关系,高高集聚区域主要分布在辽宁省经济欠发达的城市,如阜新、朝阳、葫芦岛;低低集聚区域主要集中在辽宁省经济水平相对发达的城市,如大连、鞍山、盘锦;辽宁省水足迹强度存在显著空间效应,其中人均水足迹对水足迹强度的影响最大。  相似文献   

基于核半监督判别分析的高光谱影像特征提取     

张鹏强  谭熊  余旭初  魏祥坡  薛志祥 《测绘科学技术学报》2016,(3)

针对高光谱影像特征提取中地物类别训练样本获取代价较高的情况,在线性判别分析的基础上,结合核方法和半监督学习理论,提出了一种基于核半监督判别分析(KSDA)的高光谱影像特征提取方法。该方法同时利用少量已知类别和大量未知类别样本数据进行模型的学习和训练。通过OMIS高光谱影像数据实验表明:在少量已知类别训练样本的条件下,经KSDA特征提取的样本数据在特征空间中能更好地聚集成团,且类别之间的距离较大,增加了类别之间的可分性,得到了较高的分类精度;同时,提取的特征影像能够较好地区分各种地物类别。  相似文献