High-high cluster and high-low outlier road intersections for motorcycle road traffic crashes resulting in injuries within the CoCT in 2017, 2018 and 2019

This dataset offers a detailed inventory of road intersections and their corresponding suburbs within Cape Town, meticulously curated to highlight instances of high motorcycle (Motorcycle: Above 125cc, Motorcycle: 125cc and under, Quadru-cycle, Motor Tricycle) crash counts that resulted in injuries (slight, serious, fatalities) observed in "high-high" cluster and "high-low" outlier fishnet grid cells across the years 2017, 2018 and 2019. To enhance its utility, the dataset meticulously colour-codes each month associated with elevated crash occurrences, providing a nuanced perspective. Furthermore, the dataset categorises road intersections based on their placement within "high-high" clusters (marked with pink tabs) or "high-low" outlier cells (indicated by red tabs). For ease of navigation, the intersections are further organised alphabetically by suburb name, ensuring accessibility and clarity.Data SpecificsData Type: Geospatial-temporal categorical data with numeric attributesFile Format: Word document (.docx)Size: 157 KBNumber of Files: The dataset contains a total of 158 road intersection records (11 "high-high" clusters and 147 "high-low" outliers)Date Created: 22nd May 2024MethodologyData Collection Method: The descriptive road traffic crash data per crash victim involved in the crashes was obtained from the City of Cape Town Network InformationSoftware: ArcGIS Pro, Open Refine, Python, SQLProcessing Steps: The raw road traffic crash data underwent a comprehensive refining process using Python software to ensure its accuracy and consistency. Following this, duplicates were eliminated to retain only one entry per crash incident. Subsequently, the data underwent further refinement with Open Refine software, focusing specifically on isolating unique crash descriptions for subsequent geocoding in ArcGIS Pro. Notably, during this process, only the road intersection crashes were retained, as they were the only incidents with spatial definitions.Once geocoded, road intersection crashes that involved either a motor tricycle, motorcycle above 125cc, motorcycle below 125cc and quadru-cycles and that were additionally associated with a slight, severe or fatal injury type were extracted so that subsequent spatio-temporal analyses would focus on these crashes only. The spatio-temporal analysis methods by which these motorcycle crashes were analysed included spatial autocorrelation, hotspot analysis, and cluster and outlier analysis. Leveraging these methods, road intersections with motorcycle crashes identified as either "high-high" clusters or "high-low" outliers were extracted for inclusion in the dataset.Geospatial InformationSpatial Coverage:West Bounding Coordinate: 18°20'EEast Bounding Coordinate: 19°05'ENorth Bounding Coordinate: 33°25'SSouth Bounding Coordinate: 34°25'SCoordinate System: South African Reference System (Lo19) using the Universal Transverse Mercator projectionTemporal InformationTemporal Coverage:Start Date: 01/01/2017End Date: 31/12/2019

本数据集收录开普敦市内道路交叉口及其对应郊区的详细清单，经精心编纂，重点呈现2017、2018、2019年间，在“高-高”聚类与“高-低”异常渔网格网单元内，涉及不同类型摩托车（125cc以上摩托车、125cc及以下摩托车、四轮摩托车、机动三轮车）且造成人员受伤（轻微、严重、死亡）的高事故次数案例。
为提升数据集实用性，本数据集对事故高发关联月份进行了细致的颜色编码，以提供更精细化的分析视角。此外，数据集还根据道路交叉口所属的“高-高”聚类（以粉色标签标记）或“高-低”异常单元（以红色标签标记）进行分类。为便于浏览检索，所有道路交叉口均按郊区名称的字母顺序进行排序，确保内容清晰易读。

### 数据详情
数据类型：包含数值属性的时空分类地理空间数据
文件格式：Word文档（.docx）
文件大小：157 KB
文件数量：本数据集共包含158条道路交叉口记录，其中11条属于“高-高”聚类，147条属于“高-低”异常值
创建日期：2024年5月22日

### 研究方法
数据采集方式：本研究从开普敦市网络信息系统获取了涉及事故受害者的道路交通事故描述性数据。
使用软件：ArcGIS Pro、Open Refine、Python、SQL
处理流程：首先通过Python软件对原始道路交通事故数据开展全面清洗，以确保数据准确性与一致性，同时删除重复条目，保留每起事故的唯一记录。随后使用Open Refine软件进行进一步整理，重点提取唯一的事故描述，用于后续在ArcGIS Pro中开展地理编码工作。在此过程中，仅保留具备明确空间定义的道路交叉口事故数据。
完成地理编码后，筛选出涉及机动三轮车、125cc以上摩托车、125cc以下摩托车及四轮摩托车，且造成轻微、严重或死亡伤害的道路交叉口事故，仅保留此类数据用于后续时空分析。本数据集采用的时空分析方法包括空间自相关、热点分析以及聚类与异常值分析。通过上述方法，提取出被识别为“高-高”聚类或“高-低”异常值的涉摩托车事故道路交叉口，纳入本数据集。

### 地理空间信息
空间覆盖范围：
西边界坐标：18°20'E
东边界坐标：19°05'E
北边界坐标：33°25'S
南边界坐标：34°25'S
坐标系：采用通用横轴墨卡托投影的南非参考系统（Lo19）

### 时间信息
时间覆盖范围：
起始日期：2017年1月1日
结束日期：2019年12月31日