遇见数据集

Raw input data for "Transport modelling for dynamic urban climate studies: MATSDA-roads v2.0"

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Zenodo2025-12-08 更新2026-05-26 收录
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Description This repository contains the primary raw input data used in the London, UK, study by Ma et al. (2025) for generating the MATSDA-roads v2.0 travel database with Road-Node Creator 2.0. This includes the processing domain grid, road network data, average vehicle speed data, and reference routing data from Google Maps (Google Maps Directions API, https://developers.google.com/maps/documentation/directions, accessed 5 December 2025). In addition, processed geospatial data are also archived. Full references to the data given in: Ma et. al. (2025). Transport modelling for dynamic urban climate studies: MATSDA-roads v2.0. Geoscientific Model Development, submitted MATSDA-roads v2.0 model code and User Manual: https://doi.org/10.5281/zenodo.17736682 MATSDA-roads v2.0 input data processing for the London case: https://doi.org/10.5281/zenodo.17521112 MATSDA-roads v2.0 output routes for the London case: https://doi.org/10.5281/zenodo.17736562 Files in this archive Raw road network and speed data: Raw_input_data.zip, includes Processing domain grid (ESRI Shapefile) OS road network data MasterMap Highways (ESRI Geodatabase) Open Roads (ESRI Shapefile) Average vehicle speeds (CSV) Processed road network data (Auxiliary_input_data.zip), includes: Road_input (ESRI Shapefiles; merged with CSV speed data) Junction (ESRI Shapefile) Raw Google Maps (GM) reference routes (GM_routes_data_part#.zip; in 4 parts), includes: GM_route_<origin>_<destination>_driving_ best_guess_<alternative>_<time> (GEOJSON) e.g., GM_route_9220101_10230100_driving_best_guess_0_2024_12_24_07_05_48 (GEOJSON) Processed output GM routes (Processed_GM_routes.zip)

数据集说明 本存储库包含英国伦敦地区Ma等人(2025年)的研究中,用于配合道路节点创建器2.0(Road-Node Creator 2.0)生成MATSDA-roads v2.0出行数据库的核心原始输入数据。此类数据涵盖处理域网格、道路网络数据、车辆平均速度数据,以及源自谷歌地图的参考路径数据——谷歌地图路径规划API(Google Maps Directions API,https://developers.google.com/maps/documentation/directions,获取于2025年12月5日)。此外,本存档还收录已处理的地理空间数据。 数据完整参考文献:Ma等人(2025年)。《面向动态城市气候研究的交通建模:MATSDA-roads v2.0》,《Geoscientific Model Development》,已投稿 MATSDA-roads v2.0 模型代码与用户手册:https://doi.org/10.5281/zenodo.17736682 针对伦敦案例的MATSDA-roads v2.0输入数据处理脚本:https://doi.org/10.5281/zenodo.17521112 针对伦敦案例的MATSDA-roads v2.0输出路径数据集:https://doi.org/10.5281/zenodo.17736562 本存档包含的文件 原始道路网络与速度数据: Raw_input_data.zip 包含以下内容: - 处理域网格(ESRI形状文件(ESRI Shapefile)) - OS道路网络数据 - MasterMap Highways(ESRI地理数据库(ESRI Geodatabase)) - Open Roads(ESRI形状文件(ESRI Shapefile)) - 车辆平均速度数据(CSV格式) 已处理道路网络数据(Auxiliary_input_data.zip)包含以下内容: - Road_input(ESRI形状文件(ESRI Shapefile),已与CSV速度数据合并) - 路口数据(ESRI形状文件(ESRI Shapefile)) 原始谷歌地图(GM)参考路径数据(GM_routes_data_part#.zip,共4个分卷)包含以下内容: 文件命名格式为:GM_route_<起点>_<终点>_driving_best_guess_<备选方案编号>_<时间戳>(地理JSON(GEOJSON)格式),示例:GM_route_9220101_10230100_driving_best_guess_0_2024_12_24_07_05_48(地理JSON(GEOJSON)格式) 已处理的谷歌地图参考路径输出数据(Processed_GM_routes.zip)

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2025-12-08
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