Automatic (boosted) accessibility indices for Madrid (Spain)

This dataset is the result of a research for creating automatically accessibility indices from open sources, each index is created through a gravitational index and applies to a type of opportunity. The dataset has been designed for its use in House Price models and it is delivered at Uber's H3 grid level (resolutions 9 and 10). Accessibility indices have been calculated for two modes of transport: car and walk More informacion and resources at https://github.com/davidreyblanco/accessibility Data folder contains csv files with indicator and their corresponding H3 indices and geometries, there are two sets one with CAR indices and a second one with WALK mode indices. Indices categories Indices have different nature and source, the following table contains which indices are available for each transportation mode and the source to build it. Walk indices are calculated for each H3 in the city at 10 resolution while Car are at 9th level.

本数据集为一项基于开源数据源自动生成可达性指数（accessibility indices）的研究成果，每项指数均通过引力指数（gravitational index）构建，且适配特定类型的机会场景。本数据集专为房价模型（House Price models）设计开发，数据以优步（Uber）的H3网格（H3 grid）为粒度进行交付，支持分辨率9与分辨率10两级网格。研究针对驾车与步行两种交通模式计算了可达性指数。更多信息与资源可访问：https://github.com/davidreyblanco/accessibility。数据文件夹中包含存储有各类指标、对应H3网格编码及几何信息的CSV文件，分为两个数据集：其一包含驾车模式可达性指数，其二包含步行模式可达性指数。可达性指数具备不同的属性与来源，下表列出了各交通模式下可用的指数类型及其构建来源。步行模式指数针对城市内所有分辨率为10级的H3网格计算得出，驾车模式指数则对应分辨率为9级的H3网格。