LDU | Spain | 2020 Reachable Population Counts (by age and sex) within a 60 Min timeframe by Car | 72762 Origins

This is NOT a raw population dataset. We use our proprietary stack to combine detailed 'WorldPop' UN-adjusted, sex and age structured population data with a spatiotemporal OD matrix. The result is a dataset where each record indicates how many people can be reached in a fixed timeframe (60 Mins in this case) from that record's location. The dataset is broken down into sex and age bands at 5 year intervals, e.g - male 25-29 (m_25) and also contains a set of features detailing the representative percentage of the total that the count represents. The dataset provides 72762 records, one for each sampled location. These are labelled with a h3 index at resolution 7 - this allows easy plotting and filtering in Kepler.gl / Deck.gl / Mapbox, or easy conversion to a centroid (lat/lng) or the representative geometry of the hexagonal cell for integration with your geospatial applications and analyses. A h3 resolution of 7, is a hexagonal cell area equivalent to: - ~1.9928 sq miles - ~5.1613 sq km Higher resolutions or alternate geographies are available on request. More information on the h3 system is available here: https://eng.uber.com/h3/ WorldPop data provides for a population count using a grid of 1 arc second intervals and is available for every geography. More information on the WorldPop data is available here: https://www.worldpop.org/ One of the main use cases historically has been in prospecting for site selection, comparative analysis and network validation by asset investors and logistics companies. The data structure makes it very simple to filter out areas which do not meet requirements such as: - being able to access 70% of the Spanish population within 4 hours by Truck and show only the areas which do exhibit this characteristic. Clients often combine different datasets either for different timeframes of interest, or to understand different populations, such as that of the unemployed, or those with particular qualifications within areas reachable as a commute.

本数据集并非原始人口数据集。我们依托专有技术栈，将经联合国调整的详细世界人口项目（WorldPop）分性别、分年龄结构人口数据，与时空起讫点（OD）矩阵进行融合。
最终生成的数据集中，每条记录均标注了从该记录对应位置出发，在固定时长（本案例中为60分钟）内可抵达的人口数量。
该数据集按5年间隔划分性别与年龄组别，例如男性25-29岁组（记为m_25），同时包含一组特征，用以说明该统计值占总统计人口的代表性占比。
本数据集共包含72762条记录，对应每个采样位置。每条记录均配有分辨率为7级的H3六边形格网索引——这使得其可直接在Kepler.gl、Deck.gl、Mapbox中进行便捷绘图与筛选，也可轻松转换为质心（经纬度）或六边形格网的代表几何形状，以适配各类地理空间应用与分析。
H3分辨率7级对应的六边形格网面积约为：1.9928平方英里，或5.1613平方公里。可根据需求提供更高分辨率或其他地理区域的数据集。有关H3编码系统的更多信息，请访问：https://eng.uber.com/h3/
世界人口项目（WorldPop）数据采用1弧秒间隔的网格进行人口统计，覆盖全球所有地理区域。有关WorldPop数据的更多信息，请访问：https://www.worldpop.org/
从历史应用来看，该数据集主要服务于资产投资者与物流企业的选址勘探、对比分析及网络验证工作。
依托该数据集的结构，用户可便捷筛选出不符合预设条件的区域——例如筛选出可在4小时内通过卡车抵达西班牙70%人口的区域，并仅展示符合该特征的范围。
客户常将多组数据集结合使用，既可针对不同的关注时段开展分析，也可针对特定人群展开研究——例如通勤可达范围内的失业群体或具备特定资质的人群。