five

U.S. Community Water Systems Service Boundaries, v3.0.0

收藏
DataONE2022-11-01 更新2024-06-08 收录
下载链接:
https://search.dataone.org/view/sha256:255543c63c010760308ca94aa16ebe1f52294c7381d1a50f50c94fb984519805
下载链接
链接失效反馈
官方服务:
资源简介:
This is a layer of water service boundaries for 45,973 community water systems that deliver tap water to 307.7 million people in the US. This amounts to 97% of the population reportedly served by active community water systems and 93% of active community water systems. The layer is based on multiple data sources and a methodology developed by SimpleLab and collaborators called a Tiered, Explicit, Match, and Model approach–or TEMM, for short. The name of the approach reflects exactly how the nationwide data layer was developed. The TEMM is composed of three hierarchical tiers, arranged by data and model fidelity. First, we use explicit water service boundaries provided by states. These are spatial polygon data, typically provided at the state-level. We call systems with explicit boundaries Tier 1. In the absence of explicit water service boundary data, we use a matching algorithm to match water systems to the boundary of a town or city (Census Place TIGER polygons). When multiple water systems match to the same TIGER boundary, we employ a \"best match\" algorithm that assigns one water system to one TIGER place based on features like population served and other locational information about the water system. Finally, in the absence of an explicit water service boundary (Tier 1) or a TIGER place polygon match (Tier 2), a statistical model trained on explicit water service boundary data (Tier 1) is used to estimate a reasonable radius at provided water system centroids, and model a spherical water system boundary (Tier 3). Water system centroids are taken from the ECHO database; however, where a system centroid is labeled as a county or state centroid, we take several steps to assign a better centroid (using sources like UCMR or TIGER). A summary of the systems and population assigned to different tiers is as follows: Population coverage rates per Tier, for systems with population reported: - Tier 1: 49.3% population covered (155,869,771 people) - Tier 2: 35.13% population covered (111,074,087 people) - Tier 3: 12.9% population covered (40,771,645 people) Active community water systems coverage rates per Tier: - Tier 1: 35.7% system covered (17645 systems) - Tier 2: 22.42% system covered (11079 systems) - Tier 3: 34.9% system covered (17249 systems) - No Tier/Geometry: 6.98% system covered (3451 systems) Several limitations to this data exist–and the layer should be used with these in mind. The case of assigning a Census Place TIGER polygon to the \"best match\" water system first introduced in v2.0.0 requires further validation. Tier 3 boundaries have modeled radii stemming from a lat/long centroid of a water system facility; but the underlying lat/long centroids for water system facilities are of variable quality. It is critical to evaluate the \"geometry quality\" column (included from the EPA ECHO data source) when looking at Tier 3 boundaries; fidelity is very low when geometry quality is a county or state centroid– but we did not exclude the data from the layer. Since v 2.0.0 we have improved the percentage of Tier 3 geometries with state centroids and county centroids from 50% of Tier 3 boundaries to 30% of Tier 3 boundaries. Missing water systems are typically those without a centroid, in a U.S. territory, or missing population and connection data. Finally, Tier 1 systems are assumed to be high fidelity, but rely on the accuracy of state data collection and maintenance. Changelog: # 3.0.0 (2022-10-31) * Adding manually-contributed systems from the Internet of Water's Github: https://github.com/cgs-earth/ref_pws/raw/main/02_output/contributed_pws.gpkg * Refactored to use geopackage through most of pipeline instead of geojson * Added `geometry_source_detail` column to, where possible, include notes provided by the data sources themselves about how the geometry was sourced
创建时间:
2023-12-30
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作