Data for Disparities in the siting of stream restoration projects: lessons learned from Legacy Funds in Minnesota, USA

This dataset contains data for the in-progress paper titled Disparities in the siting of stream restoration projects: lessons learned from Legacy Funds in Minnesota, USA. In the paper we present a newly assembled stream restoraiton dataset for Minnesota and analyze the siting of restoration projects using an environmental justice lens. This data product includes all data and code used in our analysis. Each folder includes metadata that describes the data within. The overall structure is as follows: Raw data - all primary data downloads, including GIS data of political boundaries and environmental variables, and tabluar data of stream restoration projects Intermediate data - data products created in the analysis, these include spatial joins and intersections of socioeconomic and environmental variables Final data - data used in statistical analysis. This includes information at individual stream restoraiton points, county and watershed level R scripts used to conduct statistical analyses are also included: Negative binomial analysis comparing the incidence of stream restoration sites with socioeconomic and environmental variables at the county and HUC 8 watershed scale Sensitivity analysis showing socioeconomic variables for buffer sizes ranging from 100 m to 2000 m around restoration points Restoration site analysis contains code for basic statistical analysis and plotting本数据集配套于一篇正在撰写中的论文，论文标题为《美国明尼苏达州河流修复项目选址差异：来自遗产基金的经验启示》。文中我们构建了全新的明尼苏达州河流修复数据集，并以环境正义视角剖析了修复项目的选址逻辑。 本数据产品涵盖本次分析所用的全部数据与代码。每个文件夹均附带元数据，用于说明文件夹内的数据内容。 整体结构如下： - 原始数据：所有原始下载数据集，包含行政边界与环境变量的地理信息系统（Geographic Information System, GIS）数据，以及河流修复项目的表格数据。 - 中间数据：分析过程中生成的数据产品，包含社会经济与环境变量的空间连接与空间交集数据。 - 最终数据：用于统计分析的数据，涵盖单个河流修复点位、县级及流域级的相关信息。 本次分析所用的R脚本亦一并提供： 1. 负二项分布分析：用于在县级与HUC 8流域尺度下，对比河流修复点位的发生频次与社会经济、环境变量之间的关联； 2. 敏感性分析：展示修复点位周边100米至2000米不同缓冲尺度下的社会经济变量分析结果； 3. 修复点位分析：包含基础统计分析与可视化绘图的代码。