A dataset of "beautiful villages" suitability with a spatial resolution of 1 km in China during 2015–2021

The construction of "beautiful villages" is an important part of China's rural revitalisation plan, which aims to promote the improvement of the rural environment and ecological restoration in China. This dataset includes the simulated distribution of the suitability of "beautiful villages" in China from 2015 to 2021, which is based on the spatial distribution of China's "beautiful villages" list on the official website of the Ministry of Agriculture of China (MOA). This dataset is based on the spatial distribution of the "Beautiful Countryside" list on the official website of the Ministry of Agriculture of China and the data of multi-source spatial environment and climate variables, and is generated by machine learning MaxEnt model algorithm, with a spatial resolution of 1,000 m, and the data format is tiff. The simulated ROC accuracies are above 0.9 for all years, which indicates that the dataset can better reflect the distribution suitability of "beautiful villages" in China. Compared with the traditional discrete distribution, this dataset can show the seamless spatial distribution of "beautiful countryside" under the influence of multiple environments more comprehensively, which can provide scientific data support for future research on the construction of "beautiful countryside" and urban-rural planning.

‘美丽村庄’（beautiful villages）建设是中国乡村振兴计划的重要组成部分，旨在推动我国农村环境改善与生态修复。本数据集涵盖2015至2021年我国‘美丽村庄’建设适宜性的模拟空间分布成果，其数据基础源自中国农业农村部（Ministry of Agriculture of China, MOA）官方网站发布的‘美丽村庄’名录空间分布信息，同时融合多源空间环境与气候变量数据，通过机器学习最大熵（MaxEnt）模型算法生成。该数据集空间分辨率为1000米，数据格式为tiff。各年份模拟的ROC（受试者工作特征，Receiver Operating Characteristic）准确率均高于0.9，表明本数据集能够较好地反映我国‘美丽村庄’的分布适宜性特征。相较于传统离散分布数据，本数据集可更全面地展现多环境因子影响下‘美丽村庄’的无缝空间分布格局，可为未来‘美丽村庄’建设研究及城乡规划工作提供科学的数据支撑。

搜集汇总

背景与挑战

背景概述

该数据集提供了2015-2021年中国'美丽乡村'适宜性的1公里空间分辨率模拟分布，基于官方数据和多源环境变量，采用MaxEnt模型算法生成，具有高精度（ROC>0.9）和tiff格式，为'美丽乡村'建设和城乡规划研究提供科学数据支持。