乡村空心化监测

整合乡村用电量数据、户籍数据及历史趋势，通过异常值过滤、用电波动分析（识别持续下降趋势）及相关算法生成空心村分布热力图，结合多维度权重（如人口密度、产业规模），分析空心村分布、划分空心化类型并触发预警等

This dataset integrates rural electricity consumption data, household registration data and historical trends. Through outlier filtering, electricity consumption fluctuation analysis (identifying sustained downward trends) and relevant algorithms, it generates heatmaps of hollow village distribution. By combining multi-dimensional weights such as population density and industrial scale, it analyzes hollow village distribution, classifies hollowing types and triggers early warnings, etc.

搜集汇总

背景与挑战

背景概述

该数据集专注于乡村空心化现象的监测，通过整合乡村用电量数据、户籍信息及历史趋势，利用异常值过滤和用电波动分析等算法，生成空心村分布热力图并进行多维度权重分析。数据规模为5G，每月更新一次，主要应用于监测省、市层面的乡村空心化情况，包括空心村分布、预警机制和类型占比分析，为电力、热力生产和供应行业提供数据支持。