地球关键带数据产品

本产品基于卫星遥感影像数据，结合气象数据、空气质量监测站点数据、人口数据、地理信息数据，采用机器学习系列算法搭建模型，实现对近地表PM2.5、近地表PM10、近地表气溶胶、XCO2等大气污染物浓度数据的反演，得到颗粒物、臭氧、一氧化碳、二氧化氮、气溶胶、甲醛、沙尘、灰霾等大气污染物的时空分布情况，为大气污染物防治、高值区域提取、污染精准管控、人工预报和模式预报等工作提供科学、有效的数据支撑。

This dataset develops models via a series of machine learning algorithms, integrating satellite remote sensing image data, meteorological data, air quality monitoring station data, population data and geographic information data. It achieves the retrieval of near-surface PM2.5, near-surface PM10, near-surface aerosols, XCO2 and other atmospheric pollutant concentration data, and derives the spatiotemporal distribution patterns of multiple atmospheric pollutants including particulate matter, ozone, carbon monoxide, nitrogen dioxide, aerosols, formaldehyde, dust and haze. This dataset provides scientific and robust data support for applications such as atmospheric pollution prevention and control, high-value region extraction, precise pollution management, manual forecasting and numerical model forecasting.

搜集汇总

背景与挑战

背景概述

地球关键带数据产品是一个基于卫星遥感影像数据，结合气象、空气质量监测站点、人口和地理信息数据，采用机器学习算法反演大气污染物浓度的数据集。该数据集覆盖全国，每日更新，主要用于大气污染物防治、污染精准管控等生态环境和绿色低碳应用场景。