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 is developed based on satellite remote sensing imagery data, integrated with meteorological data, air quality monitoring station data, population data and geographic information data. A series of machine learning algorithms are employed to construct models for inverting the concentration data of atmospheric pollutants such as near-surface PM2.5, near-surface PM10, near-surface aerosols and XCO2. Subsequently, the spatiotemporal distribution patterns of multiple atmospheric pollutants including particulate matter, ozone, carbon monoxide, nitrogen dioxide, aerosols, formaldehyde, dust and haze are derived. This work provides scientific and reliable data support for air pollution prevention and control, high-value region extraction, precise pollution management, manual forecasting and model-based forecasting.

搜集汇总

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背景概述

该数据集提供基于手机号的季度上网服务查询信息，适用于金融风控核验，每日更新，覆盖全量电信用户。