大气与环境光学学报 ›› 2024, Vol. ›› Issue (2): 232-242.doi: 10.3969/j.issn.1673-6141.2024.02.009

• 光学遥感 • 上一篇    

基于LightGBM的贵阳市气溶胶光学厚度反演

普莉兰 , 张显云 *   

  1. 贵州大学矿业学院, 贵州 贵阳 550025
  • 收稿日期:2022-10-20 修回日期:2022-11-24 出版日期:2024-03-28 发布日期:2024-04-18
  • 通讯作者: E-mail: mec.xyzhang@gzu.edu.cn E-mail:mec.xyzhang@gzu.edu.cn
  • 作者简介:普莉兰 (1997- ), 女, 云南开远人, 硕士研究生, 主要从事遥感方面的研究。E-mail: 1300864006@qq.com
  • 基金资助:
    国家自然科学基金 (41901225), 贵州省省级科技计划项目 (黔科合支撑 [2022] 一般204)

Inversion of aerosol optical depth in Guiyang City based on LightGBM

PU Lilan , ZHANG Xianyun *   

  1. College of Mining, Guizhou University, Guiyang 550025, China
  • Received:2022-10-20 Revised:2022-11-24 Online:2024-03-28 Published:2024-04-18
  • Contact: ZHANG XianYun E-mail:mec.xyzhang@gzu.edu.cn

摘要: 为充分挖掘国产高分四号卫星 (GF-4) 的环境监测能力, 克服基于查找表方法反演气溶胶光学厚度 (AOD) 的 复杂性和弥补贵阳市无气溶胶监测站点的缺陷, 并提升MODIS AOD产品的时空分辨率, 利用贵阳市研究区的高程数 据和GF-4 多光谱成像仪 (PMS) 数据提取的地表反射率、太阳天顶角、卫星天顶角、相对方位角和归一化植被指数作为 特征变量, 以MODIS气溶胶产品为标签, 基于LightGBM 算法构建了贵阳市AOD反演模型。研究结果表明: 该模型 能够基于GF-4 PMS单时相遥感数据实现较高精度的AOD智能反演, 极大简化了AOD反演步骤, 且具有较高的建模 精度 (平均绝对误差EMA、均方根误差ERMS、决定系数R2 分别为0.042、0.057、0.751) 和预测精度 (城区: EMA = 0.077, ERMS = 0.086; 非城区: EMA = 0.094, ERMS = 0.101), AOD预测值和MODIS AOD具有相似的变化趋势, 皮尔逊相关系数 为0.697。

关键词: 高分四号, 中分辨率成像光谱仪, 气溶胶光学厚度, 轻量级梯度提升模型, 贵阳市

Abstract: In order to fully exploit the environmental monitoring capability of domestic Gaofen-4 satellite (GF-4), overcome the complexity of retrieving aerosol optical depth (AOD) based on look-up table method, make up for the lack of aerosol monitoring station in Guiyang City, China, and improve spatial and temporal resolution of MODIS AOD products, the AOD inversion model for Guiyang was constructed based on LightGBM algorithm using the elevation data of the study area and the surface reflectance, solar zenith angle, satellite zenith angle, relative azimuth angle and normalized different vegetation index extracted from the data of GF-4 panchromatic multispectral sensor (PMS) as the feature variables, and taking MODIS aerosol products as the label. The research results show that the model can achieve high precision AOD intelligent inversion based on GF-4 PMS single-phase remote sensing data, greatly simplify the AOD inversion steps, and has high modeling accuracy (with mean absolute error EMA, root mean square error ERMS and coefficient of determination R2 of 0.042, 0.057, and 0.751, respectively) and prediction accuracy (with EMA and ERMS of 0.077 and 0.086 respectively in urban area, and EMA and ERMS of 0.094 and 0.101 respectively in non-urban area). In addition, it is shown that the predicted AOD with the proposed inversion model and MODIS AOD have a similar variation trend, and the Pearson correlation coefficient of them is 0.697.

Key words: Gaofen-4, moderate-resolution imaging spectroradiometer, aerosol optical depth, light gradient boosting machine, Guiyang City

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