Estimating high-spatial-resolution daily PM2.5 mass concentration from satellite top-of-atmosphere reflectance based on an improved random forest model-Reference-Cited by-同舟云学术

Estimating high-spatial-resolution daily PM2.5 mass concentration from satellite top-of-atmosphere reflectance based on an improved random forest model

Published:2023-06 Issue: Volume:302 Page:119724
ISSN:1352-2310
Container-title:Atmospheric Environment
language:en
Short-container-title:Atmospheric Environment

Author:

Tang Yuming^ORCID,Deng Ruru,Liang Yeheng,Zhang Ruihao,Cao Bin,Liu Yongming,Hua Zhenqun,Yu Jie

Publisher

Elsevier BV

Subject

Atmospheric Science,General Environmental Science

Reference52 articles.

1. Water Soluble Organic Carbon in Aerosols (PM1, PM2.5, PM10) and Various Precipitation Forms (Rain, Snow, Mixed) over the Southern Baltic Sea station[J];Agnieszka,2016

2. Ambient PM2.5 reduces global and regional life expectancy;Apte;Environ. Sci. Technol. Lett.,2018

3. Random forest in remote sensing: a review of applications and future directions[J];Belgiu;ISPRS J Photogramm,2016

4. Random forests;Breiman;Mach. Learn.,2001

5. Predicting daily urban fine particulate matter concentrations using a random forest model;Brokamp;Environ. Sci. Technol.,2018

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An explainable integrated machine learning model for mapping soil erosion by wind and water in a catchment with three desiccated lakes;Aeolian Research;2024-09

2. Mapping PM2.5 concentration from the top-of-atmosphere reflectance of Himawari-8 via an ensemble stacking model;Atmospheric Environment;2024-08

3. Spatiotemporal continuous PM2.5 concentrations inversion based on multisource data and hybrid model;Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024);2024-07-10

4. High-Resolution PM2.5 Concentrations Estimation Based on Stacked Ensemble Learning Model Using Multi-Source Satellite TOA Data;Remote Sensing;2023-11-24

5. Spatial Characteristics and Influencing Factors of Multi-Scale Urban Living Space (ULS) Carbon Emissions in Tianjin, China;Buildings;2023-09-21