Comprehensive reconstruction of missing aerosol optical depth in MAIAC product: A multi-layer LightGBM approach leveraging multi-scale spatio-temporal information

No abstract is available for this paper.

• Publication year

  2025

• Venue

  Journal of Cleaner Production

• Publication date

  2025-09-01

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1016/j.jclepro.2025.146384
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Improved surface NO2 Retrieval: Double-layer machine learning model construction and spatio-temporal characterization analysis in China (2018-2023).

  2025cited by this paper
• Influence of clouds on planetary boundary layer height: A comparative study and factors analysis

  2024cited by this paper
• Retrieving Hourly Aerosol Optical Depth for Geostationary Satellite FY-4B/AGRI by Surface-related Dynamic Spectral Reflectance Ratio Method

  2024cited by this paper
• Quantifying CO2 emissions of power plants with Aerosols and Carbon Dioxide Lidar onboard DQ-1

  2024cited by this paper
• Evaluation and analysis of long-term MODIS MAIAC aerosol products in China.

  2024cited by this paper
• Insights into Global Visibility Patterns: Spatiotemporal Distributions Revealed by Satellite Remote Sensing

  2024cited by this paper
• Research on PM2.5 Concentration Estimation Based on MAIAC AOD Spatiotemporal Supplement Data

  2024cited by this paper
• An Improved Method for Individual Tree Segmentation in Complex Urban Scenes Based on Using Multispectral LiDAR by Deep Learning

  2024cited by this paper
• Predicting Coronary Heart Disease Using an Improved LightGBM Model: Performance Analysis and Comparison

  2023cited by this paper
• An Efficient Combination of Convolutional Neural Network and LightGBM Algorithm for Lung Cancer Histopathology Classification

  2023cited by this paper
• A global evaluation of daily to seasonal aerosol and water vapor relationships using a combination of AERONET and NAAPS reanalysis data

  2023cited by this paper
• Himawari-8 High Temporal Resolution AOD Products Recovery: Nested Bayesian Maximum Entropy Fusion Blending GEO With SSO Satellite Observations

  2023cited by this paper
• A novel big data mining framework for reconstructing large-scale daily MAIAC AOD data across China from 2000 to 2020

  2022cited by this paper
• Full-coverage 250 m monthly aerosol optical depth dataset (2000–2019) amended with environmental covariates by an ensemble machine learning model over arid and semi-arid areas, NW China

  2022cited by this paper
• Spatiotemporal high-resolution imputation modeling of aerosol optical depth for investigating its full-coverage variation in China from 2003 to 2020

  2022cited by this paper
• Gap-filling MODIS daily aerosol optical depth products by developing a spatiotemporal fitting algorithm

  2022cited by this paper
• LGHAP: the Long-term Gap-free High-resolution Air Pollutant concentration dataset, derived via tensor-flow-based multimodal data fusion

  2022cited by this paper
• Validation and comparison of high-resolution MAIAC aerosol products over Central Asia

  2021cited by this paper
• Impacts of Aerosol Loading in the Hindu Kush Himalayan Region Based on MERRA-2 Reanalysis Data

  2021cited by this paper
• MODIS high-resolution MAIAC aerosol product: Global validation and analysis

  2021cited by this paper
• High-Resolution Mapping of Aerosol Optical Depth and Ground Aerosol Coefficients for Mainland China

  2021cited by this paper
• Probabilistic merging and verification of monthly gridded aerosol products

  2021cited by this paper
• Estimation of hourly full-coverage PM2.5 concentrations at 1-km resolution in China using a two-stage random forest model

  2021cited by this paper
• Handling Missing Data in Large-Scale MODIS AOD Products Using a Two-Step Model

  2020cited by this paper
• Evaluation and Comparison of Himawari-8 L2 V1.0, V2.1 and MODIS C6.1 aerosol products over Asia and the oceania regions

  2020cited by this paper
• Estimation of spatially continuous daytime particulate matter concentrations under all sky conditions through the synergistic use of satellite-based AOD and numerical models.

  2020cited by this paper
• Spatiotemporal trends of PM2.5 concentrations in central China from 2003 to 2018 based on MAIAC-derived high-resolution data.

  2020cited by this paper
• Spatiotemporal Imputation of MAIAC AOD Using Deep Learning with Downscaling.

  2020cited by this paper
• Mitigating MODIS AOD non-random sampling error on surface PM2.5 estimates by a combined use of Bayesian Maximum Entropy method and linear mixed-effects model

  2020cited by this paper
• Anthropogenic and meteorological drivers of 1980–2016 trend in aerosol optical and radiative properties over the Yangtze River Basin

  2020cited by this paper
• Light Gradient Boosting Machine for General Sentiment Classification on Short Texts: A Comparative Evaluation

  2020cited by this paper
• The interaction between urbanization and aerosols during a typical winter haze event in Beijing

  2020cited by this paper
• Comparison of MODIS- and CALIPSO-Derived Temporal Aerosol Optical Depth over Yellow River Basin (China) from 2007 to 2015

  2020cited by this paper
• Ensemble-based deep learning for estimating PM2.5 over California with multisource big data including wildfire smoke.

  2020cited by this paper
• Synergistic Use of Hyperspectral UV-Visible OMI and Broadband Meteorological Imager MODIS Data for a Merged Aerosol Product

  2020cited by this paper
• The Comparison of LightGBM and XGBoost Coupling Factor Analysis and Prediagnosis of Acute Liver Failure

  2020cited by this paper
• Evaluation and uncertainty estimate of next-generation geostationary meteorological Himawari-8/AHI aerosol products.

  2019cited by this paper
• Using gap-filled MAIAC AOD and WRF-Chem to estimate daily PM2.5 concentrations at 1 km resolution in the Eastern United States

  2019cited by this paper
• Evaluation and comparison of multiangle implementation of the atmospheric correction algorithm, Dark Target, and Deep Blue aerosol products over China

  2019cited by this paper
• Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements

  2019cited by this paper
• High-resolution daily AOD estimated to full coverage using the random forest model approach in the Beijing-Tianjin-Hebei region

  2019cited by this paper
• Validation of Himawari-8 aerosol optical depth retrievals over China

  2019cited by this paper
• Spatio-temporal variations and trends of MODIS C6.1 Dark Target and Deep Blue merged aerosol optical depth over China during 2000–2017

  2019cited by this paper
• Evaluation and comparison of MAIAC, DT and DB aerosol products over China

  2019cited by this paper
• MODIS AOD sampling rate and its effect on PM2.5 estimation in North China

  2019cited by this paper
• Understanding of Aerosol–Climate Interactions in China: Aerosol Impacts on Solar Radiation, Temperature, Cloud, and Precipitation and Its Changes Under Future Climate and Emission Scenarios

  2019cited by this paper
• A comparison study between AOD data from MODIS deep blue collections 51 and 06 and from AERONET over Saudi Arabia

  2019cited by this paper
• Filling the missing data gaps of daily MODIS AOD using spatiotemporal interpolation.

  2018cited by this paper
• Evaluation of the AVHRR DeepBlue aerosol optical depth dataset over mainland China

  2018cited by this paper
• MODIS Collection 6 MAIAC algorithm

  2018cited by this paper
• Geostatistical Methods for Filling Gaps in Level-3 Monthly-Mean Aerosol Optical Depth Data from Multi-Angle Imaging SpectroRadiometer

  2017cited by this paper
• Retrieving near‐global aerosol loading over land and ocean from AVHRR

  2017cited by this paper
• Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements

  2017cited by this paper
• Ground-based aerosol climatology of China: aerosol optical depths from the China Aerosol Remote Sensing Network (CARSNET) 2002–2013

  2015cited by this paper
• Aerosol Optical Properties over Mount Song, a Rural Site in Central China

  2015cited by this paper
• China Collection 2.0: The aerosol optical depth dataset from the synergetic retrieval of aerosol properties algorithm

  2014cited by this paper
• An improved dark object method to retrieve 500 m-resolution AOT (Aerosol Optical Thickness) image from MODIS data: A case study in the Pearl River Delta area, China

  2014cited by this paper
• Estimate of aerosol absorbing components of black carbon, brown carbon, and dust from ground‐based remote sensing data of sun‐sky radiometers

  2013cited by this paper
• Kriging interpolation method and its application in retrieval of MODIS aerosol optical depth

  2011cited by this paper
• Multiangle implementation of atmospheric correction (MAIAC): 2. Aerosol algorithm

  2011cited by this paper
• Instrument calibration and aerosol optical depth validation of the China Aerosol Remote Sensing Network

  2009cited by this paper
• The MODIS Aerosol Algorithm, Products, and Validation

  2005cited by this paper
• AERONET-a federated instrument network and data archive for aerosol Characterization

  1998cited by this paper
• ISPRS Journal of Photogrammetry and Remote Sensing

  year unknowncited by this paper

• Water quality spatial-temporal imputation using diffusion graph convolutional networks: A case study in Georgia, USA

  2026cites this paper
• Vector-Guided Post-Earthquake Damaged Road Extraction Using Diffusion-Augmented Remote Sensing Imagery

  2026cites this paper