Himawari-8 Aerosol Optical Depth (AOD) Retrieval Using a Deep Neural Network Trained Using AERONET Observations

A Robust Deep Learning Approach for Spatiotemporal Estimation of Satellite AOD and PM2.5

(2020) Lianfa Li   Remote Sensing

Deep learning in environmental remote sensing: Achievements and challenges

(2020) Qiangqiang Yuan et al.   REMOTE SENSING OF ENVIRONMENT

Investigating the performance of satellite-based models in estimating the surface PM2.5 over China

(2020) Lechao Dong et al.   CHEMOSPHERE

Black carbon dominates the aerosol absorption over the Indo-Gangetic Plain and the Himalayan foothills

(2020) S. Ramachandran et al.   ENVIRONMENT INTERNATIONAL

Comparison of Six Machine Learning Methods for Estimating PM2.5 Concentration Using the Himawari-8 Aerosol Optical Depth

(2020) Xin Zuo et al.   Journal of the Indian Society of Remote Sensing

Three-dimensional convolutional neural network model for tree species classification using airborne hyperspectral images

(2020) Bin Zhang et al.   REMOTE SENSING OF ENVIRONMENT

Refining aerosol optical depth retrievals over land by constructing the relationship of spectral surface reflectances through deep learning: Application to Himawari-8

(2020) Tianning Su et al.   REMOTE SENSING OF ENVIRONMENT

Estimation of daily PM10 and PM2.5 concentrations in Italy, 2013–2015, using a spatiotemporal land-use random-forest model

(2019) Massimo Stafoggia et al.   ENVIRONMENT INTERNATIONAL

Deep Convolutional Neural Network for Mapping Smallholder Agriculture Using High Spatial Resolution Satellite Image

(2019) Xie et al.   SENSORS

Quantitative Aerosol Optical Depth Detection during Dust Outbreaks from Meteosat Imagery Using an Artificial Neural Network Model

(2019) Stavros Kolios et al.   Remote Sensing

Multi-sensor cloud and cloud shadow segmentation with a convolutional neural network

(2019) Marc Wieland et al.   REMOTE SENSING OF ENVIRONMENT

Estimating 1-km-resolution PM2.5 concentrations across China using the space-time random forest approach

(2019) Jing Wei et al.   REMOTE SENSING OF ENVIRONMENT

Evaluation and uncertainty estimate of next-generation geostationary meteorological Himawari-8/AHI aerosol products

(2019) Jing Wei et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data

(2019) Lu She et al.   Remote Sensing

Stacking machine learning model for estimating hourly PM2.5 in China based on Himawari 8 aerosol optical depth data

(2019) Jiangping Chen et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Spatial hazard assessment of the PM10 using machine learning models in Barcelona, Spain

(2019) Bahram Choubin et al.   SCIENCE OF THE TOTAL ENVIRONMENT

First Provisional Land Surface Reflectance Product from Geostationary Satellite Himawari-8 AHI

(2019) Shuang Li et al.   Remote Sensing

Validation of Himawari-8/AHI Radiometric Calibration Based on Two Years of In-Orbit Data

(2018) Arata OKUYAMA et al.   JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN

Common Retrieval of Aerosol Properties for Imaging Satellite Sensors

(2018) Mayumi YOSHIDA et al.   JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN

Satellite-based mapping of daily high-resolution ground PM 2.5 in China via space-time regression modeling

(2018) Qingqing He et al.   REMOTE SENSING OF ENVIRONMENT

Preliminary Investigation of a New AHI Aerosol Optical Depth (AOD) Retrieval Algorithm and Evaluation with Multiple Source AOD Measurements in China

(2018) Fukun Yang et al.   Remote Sensing

Correcting Measurement Error in Satellite Aerosol Optical Depth with Machine Learning for Modeling PM2.5 in the Northeastern USA

(2018) Allan Just et al.   Remote Sensing

A Dark Target Method for Himawari-8/AHI Aerosol Retrieval: Application and Validation

(2018) Bangyu Ge et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Polarimetric remote sensing of atmospheric aerosols: Instruments, methodologies, results, and perspectives

(2018) Oleg Dubovik et al.   JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER

Investigation of Sentinel-2 Bidirectional Reflectance Hot-Spot Sensing Conditions

(2018) Zhongbin Li et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Estimating PM2.5 Concentrations in the Conterminous United States Using the Random Forest Approach

(2017) Xuefei Hu et al.   ENVIRONMENTAL SCIENCE & TECHNOLOGY

Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

(2017) Tongwen Li et al.   GEOPHYSICAL RESEARCH LETTERS

Image Super-Resolution Using Deep Convolutional Networks

(2016) Chao Dong et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Random forest in remote sensing: A review of applications and future directions

(2016) Mariana Belgiu et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Deep learning

(2015) Yann LeCun et al.   NATURE

Effect of MODIS Terra radiometric calibration improvements on Collection 6 Deep Blue aerosol products: Validation and Terra/Aqua consistency

(2015) A. M. Sayer et al.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

Global aerosol change in the last decade: An analysis based on MODIS data

(2014) K.B. Mao et al.   ATMOSPHERIC ENVIRONMENT

MODIS Collection 6 aerosol products: Comparison between Aqua's e-Deep Blue, Dark Target, and “merged” data sets, and usage recommendations

(2014) A. M. Sayer et al.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

Estimating ground-level PM2.5 concentrations in the Southeastern United States using MAIAC AOD retrievals and a two-stage model

(2013) Xuefei Hu et al.   REMOTE SENSING OF ENVIRONMENT

Enhanced Deep Blue aerosol retrieval algorithm: The second generation

(2013) N. C. Hsu et al.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

Validation and uncertainty estimates for MODIS Collection 6 “Deep Blue” aerosol data

(2013) A. M. Sayer et al.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

Incorporating Local Land Use Regression And Satellite Aerosol Optical Depth In A Hybrid Model Of Spatiotemporal PM2.5 Exposures In The Mid-Atlantic States

(2012) Itai Kloog et al.   ENVIRONMENTAL SCIENCE & TECHNOLOGY

Continental-scale validation of MODIS-based and LEDAPS Landsat ETM+ atmospheric correction methods

(2012) Junchang Ju et al.   REMOTE SENSING OF ENVIRONMENT

Uncertainty Analysis of Neural-Network-Based Aerosol Retrieval

(2011) Kosta Ristovski et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Multiangle implementation of atmospheric correction (MAIAC): 2. Aerosol algorithm

(2011) A. Lyapustin et al.   JOURNAL OF GEOPHYSICAL RESEARCH

A Data-Mining Technique for Aerosol Retrieval Across Multiple Accuracy Measures

(2010) Vladan Radosavljevic et al.   IEEE Geoscience and Remote Sensing Letters

Multiangle Imaging SpectroRadiometer global aerosol product assessment by comparison with the Aerosol Robotic Network

(2010) Ralph A. Kahn et al.   JOURNAL OF GEOPHYSICAL RESEARCH

Machine Learning and Bias Correction of MODIS Aerosol Optical Depth

(2009) D.J. Lary et al.   IEEE Geoscience and Remote Sensing Letters

Sensitivity Analysis of k-Fold Cross Validation in Prediction Error Estimation

(2009) J.D. Rodriguez et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: Multiple regression approach

(2009) Pawan Gupta et al.   JOURNAL OF GEOPHYSICAL RESEARCH

A Data-Mining Approach for the Validation of Aerosol Retrievals

(2008) Slobodan Vucetic et al.   IEEE Geoscience and Remote Sensing Letters

Global aerosol climatology from the MODIS satellite sensors

(2008) Lorraine A. Remer et al.   JOURNAL OF GEOPHYSICAL RESEARCH