Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Estimating Particulate Matter using satellite based aerosol optical depth and meteorological variables in Malaysia
Nurul Amalin Fatihah Kamarul Zaman, Kasturi Devi Kanniah, Dimitris G. Kaskaoutis
Atmospheric Research (2017) Vol. 193, pp. 142-162
Open Access | Times Cited: 85

Showing 1-25 of 85 citing articles:

COVID-19's impact on the atmospheric environment in the Southeast Asia region
Kasturi Devi Kanniah, Nurul Amalin Fatihah Kamarul Zaman, Dimitris G. Kaskaoutis, et al.
The Science of The Total Environment (2020) Vol. 736, pp. 139658-139658
Open Access | Times Cited: 338
The ChinaHighPM10 dataset: generation, validation, and spatiotemporal variations from 2015 to 2019 across China
Jing Wei, Zhanqing Li, Wenhao Xue, et al.
Environment International (2020) Vol. 146, pp. 106290-106290
Open Access | Times Cited: 304
Tackling environmental challenges in pollution controls using artificial intelligence: A review
Zhiping Ye, Jiaqian Yang, Na Zhong, et al.
The Science of The Total Environment (2019) Vol. 699, pp. 134279-134279
Closed Access | Times Cited: 277
Artificial Intelligence Technologies for Forecasting Air Pollution and Human Health: A Narrative Review
S. Shankar, Naveenkumar Raju, Abbas Ganesan, et al.
Sustainability (2022) Vol. 14, Iss. 16, pp. 9951-9951
Open Access | Times Cited: 108
Satellite remote sensing of atmospheric particulate matter mass concentration: Advances, challenges, and perspectives
Ying Zhang, Zhengqiang Li, Kaixu Bai, et al.
Fundamental Research (2021) Vol. 1, Iss. 3, pp. 240-258
Open Access | Times Cited: 93
Explore spatio-temporal PM2.5 features in northern Taiwan using machine learning techniques
Fi‐John Chang, Li‐Chiu Chang, Che-Chia Kang, et al.
The Science of The Total Environment (2020) Vol. 736, pp. 139656-139656
Closed Access | Times Cited: 86
A back propagation neural network model for accurately predicting the removal efficiency of ammonia nitrogen in wastewater treatment plants using different biological processes
Shu-Zhe Zhang, Shuo Chen, Hong Jiang
Water Research (2022) Vol. 222, pp. 118908-118908
Closed Access | Times Cited: 50
Estimating ground-level PM2.5 using subset regression model and machine learning algorithms in Asian megacity, Dhaka, Bangladesh
Abu Reza Md. Towfiqul Islam, Mohammed Al Awadh, Javed Mallick, et al.
Air Quality Atmosphere & Health (2023) Vol. 16, Iss. 6, pp. 1117-1139
Open Access | Times Cited: 28
Quantifying Urban Land Sprawl and its Driving Forces in Northeast China from 1990 to 2015
Lin Chen, Chunying Ren, Bai Zhang, et al.
Sustainability (2018) Vol. 10, Iss. 1, pp. 188-188
Open Access | Times Cited: 73
Quantifying green cover change for sustainable urban planning: A case of Kuala Lumpur, Malaysia
Kasturi Devi Kanniah
Urban forestry & urban greening (2017) Vol. 27, pp. 287-304
Open Access | Times Cited: 66
Spatial assessment of PM10 hotspots using Random Forest, K-Nearest Neighbour and Naïve Bayes
Abdulwaheed Tella, Abdul‐Lateef Balogun, Naheem Adebisi, et al.
Atmospheric Pollution Research (2021) Vol. 12, Iss. 10, pp. 101202-101202
Closed Access | Times Cited: 53
Using the Boruta algorithm and deep learning models for mapping land susceptibility to atmospheric dust emissions in Iran
Hamid Gholami, Aliakbar Mohammadifar, Shahram Golzari, et al.
Aeolian Research (2021) Vol. 50, pp. 100682-100682
Closed Access | Times Cited: 50
Improving the quantification of fine particulates (PM2.5) concentrations in Malaysia using simplified and computationally efficient models
Nurul Amalin Fatihah Kamarul Zaman, Kasturi Devi Kanniah, Dimitris G. Kaskaoutis, et al.
Journal of Cleaner Production (2024) Vol. 448, pp. 141559-141559
Closed Access | Times Cited: 7
Evaluation of linear, nonlinear, and hybrid models for predicting PM2.5 based on a GTWR model and MODIS AOD data
Mahin Mirzaei, Jamil Amanollahi, Chris G. Tzanis
Air Quality Atmosphere & Health (2019) Vol. 12, Iss. 10, pp. 1215-1224
Closed Access | Times Cited: 49
Long term variability of carbonaceous aerosols over Southeast Asia via reanalysis: Association with changes in vegetation cover and biomass burning
Gayatry Kalita, Ravi Kumar Kunchala, Suvarna Fadnavis, et al.
Atmospheric Research (2020) Vol. 245, pp. 105064-105064
Closed Access | Times Cited: 45
Evaluation of Machine Learning Models for Estimating PM2.5 Concentrations across Malaysia
Nurul Amalin Fatihah Kamarul Zaman, Kasturi Devi Kanniah, Dimitris G. Kaskaoutis, et al.
Applied Sciences (2021) Vol. 11, Iss. 16, pp. 7326-7326
Open Access | Times Cited: 37
Review of satellite-driven statistical modelsPM2.5concentration estimation with comprehensive information
Xinghan Xu, Chengkun Zhang, Yi Liang
Atmospheric Environment (2021) Vol. 256, pp. 118302-118302
Closed Access | Times Cited: 34
Impact of Covid-19 lockdown regulations on PM2.5 and trace gases (NO2, SO2, CH4, HCHO, C2H2O2 and O3) over Lahore, Pakistan
Irfan Karim, B. Rappenglück
Atmospheric Environment (2023) Vol. 303, pp. 119746-119746
Open Access | Times Cited: 15
Performance of Bayesian Model Averaging (BMA) for Short-Term Prediction of PM10 Concentration in the Peninsular Malaysia
Norazrin Ramli, Hazrul Abdul Hamid, Ahmad Shukri Yahaya, et al.
Atmosphere (2023) Vol. 14, Iss. 2, pp. 311-311
Open Access | Times Cited: 14
Impact of meteorological parameters on aerosol optical depth and particulate matter in Lahore
Zahid Ur Rehman, Salman Tariq, Zia ul Haq, et al.
Acta Geophysica (2024) Vol. 72, Iss. 2, pp. 1377-1395
Closed Access | Times Cited: 6
A minimum albedo aerosol retrieval method for the new-generation geostationary meteorological satellite Himawari-8
Xing Yan, Zhanqing Li, Nana Luo, et al.
Atmospheric Research (2018) Vol. 207, pp. 14-27
Open Access | Times Cited: 44
Spatiotemporal analysis of ground and satellite-based aerosol for air quality assessment in the Southeast Asia region
Thi Nhat Thanh Nguyen, Ha V. Pham, Kristofer Lasko, et al.
Environmental Pollution (2019) Vol. 255, pp. 113106-113106
Closed Access | Times Cited: 40
Estimation of ground-level particulate matter concentrations based on synergistic use of MODIS, MERRA-2 and AERONET AODs over a coastal site in the Eastern Mediterranean
Gizem Tuna Tuygun, Serdar Gündoğdu, Tolga Elbir
Atmospheric Environment (2021) Vol. 261, pp. 118562-118562
Open Access | Times Cited: 29
A comprehensive review of energy-efficiency of ventilation system using Artificial Intelligence
P Kumar, Ananda Shankar Hati
Renewable and Sustainable Energy Reviews (2021) Vol. 146, pp. 111153-111153
Closed Access | Times Cited: 28
Estimation of particulate matter concentrations in Türkiye using a random forest model based on satellite AOD retrievals
Gizem Tuna Tuygun, Tolga Elbir
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 9, pp. 3469-3491
Closed Access | Times Cited: 12
Page 1 - Next Page

Scroll to top