Applications of remote sensing vis-à-vis machine learning in air quality monitoring and modelling: a review

被引:8
|
作者
Bahadur, Faizan Tahir [1 ]
Shah, Shagoofta Rasool [1 ]
Nidamanuri, Rama Rao [2 ]
机构
[1] Natl Inst Technol, Dept Civil Engn, Srinagar 190006, Jammu And Kashm, India
[2] Indian Inst Space Sci & Technol, Dept Earth & Space Sci, Trivandrum 695547, Kerala, India
关键词
Air quality modelling; Remote sensing; Deep learning; Artificial neural networks; Model fusion; Google Earth Engine; POLLUTION; PREDICTION; MODIS; NETWORK; PM2.5; CALIBRATION; SENSORS;
D O I
10.1007/s10661-023-12001-2
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Environmental contamination especially air pollution is an exponentially growing menace requiring immediate attention, as it lingers on with the associated risks of health, economic and ecological crisis. The special focus of this study is on the advances in Air Quality (AQ) monitoring using modern sensors, integrated monitoring systems, remote sensing and the usage of Machine Learning (ML), Deep Learning (DL) algorithms, artificial neural networks, recent computational techniques, hybridizing techniques and different platforms available for AQ modelling. The modern world is data-driven, where critical decisions are taken based on the available and accessible data. Today's data analytics is a consequence of the information explosion we have reached. The current research also tends to re-evaluate its scope with data analytics. The emergence of artificial intelligence and machine learning in the research scenario has radically changed the methodologies and approaches of modern research. The aim of this review is to assess the impact of data analytics such as ML/DL frameworks, data integration techniques, advanced statistical modelling, cloud computing platforms and constantly improving optimization algorithms on AQ research. The usage of remote sensing in AQ monitoring along with providing enormous datasets is constantly filling the spatial gaps of ground stations, as the long-term air pollutant dynamics is best captured by the panoramic view of satellites. Remote sensing coupled with the techniques of ML/DL has the most impact in shaping the modern trends in AQ research. Current standing of research in this field, emerging trends and future scope are also discussed.
引用
收藏
页数:31
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