閬ユ劅鎶�鏈笌搴旂敤 鈥衡�� 2019, Vol. 34 鈥衡�� Issue (1): 12-20.DOI: 10.11873/j.issn.1004-0323.2019.1.0012

鈥� 缁艰堪 鈥� 涓婁竴绡�    涓嬩竴绡�

鐏伴溇閬ユ劅鐩戞祴鐮旂┒杩涘睍

鍚戝槈鏁�1锛岀鍠勫弸1锛屽紶妗傛2锛屽垬绁�1锛屽懆娲�1顎�   

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  • 鏀剁鏃ユ湡:2018-05-31 鍑虹増鏃ユ湡:2019-02-20 鍙戝竷鏃ユ湡:2019-04-02
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Progress in Haze Monitoring by Remote Sensing Technology

 Xiang Jiamin1锛孼hu Shanyou1锛孼hang Guixin2锛孡iu Yi1锛孼hou Yang1顎�   

  1.  (1.School of Remote Sensing & Geomatics Engineering锛孨anjing University顎僶f Information Science 锛� Technology锛孨anjing 210044锛孋hina;顎�
    2.School of Geographical Sciences锛孨anjing University of Information顎僑cience 锛� Technology锛孨anjing 210044锛孋hina)
  • Received:2018-05-31 Online:2019-02-20 Published:2019-04-02

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鍏抽敭璇�: 鐏伴溇, 姘旀憾鑳�, 閬ユ劅, 鐩戞祴

Abstract: The haze weather is one of the serious disasters affecting the human health and social economic development.Quantitatively monitoring the haze spatio-temporal distribution with a higher precision by remote sensing technology is the basis to predict the haze spreading and then warn its influence early锛寃hich has been a hot issue in the research field of atmospheric environment.The corresponding progress in haze monitoring by remote sensing technology at home and abroad were summarized in this paper.The main methods of haze monitoring can be classified intothree categories锛歵he image transformation from multi-channels and construction of haze indices based on the spectral differences锛宮onitoring directly by the aerosol optical depth and indirectly by estimating the content of atmospheric particulates锛宎nd monitoring vertical and horizontal distribution features from multi-sources remotely sensed data combined the passive optical sensors with the active laser radars.Then the existing problems and difficulties were also discussed.In the future锛宱n the basis of developing three-dimensional haze monitoring technology by multi-sources remote sensing methods锛宺esearch on haze simulation and prediction with high spatio-temporal resolution as well as its practical application need to be further strengthened.

Key words: Haze, Aerosol, Remote sensing, Monitoring

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