A New Approach for Dust Storm Detection Using MODIS Data

被引:1
|
作者
Sarikhani, Amin [1 ]
Dehghani, Maryam [1 ]
Karimi-Jashni, Ayoub [1 ]
Saadat, Solmaz [1 ]
机构
[1] Shiraz Univ, Sch Engn, Dept Civil & Environm Engn, Karmikhan Zand Blvd, Shiraz 7134851156, Iran
关键词
Dust storm; MODIS; Spectral overlap; Dark and bright surface; INDEX; REGION;
D O I
10.1007/s40996-020-00508-4
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Dust storms which are considered as a cause of climatic and public health concerns are induced by natural and anthropogenic activities. In this paper, based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images, a new algorithm is developed to automatically detect dust storms over water body and land surfaces. The proposed method applies two different strategies for dust storm detection over water and land surfaces through the combination of various dust indices extracted from reflectance and thermal MODIS channels. It overcomes the disadvantages of previously developed algorithms taking into account the MODIS spectral band 7 (2105-2155 nm) to discriminate between dark and bright land surfaces. Different newly defined dust indices using proper thresholds are then employed for dust storm detection over two land surface classes as well as the water body. The proposed algorithm is applied to six dust-contaminated MODIS images covering southwestern Iran, northeastern Saudi Arabia, and southeastern Iraq. The results show that the proposed dust storm detection method performs well over areas covering features such as bright land surfaces and clouds whose spectral behavior is similar to that of the dust plumes. The results are compared to those obtained from two widely used previously developed dust storm detection algorithms. The comparison of the results with those achieved from visual inspections demonstrates that the proposed method detects the dust storm with the accuracy of similar to 95%, whereas the other two methods result in the dust detection accuracies of similar to 69% and similar to 68%. Furthermore, the proposed approach is found to be promising for dust storm detection over the study area.
引用
收藏
页码:963 / 969
页数:7
相关论文
共 50 条
  • [31] DUST STORM DETECTION FOR XINGJIANG REGION USING INDIAN NATIONAL SATELLITE (INSAT 3A) DATA
    Di, Aojie
    Xue, Yong
    Yang, Xihua
    Leys, John Francis
    Guang, Jie
    Mei, Linlu
    Wang, Jingli
    She, Lu
    He, Xingwei
    Che, Yahui
    Fan, Cheng
    2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 4063 - 4066
  • [32] Dust storm detection and monitoring using multi-temporal INSAT-3A-CCD data
    Sanwlani, Nivedita
    Chauhan, Prakash
    Navalgund, R. R.
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2011, 32 (19) : 5527 - 5539
  • [33] Estimation of dust loading and height using MODIS, AIRS and MAERI data
    De Souza-Machado, S.
    Chu, D. A.
    Nalli, N. R.
    Strow, L. L.
    Hannon, S. E.
    Motteler, H. E.
    Minnett, P. J.
    REMOTE SENSING OF AEROSOL AND CHEMICAL GASES, MODEL SIMULATION / ASSIMILATION, AND APPLICATIONS TO AIR QUALITY, 2006, 6299
  • [34] Investigating the performance of dust detection indices using MODIS data and products (Case study: Khuzestan province of Iran)
    Arezoo Soleimany
    Eisa Solgi
    Khosro Ashrafi
    Reza Jafari
    Raimondas Grubliauskas
    Meteorology and Atmospheric Physics, 2022, 134
  • [35] AEROSOL OPTICAL DEPTH RETRIEVAL OVER LAND USING MODIS DATA AND ITS APPLICATION IN DETECTION OF DUST EVENT
    Mei, Linlu
    Xue, Yong
    Guang, Jie
    Li, Yingjie
    Wang, Ying
    Xu, Hui
    Ai, Jianwen
    2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, : 1129 - 1132
  • [36] Investigating the performance of dust detection indices using MODIS data and products (Case study: Khuzestan province of Iran)
    Soleimany, Arezoo
    Solgi, Eisa
    Ashrafi, Khosro
    Jafari, Reza
    Grubliauskas, Raimondas
    METEOROLOGY AND ATMOSPHERIC PHYSICS, 2022, 134 (04)
  • [37] An enhanced dust index for Asian dust detection with MODIS images
    Han, Lijian
    Tsunekawa, Atsushi
    Tsubo, Mitsuru
    Zhou, Weiqi
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2013, 34 (19) : 6484 - 6495
  • [38] ESTIMATING THE GREATEST DUST STORM IN EASTERN AUSTRALIA WITH MODIS SATELLITE IMAGES
    Li, Xiaojing
    Ge, Linlin
    Dong, Yusen
    Chang, Hsing-Chung
    2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, : 1039 - 1042
  • [39] BACKGROUND SUBTRACTION AND DUST STORM DETECTION
    Liu, Chenyi
    Fieguth, Paul
    Garbe, Christoph
    2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 2179 - 2181
  • [40] Detection of Russian fires using MOPITT and MODIS data
    Lee, S
    Choi, GH
    Lim, HS
    Lee, JH
    Lee, KH
    Kim, YJ
    Kim, J
    ON THE CONVERGENCE OF BIO-INFORMATION-, ENVIRONMENTAL-, ENERGY-, SPACE- AND NANO-TECHNOLOGIES, PTS 1 AND 2, 2005, 277-279 : 816 - 823