Detection of Dust Storm Origins in the Middle East by Remotely Sensed Data

被引:5
|
作者
Saeifar, Mohammad Hamed [1 ]
Alijani, Bohloul [2 ]
机构
[1] Kharazmi Univ, Tehran, Iran
[2] Kharazmi Univ, Ctr Excellence Spatial Anal Environm Hazards, Tehran, Iran
关键词
Dust storms; Image processing techniques; Dust origins; Differential index; Threshold limit; CHINA;
D O I
10.1007/s12524-019-01030-5
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Dust storms are one of the most common natural phenomena in the arid and semiarid regions. Long periods of drought and inappropriate land management practices, by removing soil moisture and vegetation cover, can make these region more susceptible to the occurrence dust storms. Over the last few years in the Middle East, the intensity and frequency of this phenomenon have increased, interrupting daily economic and social routines. The purpose of this study was to identify the sources of dust in the Middle East during the time period from 2003 to 2017 using the differential index of dust detection and MODIS satellite images in the period 2003 to 2017. The final steps involved detecting possible driving forces and consequences of dust storms in the region. The results showed that the origin of dust storms incoming to the west, northwest, and southwest of Iran is from Syria, Iraq, and parts of Saudi Arabia, which is also the main source of dust in northern Iraq and the border between Iraq and Syria. The results also showed that satellite images, by providing wide-angle view of surface features and acquiring daily images, would be a helpful tool to identify the origins of dust storms and detect their spatial pattern.
引用
收藏
页码:1883 / 1893
页数:11
相关论文
共 50 条
  • [21] Dust storm detection using random forests and physical-based approaches over the Middle East
    Souri, Amir Hossein
    Vajedian, Sanaz
    JOURNAL OF EARTH SYSTEM SCIENCE, 2015, 124 (05) : 1127 - 1141
  • [22] Detection of levee slides using commercially available remotely sensed data
    Hossain, A. K. M. Azad
    Easson, Greg
    Hasan, Khaled
    ENVIRONMENTAL & ENGINEERING GEOSCIENCE, 2006, 12 (03): : 235 - 246
  • [23] Predictive Modeling for Site Detection Using Remotely Sensed Phenological Data
    Kirk, Scott Detrick
    Thompson, Amy E.
    Lippitt, Christopher D.
    ADVANCES IN ARCHAEOLOGICAL PRACTICE, 2016, 4 (01): : 87 - 101
  • [24] Detection of Logging Infrastructure in the State of Rondonia Using Remotely Sensed Data
    Pinage, Ekena Rangel
    Trondoli Matricardi, Eraldo Aparecido
    FLORESTA E AMBIENTE, 2015, 22 (03): : 377 - 390
  • [25] Detection of landuse/landcover changes using remotely-sensed data
    Park, Jinwoo
    Lee, Jungsoo
    JOURNAL OF FORESTRY RESEARCH, 2016, 27 (06) : 1343 - 1350
  • [26] Detection of landuse/landcover changes using remotely-sensed data
    Jinwoo Park
    Jungsoo Lee
    Journal of Forestry Research, 2016, 27 : 1343 - 1350
  • [27] Detection of landuse/landcover changes using remotely-sensed data
    Jinwoo Park
    Jungsoo Lee
    Journal of Forestry Research, 2016, 27 (06) : 1343 - 1350
  • [29] Remotely sensed images and GIS data fusion for automatic change detection
    Li, Deren
    INTERNATIONAL JOURNAL OF IMAGE AND DATA FUSION, 2010, 1 (01) : 99 - 108
  • [30] APPLICATION OF REMOTELY SENSED DATA TO THE DETECTION OF SEA-SURFACE PHENOMENA
    OCHIAI, H
    TSUCHIYA, K
    ACTA ASTRONAUTICA, 1981, 8 (5-6) : 497 - 509