Mapping and monitoring of dust storms in Iran by fuzzy clustering and remote sensing techniques

被引:0
|
作者
Batool Zeinali
Sayyad Asghari
机构
[1] University of Mohaghegh Ardabili,Department of Physical Geography
[2] University of Urmia,Department of Physical Geography
来源
关键词
Fuzzy C; Brightness temperature index; MODIS; Dust storms; Monitoring;
D O I
暂无
中图分类号
学科分类号
摘要
In this research, the frequency of dust storms was prepared at 87 synoptic stations for the period of 1987–2013. These data were classified by means of Fuzzy c-means clustering algorithm. Satellite images of MODIS and brightness temperature index were also used for detection and tracking dust storm of 30 Jun 4 July 2008. The results indicated that Iran is classified in five clusters by the dust-storm-frequencies from which, cluster 5 is reclassified in three clusters because of its wide range. The maximum number of days with dust storms was observed in cluster 1 that includes only Zabol station with the frequency of 790 days with the duration 1987–2013. The minimum number of days with dust storms was observed in cluster 5-3 that includes the stations located in portions of North, Northwest, Northeast Iran and the higher elevations of the Zagros in western Iran. A case study about a severe dust storm in Iran using satellite images indicate that brightness temperature index (BTI) is a desired index for detection and monitoring of dust storms. The source of the investigated dust storms is Iraq and South of the Arabian Peninsula that had influenced the western half of Iran in several days. The frequency of dust storms increased markedly in the west, southwest of Iran and Persian Gulf around as main receptors from emerging dusty areas but it increased slightly in the eastern half of Iran.
引用
收藏
相关论文
共 50 条
  • [1] Mapping and monitoring of dust storms in Iran by fuzzy clustering and remote sensing techniques
    Zeinali, Batool
    Asghari, Sayyad
    [J]. ARABIAN JOURNAL OF GEOSCIENCES, 2016, 9 (09)
  • [2] Remote Sensing Techniques in Landslide Mapping and Monitoring, Keynote Lecture
    Casagli, Nicola
    Tofani, Veronica
    Morelli, Stefano
    Frodella, William
    Ciampalini, Andrea
    Raspini, Federico
    Intrieri, Emanuele
    [J]. ADVANCING CULTURE OF LIVING WITH LANDSLIDES, VOL 3: ADVANCES IN LANDSLIDE TECHNOLOGY, 2017, : 1 - 19
  • [3] Remote sensing techniques: mapping and monitoring of mangrove ecosystem—a review
    Khushbu Maurya
    Seema Mahajan
    Nilima Chaube
    [J]. Complex & Intelligent Systems, 2021, 7 : 2797 - 2818
  • [4] Mapping of dust source susceptibility by remote sensing and machine learning techniques (case study: Iran-Iraq border)
    Sima Pourhashemi
    Mohammad Ali Zangane Asadi
    Mahdi Boroughani
    Hossein Azadi
    [J]. Environmental Science and Pollution Research, 2023, 30 : 27965 - 27979
  • [5] Mapping of dust source susceptibility by remote sensing and machine learning techniques (case study: Iran-Iraq border)
    Pourhashemi, Sima
    Asadi, Mohammad Ali Zangane
    Boroughani, Mahdi
    Azadi, Hossein
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (10) : 27965 - 27979
  • [6] Dust source susceptibility mapping based on remote sensing and machine learning techniques
    Jafari, Reza
    Amiri, Mohadeseh
    Asgari, Fatemeh
    Tarkesh, Mostafa
    [J]. ECOLOGICAL INFORMATICS, 2022, 72
  • [7] MAPPING GLAUCONITE UNITES WITH USING REMOTE SENSING TECHNIQUES IN NORTH EAST OF IRAN
    Ahmadirouhani, R.
    Samiee, S.
    [J]. 1ST ISPRS INTERNATIONAL CONFERENCE ON GEOSPATIAL INFORMATION RESEARCH, 2014, 40 (2/W3): : 7 - 11
  • [8] Remote sensing techniques: mapping and monitoring of mangrove ecosystem-a review
    Maurya, Khushbu
    Mahajan, Seema
    Chaube, Nilima
    [J]. COMPLEX & INTELLIGENT SYSTEMS, 2021, 7 (06) : 2797 - 2818
  • [9] Vulnerability mapping and risk analysis of sand and dust storms in Ahvaz, IRAN
    Boloorani, Ali Darvishi
    Shorabeh, Saman Nadizadeh
    Samany, Najmeh Neysani
    Mousivand, Alijafar
    Kazemi, Yasin
    Jaafarzadeh, Nemat
    Zahedi, Amir
    Rabiei, Javad
    [J]. ENVIRONMENTAL POLLUTION, 2021, 279
  • [10] Remote sensing techniques for mangrove mapping
    World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge CB3 0DL, United Kingdom
    [J]. Int J Remote Sens, 5 (935-956):