Journal of Range and Watershed Managment

Dust & Sand Source Identification Using Remotely Sensed Data: a comprehensive Approach

Document Type : Research Paper

Authors

Behzad Rayegani 1
Susan Barati Ghahfarokhi 2
Ahmad Khoshnava 3

1 هیات علمی مدیر پژوهش و فناوری

2 Natural Resource Faculty, Isfahan University of Technology, Isfahan, Iran

3 College of Environment, Department of Environment, Karaj, Iran

https://doi.org/10.22059/jrwm.2019.251015.1223
Abstract
The aim of this study is to develop a comprehensive approach to identifying dust & sand sources and to investigate their changes over a set period of time using remotely sensed data. For this purpose, data OLI data of Landsat 8 during the years 2013 through 2015 were used to make maps of vegetation cover, soil moisture and land cover sensibility to wind erosion. These maps were combined with geology and roughness by multi-criteria evaluation method to obtain a map of sand & dust source potential areas. In the second step, information of synoptic stations, meteorological and air pollution measurements was prepared, and using statistical analysis and with the help of Modis data, the history of local events was obtained. These regions were integrated with the map of sand & dust source potential areas using the MCE method (WLC) and based on a stratified random sampling plan, susceptible sites of sand & dust sources were identified. In order to validate the identified areas and investigate the trend of their changes, the time series of satellite data and weather stations data were used and the trend of vegetation, soil moisture and surface temperature at the location of identified areas during a 15-year period were monitored. Validation results show high accuracy of identified areas and significant reduction trend of vegetation, soil moisture and surface temperature in the locations of identified sites during the study period

Keywords

HYSPLIT
the time series of satellite data
Trend Analysis
Comprehensive Approach
MODIS
TMI
Journal of Range and Watershed Managment
Volume 72, Issue 1
Spring 2019
Pages 83-105

  • Receive Date 23 January 2018
  • Revise Date 20 February 2019
  • Accept Date 20 February 2019
  • Publish Date 22 May 2019

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