Dust detection in western and southwestern Iran based on DAI index algorithm and Modis spectral data

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Faryabi Azar; MATINFAR HAMID REZA; Alavi Panah Seyyed Kazem; NOROUZI ALI AKBAR

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Environmental Sciences Year:2019 | Volume:17 | Issue:3 Page(s): 151-162

Download Full-Text

Persian Verion

View:

554

Download:

Cites:

Information Journal Paper

Title

Dust detection in western and southwestern Iran based on DAI index algorithm and Modis spectral data

Author(s)

Faryabi Azar | MATINFAR HAMID REZA | Alavi Panah Seyyed Kazem | NOROUZI ALI AKBAR | Issue Writer Certificate

Keywords

DAI algorithmQ1

MODIS satellite imagesQ1

dustQ1

Abstract

Introduction: A dust aerosol index (DAI) algorithm based on measurements in deep blue (412 nm), blue (440 nm), and shortwave IR (2130 nm) wavelengths using Moderate Resolution Imaging Spectroradiometer (MODIS) observations has been developed. Measurements made in the short-wavelength segment, such as the deep blue or ultraviolet section, are well-detectable in the desert area. Using short-range waves, the visual retention of fine-grained mass data, especially in desert areas, was carefully monitored. The western and southwestern Iran are always exposed to dusty systems due to its vicinity to the deserts of neighboring countries. With regard to the fact that most of the spectral indices proposed for the identification of dust have been tested and implemented based on satellite indicators for desert areas, these indicators and their related thresholds for complex topography areas need more accurate analyses. Therefore, in the western and southwestern Iran, which are mountainous with a diverse vegetation, it is necessary to test and evaluate dust detection methods. Material and methods: The study area included Khuzestan, Ilam and Kermanshah provinces, which is about 107307 square kilometers. In this study, MODIS L1B data from the Aqua satellite was used for dusty days on May 18 and June 25, 2013 and 2015. Before performing spectral calculations on various products, the data of this sensor was preprocessed, which included geometric correction of images, mask cloud and water masks with ENVI and the conversion tool module. After preprocessing (georges, separating the study area, and water mask, and cloud cover) the satellite data, the retrieved spatial radiance of TOA was normalized using satellite data considering the sun's conditions for each wavelength. Results and discussion: In general, it was found that all AOD maps generated from the direct method showed a very good spatial distribution of the local aerosol pattern compared to other methods. As expected, the retrieved AOD map from the L1B spectrum showed that the spatial distribution of the local AOD was very clear. The DAI index algorithm simulates the high-spectral dependence of the atmosphere in the blue wavelength for different surface and atmosphere conditions with a fully tested copy of the radiation-transfer code of-6 S, which is a trusted tool for measuring particle pumping over the oceans, different surfaces of the earth, and clouds. Conclusion: Unlike some of the dust detection algorithms that are carried out using measurements in the infrared thermal band, the advantage of this algorithm to detect dust is the use of spectral scattering, reflection of the surface, and absorption of dust in the air. The advantage of using measurments in the blue wavelength (410 to 490 nm) is to recover the optical properties of the aerosol.

Cites

No record.

References

No record.

Cite

APA: Copy

Faryabi, Azar, MATINFAR, HAMID REZA, Alavi Panah, Seyyed Kazem, & NOROUZI, ALI AKBAR. (2019). Dust detection in western and southwestern Iran based on DAI index algorithm and Modis spectral data. ENVIRONMENTAL SCIENCES, 17(3 ), 151-162. SID. https://sid.ir/paper/117731/en

Vancouver: Copy

Faryabi Azar, MATINFAR HAMID REZA, Alavi Panah Seyyed Kazem, NOROUZI ALI AKBAR. Dust detection in western and southwestern Iran based on DAI index algorithm and Modis spectral data. ENVIRONMENTAL SCIENCES[Internet]. 2019;17(3 ):151-162. Available from: https://sid.ir/paper/117731/en

IEEE: Copy

Azar Faryabi, HAMID REZA MATINFAR, Seyyed Kazem Alavi Panah, and ALI AKBAR NOROUZI, “Dust detection in western and southwestern Iran based on DAI index algorithm and Modis spectral data,” ENVIRONMENTAL SCIENCES, vol. 17, no. 3 , pp. 151–162, 2019, [Online]. Available: https://sid.ir/paper/117731/en

Related Journal Papers