Effect of Atmospheric Mixing on Spectral Reflectivity in Sentinel Images of Baghdad Province

The lowest layer of the atmosphere is called the atmospheric mixed layer, characterized by small-scale, irregular air motions defined by winds that change in speed and direction. Aerosol radiative effects impact the atmospheric boundary layer (ABL), which holds most aerosols in the lower atmosphere. Aerosol absorption and scattering both lower the quantity of solar energy that reaches the ground, which has an impact on the spectral signature of the land coverings. In this study, 51 locations in downtown Baghdad were chosen for four different types of land cover (water bodies, farms, open areas, and residential areas) for Sentinel 2 satellite imagery, and the time the pictures were taken was 8:00 am ( 22 March, 22 June, 20 September, and 22 December) 2021. Their spectral reflectance was calculated at the NIR band using a mathematical equation in the ArcGIS program for Sentinel 2 satellite images that had been processed and analyzed. Also, atmospheric boundary layer height and solar radiation values were downloaded for the same date as the satellite images and compared with the spectral reflectivity values of the land covers(agriculture area, residential area, open area, and river) and knowing the effect of the mixing layer and solar radiation on the spectral reflectance values. The highest value of spectral reflectivity, mixing layer height, and solar radiation was in June at (0.065, 1965.524629, and 897.7088) respectively. The spectral reflectivity of plants at near-infrared (NIR) was higher than the rest of the earth’s features because plants reflect near-infrared radiation and absorb the red and blue parts of the spectrum.

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Publication Details

Journal
Iraqi Journal of Science
Published
2024-09-30
DOI
https://doi.org/10.24996/ijs.2024.65.9.42
Citations
2
Primary Topic
Remote-Sensing Image Classification
Type
article
Field-Weighted Citation Impact
0.64
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article

Effect of Atmospheric Mixing on Spectral Reflectivity in Sentinel Images of Baghdad Province

Ahmed F. Hassoon, Eman S. Hassan, Ebtesam F. Khanjer
2 citations
Iraqi Journal of Science
Remote-Sensing Image Classification
0.64
article

Effect of Atmospheric Mixing on Spectral Reflectivity in Sentinel Images of Baghdad Province

Ahmed F. Hassoon, Eman S. Hassan, Ebtesam F. Khanjer
article en
2 citations

Abstract

The lowest layer of the atmosphere is called the atmospheric mixed layer, characterized by small-scale, irregular air motions defined by winds that change in speed and direction. Aerosol radiative effects impact the atmospheric boundary layer (ABL), which holds most aerosols in the lower atmosphere. Aerosol absorption and scattering both lower the quantity of solar energy that reaches the ground, which has an impact on the spectral signature of the land coverings. In this study, 51 locations in downtown Baghdad were chosen for four different types of land cover (water bodies, farms, open areas, and residential areas) for Sentinel 2 satellite imagery, and the time the pictures were taken was 8:00 am ( 22 March, 22 June, 20 September, and 22 December) 2021. Their spectral reflectance was calculated at the NIR band using a mathematical equation in the ArcGIS program for Sentinel 2 satellite images that had been processed and analyzed. Also, atmospheric boundary layer height and solar radiation values were downloaded for the same date as the satellite images and compared with the spectral reflectivity values of the land covers(agriculture area, residential area, open area, and river) and knowing the effect of the mixing layer and solar radiation on the spectral reflectance values. The highest value of spectral reflectivity, mixing layer height, and solar radiation was in June at (0.065, 1965.524629, and 897.7088) respectively. The spectral reflectivity of plants at near-infrared (NIR) was higher than the rest of the earth’s features because plants reflect near-infrared radiation and absorb the red and blue parts of the spectrum.

Iraqi Journal of Science
Openalex Percentile: Top 26%
Remote-Sensing Image Classification
0.64
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