Comparison and Estimation of Surface Albedo of Various Levels of Land use by SEBAL and METRIC Methods

Asadi, Mehdi; khamran, Khalil Valizadeh; Baaghdeh, Mohammad; Adab, Hamed

doi:10.29252/jgs.20.59.157

Cited by 6 publications

(1 citation statement)

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“…In other words, the general albedo conditions are a function of the radiation angle and altitude, and other factors such as temperature, cloudiness, vegetation cover, soil moisture and even soil type play a role in the albedo of each place. In Iran, many researches have been done on albedo on a local scale (Kheirkhah Zarkesh et al, 2014;Akbarzadeh et al, 2013;Tazik et al, 2015;Firozi et al, 2018;Solaimani et al, 2018;Asadi et al , 2021). Albedo has been studied on a macro scale in some studies (Hejazizadeh, et al, 2017;Soltani Akmal, 2018;Karbalaee, 2020;Kefayat Motlagh, 2021).…”

Section: Introductionmentioning

confidence: 99%

Detection of Land Surface Albedo Changes over Iran using Remote Sensing Data

Motlagh

Darand

2023

Preprint

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Albedo is one of the key parameters in climatic studies. Investigating its temporal and spatial behavior can be a tool for understanding environmental changes. The MODIS sensor continuously produces the land surface albedo on a global scale and with the appropriate spatial resolution and makes it available to researchers. In this study, to analyze Iran’s surface albedo trend, first, the daily albedo data of the MODIS on Iran in the period from 1/1/2001 to 12/30/2021 with a spatial resolution of 500 meters was prepared from the NASA website. After the necessary pre-processing, the long-term seasonal and annual trend of Iran's albedo was calculated at the 90% confidence level using the non-parametric Mann-Kendall test. The findings showed that the albedo trend is positive in the lowland interior areas of Iran and negative in the highland areas. Since the decreasing trend of albedo in highland areas indicates the reduction of snow cover in these areas, this issue can challenge the life and water resources of these areas that rely on the accumulation of snow.

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Section: Introductionmentioning

confidence: 99%

Detection of Land Surface Albedo Changes over Iran using Remote Sensing Data

Motlagh

Darand

2023

Preprint

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Detection of land surface albedo changes over Iran using remote sensing data

Kefayat Motlagh,

Darand

2024

Meteorological Applications

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Albedo is one of the key parameters in climatic studies. Investigating its temporal and spatial behavior can be a tool for understanding environmental changes. The MODIS sensor continuously produces the land surface albedo on a global scale and with the appropriate spatial resolution and makes it available to researchers. In this study, to analyze Iran's surface albedo trend, first, the daily albedo data of the MODIS on Iran in the period from January 1, 2001 to December 30, 2021 with a spatial resolution of 500 m were prepared from the NASA website. After the necessary pre‐processing, the long‐term seasonal and annual trend of Iran's albedo was calculated at the 90% confidence level using the non‐parametric Mann–Kendall test. The findings showed that the albedo trend is positive in the lowland interior areas of Iran and negative in the highland areas. Since the decreasing trend of albedo in highland areas indicates the reduction of snow cover in these areas, this issue can challenge the life and water resources of these areas that rely on the accumulation of snow.

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Identification of the Driving factors impacts of Land Surface Albedo over Iran: An analysis with the MODIS data

Motlagh,

Darand

2024

Journal of Atmospheric and Solar-Terrestrial Physics

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Comparison and Estimation of Surface Albedo of Various Levels of Land use by SEBAL and METRIC Methods

Cited by 6 publications

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Detection of Land Surface Albedo Changes over Iran using Remote Sensing Data

Detection of Land Surface Albedo Changes over Iran using Remote Sensing Data

Detection of land surface albedo changes over Iran using remote sensing data

Identification of the Driving factors impacts of Land Surface Albedo over Iran: An analysis with the MODIS data

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