Evaluation of the effect of land use / land cover and vegetation cover change on land surface temperature: The case of Aydın province

Atak, Birsen Kesgin; Tonyaloğlu, Ebru Ersoy

doi:10.18182/tjf.786827

Cited by 6 publications

(3 citation statements)

References 33 publications

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“…LST is measured through remote sensing methods using satellite image data and mapping the thermal energy released to the atmosphere from the earth. The LST measurements from thermal satellite images are easy, fast, continuous and very reliable as it allows calculating the energy emitted from the earth to the atmosphere (Celik et al, 2019;Atak and Tonyaloğlu, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Greenhouse gas emissions and LULC changes are the main factors affecting LST values (Sharma and Joshi, 2016;Koday and Kızılkan, 2019;Atak and Tonyaloğlu, 2020;Das et al 2021;Das, 2022;Amadou and Arouna, 2022). Industrialization mainly depended on fossil fuels escalates greenhouse gas emissions, increasing the rate of greenhouse gases in the lower atmosphere (troposphere).…”

Section: Introductionmentioning

confidence: 99%

“…Impervious surfaces such as buildings and roads reflect radiation, but surfaces vegetation or covered with permeable materials absorb most radiation (Pal and Ziaul, 2017). Therefore, LULC changes affect LST values by changing the radiation absorption rates of the land surface (Atak and Tonyaloğlu, 2020).…”

Section: Introductionmentioning

confidence: 99%

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The Effects of Urbanization and Vegetation Cover on Urban Heat Island: A Case Study in Osmaniye Province

Çolakkadıoğlu

2023

International Journal of Environment and Geoinformatics

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This study analyzed the changes in the urban heat island effect in the 30 years (from 1990 to 2021) in the central district of Osmaniye. In this sense, there were two primary goals. Firstly, Land use/land cover change (LULC), land surface temperature (LST), normalized difference built-up index (NDBI), and normalized difference vegetation index (NDVI) were analyzed by using remote sensing methods between 1990 and 2021. Secondly, a linear regression analysis was conducted to determine the factors associated with LST, NDVI, and NDBI. The study results revealed increases in urban surfaces and the average land surface temperature values in the past 30 years and showed a decline in the vegetation with low, medium, and high NDVI values. The regression analysis results indicated a strong negative relationship between LST and NDVI and a strong positive relationship between LST and NDBI. It was also found a robust negative relationship between NDBI and NDVI. In light of the findings, it was stated that the amount of open and green areas should be increased in order to prevent the negative effects of the urban heat island in the central district of Osmaniye. For this purpose, it has been proposed to encourage green roof systems throughout the city, to create city parks and to create a green belt system. In addition, as a result of the study, the importance of preventing forest destruction caused by over-settlement in the Amanos Mountains, which is one of the rare habitats of the world with different plant species, was emphasized. In this sense, legal sanctions should be employed to protect those areas and prevent construction.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Effects of Urbanization and Vegetation Cover on Urban Heat Island: A Case Study in Osmaniye Province

Çolakkadıoğlu

2023

International Journal of Environment and Geoinformatics

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Assessment of vegetation change using NDVI, LST, and carbon analyses in Çankırı Karatekin University, Turkey

Şahin Körmeçli,

Seçkin Gündoğan

2024

Environ Monit Assess

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Changes of Remote Sensing Data in Urban Buildings Based on Neural Network Algorithm

Xue

Meng

2022

Mobile Information Systems

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Remote sensing data refer to remote sensing data sets with typical big data characteristics obtained by various remote sensing technologies. Based on this understanding, massive remote sensing datasets are the main method, and auxiliary data from other sources are integrated. The DN value (digital number) is the brightness value of the remote sensing image pixel and the gray value of the recorded ground objects. Unitless is an integer value. The value is related to the sensor’s radiation resolution, ground object emissivity, atmospheric transmittance, and scattering rate. This study aims to study the neural network algorithm for remote sensing data changes in urban buildings. This study deliberately goes to Tianjin Binhai New Area, taking this as an example to analyze and study the change of construction land. It uses satellite remote sensing data as a basis to analyze the trend of its building land. This study proposes which factors lead to the decline of urban construction land in Tianjin Binhai New Area. Finally, through experimental research and analysis, it is found that from 1996 to 2016, the registered population of Tianjin Binhai New Area has increased a lot, accounting for 26.49% of the total population. The number of urban employees increased by 956,500. This is also the leading factor in the direction of the city for the building.

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Evaluation of the effect of land use / land cover and vegetation cover change on land surface temperature: The case of Aydın province

Cited by 6 publications

References 33 publications

The Effects of Urbanization and Vegetation Cover on Urban Heat Island: A Case Study in Osmaniye Province

The Effects of Urbanization and Vegetation Cover on Urban Heat Island: A Case Study in Osmaniye Province

Assessment of vegetation change using NDVI, LST, and carbon analyses in Çankırı Karatekin University, Turkey

Changes of Remote Sensing Data in Urban Buildings Based on Neural Network Algorithm

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