Land Use Analysis on Land Surface Temperature in Urban Areas Using a Geographically Weighted Regression and Landsat 8 Imagery, a Case Study: Tehran, Iran

Karimi, Amer; Pahlavani, Parham; Bigdeli, Behnaz

doi:10.5194/isprs-archives-xlii-4-w4-117-2017

Cited by 9 publications

(6 citation statements)

References 31 publications

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“…Other studies were conducted on the spatial distribution of LST in a small city in China or Korea (Buyadi et al 2013;Hu et al 2015;Babalola and Akinsanola 2016). Moreover, previous studies constructed only NDBI or NDVI to investigate the influence of land changes over LST (Karimi et al 2017;Xiong et al 2012;Pal and Ziaul 2017). Most studies only focused either on small cities or only one or two variables for assessing the impact of LST over land use.…”

Section: Introductionmentioning

confidence: 99%

Impact of Land Cover Changes on Land Surface Temperature and Human Thermal Comfort in Dhaka City of Bangladesh

et al. 2021

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Urbanization leads to the construction of various urban infrastructures in the city area for residency, transportation, industry, and other purposes, which causes major land use change. Consequently, it substantially affects Land Surface Temperature (LST) by unbalancing the surface energy budget. Higher LST in city areas decreases human thermal comfort for the city dwellers and affects the urban environment and ecosystem. Therefore, a comprehensive investigation is needed to evaluate the impact of land use change on the LST. Remote Sensing (RS) and Geographic Information System (GIS) techniques were used for the detailed investigation. RS data for the years 1993, 2007 and 2020 during summer (March–May) in Dhaka city were used to prepare land cover maps, analyze LST, generate hazard maps and relate the land cover change with LST by using GIS. The results show that the built-up area in Dhaka city increased by 67% from 1993 to 2020 by replacing lowland mainly, followed by vegetation, bare soil and water bodies. LSTs found in the study area were ranged from 23.26 to 39.94 °C, 23.69 to 43.35 °C and 24.44 to 44.58 °C for the years 1993, 2007 and 2020, respectively. The increases of spatially distributed maximum and mean LST were found 4.62 °C and 6.43 °C, respectively, for the study period of 27 years while the change in minimum LST was not substantial. LST increased by around 0.24 °C per year and human thermal discomfort shifted from moderate to strong heat stress for the total study period due to the increase of built-up and bare lands. This study also shows that normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were negatively correlated with LST while normalized difference built-up Index (NDBI) and normalized difference built-up Index (NDBAI) were positively correlated with LST. The methodology developed in this study can be adapted to other cities around the globe.

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Section: Introductionmentioning

confidence: 99%

Impact of Land Cover Changes on Land Surface Temperature and Human Thermal Comfort in Dhaka City of Bangladesh

et al. 2021

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“…In this study, land surface temperature (LST) was considered to be equivalent to the temperature below the urban atmosphere and to be the primary factor in the analysis of surface radiation and energy variations, the inner climate of buildings, and human comfort in the urban environment. Physical features and color of urban surfaces, sky-view factor, street geometry, traffic lines, and human-made changes in nature are some of the essential factors that determine LST in urban environments (Deo & Şahin, 2017;Jiang & Weng, 2017;Karimi, Pahlavani, & Bigdeli, 2017). In this study, the data needed to model LST, were extracted from Landsat 8 satellite images.…”

Section: Methodsmentioning

confidence: 99%

Computational modeling of land surface temperature using remote sensing data to investigate the spatial arrangement of buildings and energy consumption relationship

Faroughi

Karimimoshaver

Aram

et al. 2020

Engineering Applications of Computational Fluid Mechanics

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The effect of urban form on energy consumption has been the subject of various studies around the world. Having examined the effect of buildings on energy consumption, these studies indicate that the physical form of a city has a notable impact on the amount of energy consumed in its spaces. The present study identified the variables that affected energy consumption in residential buildings and analyzed their effects on energy consumption in four neighborhoods in Tehran: Apadana, Bimeh, Ekbatan-phase I, and Ekbatan-phase II. After extracting the variables, their effects are estimated with statistical methods, and the results are compared with the land surface temperature (LST) remote sensing data derived from Landsat 8 satellite images taken in the winter of 2019. The results showed that physical variables, such as the size of buildings, population density, vegetation cover, texture concentration, and surface color, have the greatest impacts on energy usage. For the Apadana neighborhood, the factors with the most potent effect on energy consumption were found to be the size of buildings and the population density. However, for other neighborhoods, in addition to these two factors, a third factor was also recognized to have a significant effect on energy consumption. This third factor for the Bimeh, Ekbatan-I, and Ekbatan-II neighborhoods was the type of buildings, texture concentration, and orientation of buildings, respectively.

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“…Some researchers acknowledge that land degradation that is the change in land cover from vegetated land to open or built areas causes heating of air temperature and is a significant factor in increasing evapotranspiration. Land degradation also causes more runoff or surface flow than infiltration, and the increasing air temperature and surface flow will increase potential evapotranspiration (Karimi et al, 2017;Rushayati et al, 2018;Ping and Liu, 2018). In contrast, researchers also found that the deforestation process can also reduce evapotranspiration because of reduced transpiration by plants (Snyman, 2001;Feddema and Freire, 2001;Zeng and Yang, 2008;Li et al, 2013;Gong, 2017;Karimi et al, 2017;Rushayati et al, 2018;Ping and Liu, 2018).…”

Section: Analysis Of Evapotranspiration In Indonesian Tropical Areamentioning

confidence: 99%

Evapotranspiration of Indonesia Tropical Area

Marganingrum

Santoso

2019

J. Presipitasi

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Indonesia is an archipelago country with a tropical climate. The region of Indonesia is quite large and located between two continents (Asia and Australia) and between two oceans (Indian and Pacific), making the territory of Indonesia has a unique climate pattern. One of the climate variables that quite important to be studied in this chapter is evapotranspiration. The Thornthwaite method was used to estimate potential evapotranspiration based on average air temperature. The relationships between evapotranspiration, precipitation, and elevation were then examined. Besides, temperature variations that affect climate patterns between monsoonal and equatorial regions were compared, between the mainland and small islands, and between mountain and coastal area. The impact of global warming was also examined on the climate and potential evapotranspiration of the Indonesian region. Data analysis showed that evapotranspiration correlates weakly with precipitation, and the contrary, the evapotranspiration correlates strongly with elevation, with correlation indices of 0.02 and 0.89, respectively. The study confirmed that air temperature is the primary controlling variable of the evapotranspiration in this very heterogeneous landscape. Under a global temperature increase of 1.5 °C above the pre-industrialized year (1765), the evapotranspiration is expected to increase in a range from 4.8 to 11.1%. In general, the excess of water to restore soil moisture in the future tends to decrease, i.e., drier.

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Land Use Analysis on Land Surface Temperature in Urban Areas Using a Geographically Weighted Regression and Landsat 8 Imagery, a Case Study: Tehran, Iran

Cited by 9 publications

References 31 publications

Impact of Land Cover Changes on Land Surface Temperature and Human Thermal Comfort in Dhaka City of Bangladesh

Impact of Land Cover Changes on Land Surface Temperature and Human Thermal Comfort in Dhaka City of Bangladesh

Computational modeling of land surface temperature using remote sensing data to investigate the spatial arrangement of buildings and energy consumption relationship

Evapotranspiration of Indonesia Tropical Area

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