برآورد دمای سطح زمین با استفاده از الگوریتم RTE و بررسی ارتباط آن با کاربری های زمین، مطالعه موردی: شهر کرج (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
دمای سطح زمین یک پدیده مهم در بسیاری از زمینه ها مانند تغییرات جهانی اقلیم، هیدرولوژیکی، کشاورزی و کاربری زمین محسوب می شود. ارتباط بین دمای سطح زمین و کاربری زمین به ویژه پوشش گیاهی، از جمله مسائل موردتوجه در این زمینه است. هدف پژوهش حاضر، برآورد دمای سطح زمین با استفاده از روش معادلات انتقال تابشی و بررسی ناهمگنی مکانی آن در شهر کرج است. در این پژوهش، با تحلیل داده های ماهواره ای لندست 8، نقشه دمای سطح زمین با استفاده از الگوریتم معادله انتقال تابشی و نقشه پوشش زمین شهر کرج با روش ماشین بردار پشتیبان استخراج شد. نتایج نشان داد تصاویر ماهواره ای کارایی بالایی در برآورد دمای سطح زمین و بررسی ارتباط آن با کاربری زمین و پوشش گیاهی دارد. بررسی سهم هر کاربری در طبقات دمایی سطح شهر کرج آشکار ساخت زمین های بایر با دمای 04/43 درجه سانتی گراد، بیشترین نقش را در افزایش دمای شمال و جنوب غرب شهر کرج و کاربری باغات و فضای سبز با دمای کمتر (31/30– 08/27 درجه سانتی گراد) بیشترین نقش را در کاهش دمای نواحی مرکزی داشتند. همچنین نتایج نشان داد مناطق مسکونی و انسان ساخت مرتفع و جاده ها با کمربند سبز درختی اطراف خود، وضعیت بهتری از نظر شرایط دمایی دارند. علاوه بر آن، نتایج به دست آمده اهمیت وجود فضاهای سبز شهری را در تعدیل دمای سطح زمین به ویژه در مناطق شهری آشکار ساخت. بنابراین، با توجه به افزایش شهرنشینی و اهمیت دستیابی به شرایط دمایی مطلوب، ایجاد و توسعه فضاهای سبز در برنامه های توسعه شهری توسط برنامه ریزان و طراحان شهری می تواند پایداری شهر را به دنبال داشته باشد.Estimating land surface temperature using the rte algorithm and investigating its relationship with Land Use: A case study of Karaj city
Land surface temperature is essential in many fields, such as global climate changes, hydrological, agricultural, and land use. The relationship between land surface temperature and land use, especially vegetation, is one of the important issues in this field. This research aims to estimate the land surface temperature using the method of Radiative Transfer Equations and to investigate its locative heterogeneity in the city of Karaj. In this research, by analyzing the Landsat 8 satellite data, the land surface temperature map was extracted using the Radiative Transfer Equation (RTE) algorithm, and the land use/ cover map was extracted using the Support Vector Machine method. Investigating the contribution of each land use in temperature classes in Karaj city showed that bare lands with 43.04°C had the highest role in increasing the temperature of the north and southwest of Karaj. The gardens and green spaces land use with lower temperatures (27.08-30.31 °C) had the highest role in decreasing the temperature of central areas. Also, the results showed that high residential areas and roads with tree green belts around them have better conditions in terms of thermal comfort. In addition, the results revealed the importance of urban green spaces in regulating the earth's surface temperature, especially in urban areas. Therefore, due to the increasing urbanization and the importance of achieving favorable temperature conditions, the creation and development of green space in urban development plans by urban planners and designers can lead to the city's sustainability
Extended Abstract
Introduction
Estimating land surface temperature is crucial for understanding climate change, energy balance, and vegetation coverage. According to the vegetation, water, soil, and built-up areas, LST is variable, and its accurate estimation is complicated due to its many applications in different fields of knowledge. Research has shown that the type of land use can, directly and indirectly, affect LST; for example, industrial or urban use usually increases the temperature, while the levels of agricultural use or green spaces cause a decrease in LST. In addition, land cover indexes such as the Normalized Difference Vegetation Index (NDVI) also have a significant correlation with temperature changes, and these indexes significantly affect LST. Therefore, understanding the spatial relationships of LST and different land uses can be very important in urban studies and land planning. In order to estimate LST, various algorithms have been developed using the analysis of satellite images. Research has shown that the LST obtained from the radiative transfer equation algorithm is closer to the weather station temperature and provides acceptable results. Based on this, considering the importance of studying and investigating temperature changes in urban land use, the relationship between land surface temperature and types of land use and the normalized vegetation difference index was studied in Karaj city. This study aims to estimate LST using the RTE method to retrieve LST and analyze its spatial characteristics in relation to the land use/land cover of Karaj city. The results of this research can help to better understand the effect of land use and vegetation on the LST and could be used in decisions related to urban development and green space in this region.
Methodology
In this research, Landsat 8 satellite sensor data were utilized to extract land use maps, the Normalized Difference Vegetation Index and to generate Land Surface Temperature (LST) maps for August 2021. To conduct the present research, satellite image preprocessing was performed after collecting and obtaining the necessary data from the USGS website. This involved using the Atmospheric and Radiometric Correction tool (Flaash) in the ENVI 5.6 software environment to rectify systematic and non-systematic errors in the digital data acquired through satellite imaging. In the current study, focusing on changes in land surface temperature across different land use types, a Support Vector Machine (SVM) classification method was employed to generate a land use/land cover map in the ENVI 5.6 software. Subsequently, the accuracy and precision of the classified map were assessed using the error matrix function. In the next step, considering the relationship between spectral indices and land surface temperature, the NDVI index was utilized to investigate the correlation between Land Surface Temperature and vegetation cover. For spatial analysis of temperature changes, the Land Surface Temperature was initially estimated using the Radiative Transfer Equation (RTE) and an open-source Python-based software called "LST." The Natural Breaks function calculates the average Land Surface Temperatures for different land use categories. Subsequently, a matching process was conducted utilizing the Zonal Statistics function in the ArcGIS software for each of the various land use categories within the urban area.
Results and discussion
The study findings indicate that the type of land use (such as residential and urban green spaces) directly and indirectly impacts Land Surface Temperature. As mentioned, the Land Surface Temperature was calculated using the RTE algorithm. The RTE algorithm is more accurate than similar algorithms in retrieving Land Surface Temperature because it relies on physics-based Radiative Transfer Equations. Then, by generating a land use map to determine the contribution of each land use to Land Surface Temperature changes, it was demonstrated that the majority of the area in Karaj city is attributed to residential land use (42.67%), followed by orchards and urban green spaces, covering 14.85% of the area. In the context of the relationship between urban form and land surface temperature in arid and semi-arid regions, residential areas and roads in the central regions of Karaj city fell into the second thermal zone (30.31), registering lower temperatures compared to other areas. The reason for this is the presence of tall and dense buildings with surrounding vegetation in these areas, which, by creating shade, have taken on the role of temperature moderation. Urban green spaces effectively reduce ambient temperature through their evaporation and transpiration processes. By examining the study area on the outskirts of Karaj city, higher temperatures were observed compared to the city centers. This may be because of the lack of green space development on the city's outskirts and the presence of land without vegetation cover.
Conclusion
This study was conducted to analyze the spatial characteristics of Land Surface Temperature and its relationship with land use/land cover in Karaj city for August 2021. As mentioned, with the high precision of the Radiative Transfer Equation method, the Land Surface Temperature was calculated. Based on the current research findings, in arid and semi-arid regions, especially in urban areas, the Land Surface Temperature is lower compared to other land uses. The reason for this is the presence of tall and dense buildings with surrounding vegetation in these areas, which, by creating shade, have taken on the role of temperature moderation. However, this does not mean that urban green spaces and orchards do not play a role in cooling the city. On the contrary, plants contribute to temperature reduction through shading and high evaporation and transpiration rates. Furthermore, this research identified that bare lands play the most significant role in increasing Land Surface Temperature. These bare lands are situated as large patches on the outskirts of Karaj city. Information about Land Surface Temperature and its relationship with land surface features can be obtained by analyzing satellite images. Therefore, understanding the spatial relationships between LST and land use can be important in future studies and urban planning. Urban planners and designers can take effective steps in achieving sustainable urban development against temperature changes by predicting and planning for future changes.
Funding
There is no funding support.
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
Conflict of Interest
Authors declared no conflict of interest.
Acknowledgments
We are grateful to all the scientific consultants of this paper.
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