Remote Sensing and GIS Applications in Environmental Sciences

Factors affecting ground surface temperature in urban areas: a case study of Karaj city

Document Type : Original Article

Author

student

10.22034/rsgi.2024.60692.1065

Abstract

The urban heat island (UHI) phenomenon caused by rapid urbanization has become an important global ecological and environmental problem that cannot be ignored. In this study, the effect of influencing factors on ground surface temperature in Karaj city was measured and using ordinary least square regression (OLS), geographic weighted regression (GWR) and multiscale geographic weighted regression (MGWR) models, spatial heterogeneities Factors affecting temperature were investigated.The results indicated that, compared with traditional OLS models, GWR improved the model fit by considering spatial heterogeneity, whereas MGWR outperformed OLS and GWR in terms of goodness of fit by considering the effects of different bandwidths on LST.Building density Normalized Difference Impervious Surface Index (NDISI) and traffic density had the greatest effect on high LST by 0.323, 0.246 and 0.260 respectively, while NDVI index, MNDWI and population density were negatively correlated with temperature. These findings show the need to consider spatial heterogeneity in the analysis of impact factors. This study can be used to provide guidance on strategies to reduce temperature in different regions.

Keywords

Main Subjects

پدیده جزیره گرمایی شهری )UHI( ناشی از شهرنشینی سریع به یک مشکل مهم اکولوژیکی و محیطزیستی جهانی تبدیل شده است که نمیتوان آن را نادیده گرفت. در این مطالعه، اثر عوامل تاثیر گذار بر روی دمای سطح زمین در شهر کرج اندازهگیری شد و با استفاده از رگرسیون حداقل مربعات معمولی )OLS(، مدلهای رگرسیون وزندار جغرافیایی )GWR( و رگرسیون وزندار جغرافیایی چند مقیاسی )MGWR(، ناهمگونیهای فضایی عوامل تأثیرگذار وLST را بررسی کردیم. نتایج نشان داد که در مقایسه با مدلهای OLS مرسوم، GWR با در نظر گرفتن ناهمگونی فضایی برازش مدل را بهبود بخشید، در حالی که MGWR از نظر خوبی برازش OLS و GWR با در نظر گرفتن اثرات پهنای باند مختلف بر LST بهتر عمل کرد. تراکم ساختمان، شاخص اختلاف نرمال شده سطح غیرقابل نفوذ )NDISI( و تراکم ترافیک به ترتیب 323/0، 246/0 و 260/0 بیشترین تاثیر بر LST بالا داشتند، در حالی که شاخص MNDWI ،NDVI و تراکم جمعیت با دما همبستگی منفی داشتند. این یافته ها نیاز به در نظر گرفتن ناهمگونی فضایی در تجزیه و تحلیل عوامل تاثیر را نشان میدهد. این مطالعه میتواند برای ارائه راهنمایی در مورد استراتژیهای برای کاهش دما در مناطق مختلف استفاده شود.

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Remote Sensing and GIS Applications in Environmental Sciences
Volume 4, Issue 11
August 2024
Pages 22-1
  • Receive Date: 29 February 2024
  • Revise Date: 25 July 2024
  • Accept Date: 20 August 2024