کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6729888 504005 2016 27 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Prediction of surface temperatures for the assessment of urban heat island effect over Ahmedabad city using linear time series model
ترجمه فارسی عنوان
پیش بینی دمای سطح برای ارزیابی اثر بخشی گرمایی شهری در شهرستان احمدآباد با استفاده از مدل سری زمانی خطی
کلمات کلیدی
جزیره گرمایی شهری، دمای سطح زمین، مدل سری زمانی خطی، شاخص رشد گیاهی مدل ارتفاع دیجیتال، تراکم جاده،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
Ahmedabad is one of the fastest growing metropolitan cities in India showing rapidly urbanizing agglomeration. Due to the rapid urbanization natural land surfaces are being replaced by anthropogenic materials which negatively impact the environment resulting in urban heat island (UHI) effect. Land surface temperature (LST) is the primary and key step for the analysis of UHI effect. The present study has been carried out to predict the land surface temperatures for the assessment of UHI effect of area surrounding Ahmedabad city. Remote sensing data from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensors has been used for the present study for the prediction of LST. Linear time series (LTS) model has been developed from LST values of 10 years along with enhanced vegetation index (EVI), road density (RD) and elevation as other parameters to predict LST for the year subsequent to the 10 year data period. The results of the model have been validated using the observed data of year 2014. A comparison of the model predicted LST and observed LST shows that the range of mean absolute error (MAE) and mean absolute percentage error (MAPE) varies between 0.23 K-0.31 K and 0.08%-0.10%, respectively. High correlation exists between the model predicted and observed LST with an average R2 value of 0.96. Hence, LTS model can be used as a significant tool to predict LST for the assessment of UHI effect at any location.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy and Buildings - Volume 128, 15 September 2016, Pages 605-616
نویسندگان
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