تأثير كاربري اراضي بر تغييرات شاخص حرارتي زمين در حوضه‌هاي شهري (مطالعۀ موردي: بندر امام خميني، خوزستان)

Assessment the Effect of Land use based on changes of the land surface temperature index in urban basins (Case Study: Bandar-e Emam Khomeyni, Khuzestan (

اﻣﺮوزه روشﻫﺎي ﺳـﻨﺠﺶ از دوري ﮐﺎراﯾﯽ ﺑﺎﻻﯾﯽ در ﺑﺮآورد ﺻﺤﯿﺢ ﺗﻐﯿﯿﺮات ﺟﺰﺋﯽ ﺣﺮارﺗﯽ و ﭘﺎﯾﺶ ﺗﻐﯿﯿﺮات اﻗﻠﯿﻤﯽ دﻗﯿﻖ اراﺿﯽ داﺷﺘﻪ اﺳﺖ. ﻣﻄﺎﻟﻌﮥ ﺣﺎﺿﺮ در اﺑﺘﺪا ﺑﺎ اﺳﺘﻔﺎده از ﺗﮑﻨﯿﮏﻫﺎي ﺳﻨﺠﺶ از دور ﺑﻪ ﺗﺄﺛﯿﺮ ﮐﺎرﺑﺮي اراﺿﯽ ﺑﺮ ﺷﺎﺧﺺ ﺣﺮارﺗﯽ، ﺳﭙﺲ ﮐﺎراﯾﯽ ﺑﺎﻧﺪﻫﺎي ﺣﺮارﺗﯽ در ﺗﻌﯿﯿﻦ دﻣﺎي ﮐﺎرﺑﺮي اراﺿﯽ و در ﻧﻬﺎﯾﺖ ﺗﻌﯿﯿﻦ ﺷﺎﺧﺺ دﻣﺎي ﺳﻄﺢ زﻣﯿﻦ1در ﻫﺮ ﮐﺎرﺑﺮي ﺑﺎ اﺳﺘﻔﺎده از اﻟﮕﻮرﯾﺘﻢ ﭘﻨﺠﺮة ﻣﺠﺰا2 در ﻣﻨﻄﻘﮥ ﺑﻨﺪر اﻣﺎم ﺧﻤﯿﻨﯽ اﺳﺘﺎن ﺧﻮزﺳﺘﺎن ﭘﺮداﺧﺘﻪ اﺳﺖ. در اﺑﺘﺪا ﺷﺎﺧﺺ ﭘﻮﺷﺶ ﮔﯿﺎﻫﯽ3، ﺑﺎ ﻧﺴﺒﺖﮔﯿﺮي اﺧﺘﻼف ﺑﺎزﺗﺎب ﺑﺎﻧﺪ ﻣﺎدون ﻗﺮﻣﺰ ﻧﺰدﯾﮏ و ﺑﺎﻧﺪ ﻗﺮﻣﺰ ﺑﺎ ﺗﺼـﺎوﯾﺮ ﻣﺎﻫﻮارة ﻟﻨﺪﺳـﺖ 8 و ﻣﻮدﯾﺲ، ﺳـﭙﺲ ﺑﻪ ﺗﻬﯿﮥ ﻧﻘﺸﮥ دﻣﺎي ﺳﻄﺢ زﻣﯿﻦ در ﭼﻬﺎر ﻓﺼﻞ ﭘﺮداﺧﺘﻪ ﺷﺪ. اﻟﮕﻮرﯾﺘﻢ ﭘﻨﺠﺮة ﻣﺠﺰا، ﯾﮑﯽ از اﻟﮕﻮرﯾﺘﻢﻫﺎي ﮐﺎرﺑﺮدي و دﻗﯿﻖ ﺳــﻨﺠﺶ از دوري اﺳــﺖ ﮐﻪ ﺑﺎ ﺣﺬف اﺛﺮات ﺟﻮي ﻣﯽﺗﻮاﻧﺪ دﻣﺎي ﺳــﻄﺤﯽ زﻣﯿﻦ را ﺑﻪ ﺻـﻮرت ﻣﻨﻄﻘﻪاي ﭘﺎﯾﺶ و اﻧﺪازهﮔﯿﺮي ﻧﻤﺎﯾﺪ. ﻧﺘﺎﯾﺞ ﻣﻘﺎﯾﺴـﮥ دو ﺑﺎﻧﺪ ﺣﺮارﺗﯽ ﻧﺸﺎن داد، ﺑﺎﻧﺪ ﺣﺮارﺗﯽ RMSE4= 3/7)11)، ﺑﻪ دﻟﯿﻞ ﻃﻮل ﻣﻮج ﺑﺎﻻﺗﺮ، از دﻗﺖ ﺑﺎﻻﺗﺮي (ﺿﺮﯾﺐ ﺗﺒﯿﯿﻦ 0/9)، در ﺑﺮآورد دﻣﺎي ﺳﻄﺤﯽ، ﺧﺼﻮﺻﺎً در دﻣﺎﻫﺎي ﺑﺎﻻ، ﻧﺴﺒﺖ ﺑﻪ ﺑﺎﻧﺪ ﺣﺮارﺗﯽ10(4/4 =RMSE) ﺑﺮﺧﻮردار اﺳــﺖ. ﻧﺘﺎﯾﺞ ﺑﺮآوردﻫﺎ در ﻧﻘﺎط ﮐﻤﯿﻨﻪ و ﺑﯿﺸــﯿﻨﮥ دﻣﺎي ﮐﺎرﺑﺮيﻫﺎي ﻣﺨﺘﻠﻒ ﻧﺸــﺎن داد، ﻣﻨﺎﻃﻖ ﺻــﻨﻌﺘﯽ و ﮐﺎرﺧﺎﻧﻪﻫﺎ، ﺑﺎ ﺟﺬب ﻃﻮل ﻣﻮج ﻣﺎدون ﻗﺮﻣﺰ ﺣﺮارﺗﯽ و اﻓﺰاﯾﺶ ﮔﺴﯿﻞﻣﻨﺪي، ﻧﺴﺒﺖ ﺑﻪ ﭘﻮﺷﺶﻫﺎي درﺧﺘﯽ و رودﺧﺎﻧﻪﻫﺎ ﺗﺄﺛﯿﺮ ﺑﯿﺸﺘﺮي در ﺑﺎﻻ ﺑﺮدن ﻣﯿﺎﻧﮕﯿﻦ ﻧﺴـﺒﯽ دﻣﺎي ﻣﻨﻄﻘﻪ در ﻣﺤﺪودة ﺻﻨﻌﺘﯽ و ﺷﻬﺮي داﺷﺘﻪاﻧﺪ. ﺑﺎ ﺻﻨﻌﺘﯽ ﺷﺪن ﻣﻨﻄﻘﻪ، ﻣﯿﺰان ﺷﺎﺧﺺ ﭘﻮﺷﺶ ﮔﯿﺎﻫﯽ ﺑﺎ اﻓﺰاﯾﺶ دﻣﺎي ﻫﻮا، ﮐﺎﻫﺶ ﯾﺎﻓﺘﻪ اﺳــﺖ. ﺑﻪﻃﻮريﮐﻪ ﮐﻤﺘﺮﯾﻦ ﻣﯿﺰان ﭘﻮﺷــﺶ ﮔﯿﺎﻫﯽ در ﻣﺎه ﻣﺮداد (0/42-) و ﺑﯿﺸــﺘﺮﯾﻦ ﻣﻘﺪار در ﻣﻬﺮﻣﺎه (0/35) ﺑﺮآورد ﺷﺪ.

The phenomenon of climate change and global warming and its impact on different ecosystems Needed extensive studies. For this purpose, was done Study of the efficiency of thermal bands and land use changes in determining the surface temperature index using a separate window algorithm in the Bandar-e Emam Khomeyni of Khuzestan province by Landsat 8 satellite imagery. Based on this, was used vegetation index (NDVI) for band ratio between the red and near infrared bands to prepare the LST map and were used four seasonal images in 2016-2017 years. The results of the comparison of the two thermal bands showed that the thermal bond 11 is higher accuracy than the thermal bond 10 (RMSE = 3.6 for the band 11 and RMSE = 4.4 for the band 10) because the wavelength of it is higher. Also, the estimation of the comparison of satellite imagery data with ground truth showed a high accuracy (R2 =0.9). Comparing the temperature of the users was determined that the industrial and urban areas more effective on increasing LST than the vegetation and water areas. Base on bands ratio between near and red infrared bands showed that the vegetation index decreased with increasing temperature. So, the lowest amount of vegetation was estimated in August (-0.42) and the highest was in October (0.35).