بررسی و مدل‌سازی تأثیر ترکیب و آرایش چشم‌انداز شهر یزد بر دمای سطح زمین با استفاده از یادگیری ماشین و داده‌های لندست-8 و سنتینل-2

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری سنجش از دور، مرکز مطالعات سنجش از دور و GIS، دانشگاه شهید بهشتی، تهران

2 استادیار اقلیم‌شناسی ماهواره‌ای، دانشگاه یزد، یزد

3 استادیار علوم ریاضی، دانشگاه یزد، یزد

4 دانشیار سنجش ‌از‌ دور، دانشگاه یزد، یزد

5 گروه سنجش ‌از دور، دانشگاه تهران، تهران

6 استاد سنجش از دور، دانشگاه تهران، تهران

چکیده

اثر جزیره گرمایی شهری به‌دلیل تلاقی با چالش‌های محیط زیستی مهم قرن بیست و یکم یکی از مهم‌ترین بررسی‌ها در مورد پدیده‌های محیط زیستی است. در همین راستا، مطالعه دمای سطح زمین (LST)، چشم‌انداز واضحی از بررسی جزایر گرمایی در شهرها به‌دست می‌دهد که با توجه به اقلیم گرم و خشک شهر یزد، بررسی وضعیت و عوامل اثرگذار بر LST در این شهر را ضروری می‌نمایاند. این پژوهش با استفاده از تصویر فیوژن شده طیفی و مکانی لندست-8 برای ماه آگوست سال 2020 میلادی و با بهره‌گیری از الگوریتم‌های یادگیری ماشین سعی دارد تا تغییرات LST را با محاسبه پارامترهای مختلف مرتبط با چشم‌انداز سطح زمین شهری مدل کند. بر اساس نتایج این پژوهش، فیوژن طیفی-مکانی تصویر لندست-8 با سنتینل-2 به روش بارزسازی پن، موجب افزایش 10.7%ی دقت کلی و 16.5%ی ضریب کاپا در طبقه بندی این تصویر شد. این پژوهش همچنین نشان داد که اکثر پارامترهای مرتبط با همسایگی با پوشش اراضی در رده 1 تا 11 تأثیرگذاری بر LST شهر یزد قرار دارند. دراین‌بین، مجاورت با پوشش زمین‌های بایر در شعاع 100، 50 و 150 متر به‌ترتیب رتبه 1 تا 3 مهم‌ترین پارامترهای اثرگذار بر LST را از آن خود کردند. این پژوهش نشان داد که تغییر آرایش پوشش اراضی می‌تواند بر LST اثرگذار بوده و تغییر پوشش زمین‌های بایر به مناطق ساخته‌شده، تا °C 1.1، به پوشش گیاهی، تا °C 2.1 و تغییر 30% از زمین‌های بایر به پوشش گیاهی، تا °C 1.6 می‌تواند میانگین LST را در شهر یزد کاهش دهد. همچنین این پژوهش با بررسی دو رویکرد مختلف شبیه‌سازی ایجاد پوشش گیاهی در سطح شهر یزد نشان داد که رویکرد صرفه جویی در زمین می‌تواند میانگین LST را در شهر یزد تا 1.3 درجه و رویکرد تقسیم زمین تا °C 1.4 کاهش دهد.

کلیدواژه‌ها

عنوان مقاله [English]

Investigating and Modeling the Effect of the Composition and Arrangement of the Landscapes of Yazd City on the Land Surface Temperature Using Machine Learning and Landsat-8 and Sentinel-2 Data

نویسندگان [English]

  • Mohammad Mansourmoghaddam 1
  • Iman Rousta 2
  • Mohammad Sadegh Zamani 3
  • Mohammad Hossein Mokhtari 4
  • Mohammad Karimi Firozjaei 5
  • Seyed Kazem Alavipanah 6
1 Ph.D. Student of Remote Sensing, R.S. & GIS, Research Center, Shahid Beheshti University,
2 Assistant Prof. of Satellite Climatology, Yazd University
3 Assistant Prof. of Mathematics, Yazd University
4 Associate Prof. of Remote Sensing, Yazd University
5 Dep. of Remote Sensing, Tehran University
6 Prof. of Remote Sensing, Tehran University
چکیده [English]

The effect of urban thermal islands due to intersections with major environmental challenges of the 21st century is one of the most important studies on environmental phenomena, and in this regard, the study of the land surface temperature gives a clear perspective of the thermal islands in cities, which, according to the warm and dry climate of Yazd, examines the status and factors affecting the land surface temperature in this city seem to be necessary. This research, using the spectrally and spatially fused image of Landsat-8, for August 2020, and using machine learning algorithms, tries to model the changes in land surface temperature by calculating different parameters related to urban land perspective. Based on the results of this study, the spectral-spatial fusion of Landsat-8 with Sentinel-2 by Pan sharpening, increased 10.7% of the overall accuracy and 16.5% of the Kappa coefficient in the classification of this image. The study also showed that most neighboring parameters associated with land cover are ranked 1 to 11 of influencing the land surface temperature of Yazd city. In this area, the proximity to bare lands in the radius of 100, 50, and 150 meters ranked 1 to 3 of the most important parameters affecting the land surface temperature respectively. This study showed that the change in land cover arrangement could affect the land surface temperature and changing the bare lands to the built-up areas, up to 1.1°C, to vegetation, up to 2.1°C, and changing 30% of bare land to vegetation, up to 1.6°C can reduce the average land surface temperature in Yazd. Also, this study showed that two different models of vegetation simulation in Yazd city showed that the "land-sparing " model could reduce the average land surface temperature in Yazd by 1.3° and the "land-sharing" model by 1.4°C.

کلیدواژه‌ها [English]

  • Gradient boosting
  • Image fusion
  • Urban parameters
  • Land cover simulation
  • Remote sensing

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