بررسی تغییرات جزایر حرارتی سطحی با استفاده از شاخص‌های پوشش گیاهی (مطالعه موردی: شهرستان سرپل‌ذهاب)
محورهای موضوعی : منابع طبیعی و مدیریت زیست محیطی
1 - استادیار دانشکده جغرافیا و علوم محیطی دانشگاه حکیم سبزواری
کلید واژه: شهرستان سرپل‌ذهاب, سنجش از دور, لندست, تغییرات دمایی, پوشش‌گیاهی,
چکیده مقاله :
تحقیق حاضر به منظور اندازه‌گیری تغییرات جزایر گرمایی سطحی شهری در 3 مقطع زمانی 1984، 1998 و 2016 با استفاده از شاخص‌های پوشش گیاهی، شاخص ساخت و ساز شهری و شاخص دمای سطح زمین انجام شده است. بدین منظور پس از تعیین حدود منطقه، مراحل پیش‌پردازش شامل تصحیحات رادیومتریک و اتمسفری تصاویر، چینش باندها، موزاییک و برش تصاویر بر اساس محدوده مطالعاتی بر روی تصاویر سنجنده TM و ETM+ لندست 8 صورت گرفت. سپس شاخص‌هایNDVI، SAVI و NDBI بر روی تصاویر اعمال شد و از طریق تفاضل تصاویر، مبادرت به پایش زمانی و مکانی پوشش گیاهی گردید و تغییرات در قالب سه نوع کاهشی، افزایشی و بدون تغییر مورد بررسی قرار گرفت. همچنین جهت محاسبه شاخص (LST) از باندهای حرارتی 10 و 11 لندست 8 و باند 6 لندست 5 استفاده شد.نتایج نشان دادکه دو شاخص NDVI و SAVI روند کاهشی داشته‌اند ولی شاخص NDBI روند افزایشی داشته است. بطوری که میزان تغییرات در بازه اول از 77 درصد به 63 درصد در شاخص SAVIودر شاخص NDVI از 45 درصد به 41 درصد کاهش پیدا کرده در حالی که شاخص NDBI در بازه اول 51 درصد بوده و در بازده دوم به 57 درصد افزیش پیدا کرده است. در همین بازه، شاخص LST روندی ناهمگون داشته ولی به نظر می رسد توزیع این شاخص از حالت گسترده به حالت لکه ای تغییر یافته است بدین معنی که امواج حرارتی در آینده بصورت موضعی در مناطقی از شهر که دچار مشکل تهویه هستند رخ داده و می تواند کیفیت زندگی را کاهش داده و زمینه برای بیماری های مرتبط را فراهم سازد. بنابراین مناطق ساخته شده شهری موجب تشدید جزایر شهری و تراکم پوشش گیاهی باعث تعدیل جزایر حرارتی شهری گردیده است.
The present research was conducted in order to measure the changes of urban surface heat islands in 3 time periods of 1984, 1998 and 2016 using vegetation indices, urban built-up areas index and land surface temperature index. For this purpose, after determining the boundaries of the area, pre-processing steps including radiometric and atmospheric corrections of images, arrangement of bands, mosaicing and cropping of images based on the study area were carried out on TM and ETM+ Landsat 8 sensor images. Then, NDVI, SAVI and NDBI indexes were applied on the images and through the difference of the images, temporal and spatial monitoring of vegetation cover was started and changes were studied in the form of three types of decrease, increase and no change. Also, to calculate the surface temperature index (LST), thermal bands 10 and 11 of Landsat 8 and band 6 of Landsat 5 were used. The results showed that the two indices NDVI and SAVI had a decreasing trend, but the NDBI index had an increasing trend so that the amount of changes in the first period decreased from 77% to 63% in the SAVI index and in the NDVI index from 45% to 41%, while the NDBI index was 51% in the first period and increased to 57% in the second period. In the same period, the LST index has had a heterogeneous trend, but it seems that the distribution of this index has changed from a widespread state to a patchy state, which means that in the future, heat waves will occur locally in areas of the city that have ventilation problems and It can reduces the quality of life and provides the basis for related diseases. Therefore, built-up urban areas have intensified urban heat islands and the density of vegetation has moderated urban heat islands.
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