|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|5755422||1412666||2018||13 صفحه PDF||سفارش دهید||دانلود کنید|
- Urban heat island (UHI) study in Metropolitan Area of Rio de Janeiro (MARJ).
- Urban climate analysis using 32 years of Landsat data from 1984 to 2015.
- UHI magnitude for two periods: 1984-1999 and 2000-2015.
- Land-surface temperature evolution assessed using parametric and non-parametric tests.
The aim of this work is to study urban heat island (UHI) in Metropolitan Area of Rio de Janeiro (MARJ) based on the analysis of land-surface temperature (LST) and land-use patterns retrieved from Landsat-5/Thematic Mapper (TM), Landsat-7/Enhanced Thematic Mapper Plus (ETM+) and Landsat-8/Operational Land Imager (OLI) and Thermal Infrared Sensors (TIRS) data covering a 32-year period between 1984 and 2015. LST temporal evolution is assessed by comparing the average LST composites for 1984-1999 and 2000-2015 where the parametric Student t-test was conducted at 5% significance level to map the pixels where LST for the more recent period is statistically significantly greater than the previous one. The non-parametric Mann-Whitney-Wilcoxon rank sum test has also confirmed at the same 5% significance level that the more recent period (2000-2015) has higher LST values. UHI intensity between “urban” and “rural/urban low density” (“vegetation”) areas for 1984-1999 and 2000-2015 was established and confirmed by both parametric and non-parametric tests at 1% significance level as 3.3Â Â°C (5.1Â Â°C) and 4.4Â Â°C (7.1Â Â°C), respectively. LST has statistically significantly (p-valueÂ <Â 0.01) increased over time in two of three land cover classes (“urban” and “urban low density”), respectively by 1.9Â Â°C and 0.9Â Â°C, except in “vegetation” class. A spatial analysis was also performed to identify the urban pixels within MARJ where UHI is more intense by subtracting the LST of these pixels from the LST mean value of “vegetation” land-use class.
Journal: International Journal of Applied Earth Observation and Geoinformation - Volume 64, February 2018, Pages 104-116