The Impact of Urbanization on Urban Heat Island: Predictive Approach Using Google Earth Engine and CA-Markov Modelling (2005–2050) of Tianjin City, China

Abstract

Urbanization has adverse environmental effects, such as rising surface temperatures. This study analyzes the relationship between the urban heat island (UHI) intensity and Tianjin city’s land cover characteristics. The land use cover change (LUCC) effects on the green areas and the land surface temperature (LST) were also studied. The land cover characteristics were divided into five categories: a built-up area, an agricultural area, a bare area, a forest, and water. The LST was calculated using the thermal bands of spatial images taken from 2005 to 2020. The increase in the built-up area was mainly caused by the agricultural area decreasing by 11.90%. The average land surface temperature of the study area increased from 23.50 to 36.51 °C, and the region moved to a high temperature that the built-up area’s temperature increased by 1.5%. Still, the increase in vegetation cover was negative. From 2020 to 2050, the land surface temperature is expected to increase by 9.5 °C. The high-temperature areas moved into an aerial distribution, and the direction of urbanization determined their path. Urban heat island mitigation is best achieved through forests and water, and managers of urban areas should avoid developing bare land since they may suffer from degradation. The increase in the land surface temperature caused by the land cover change proves that the site is becoming more urbanized. The findings of this study provide valuable information on the various aspects of urbanization in Tianjin and other regions. In addition, future research should look into the public health issues associated with rapid urbanization.

Diễn biến đô thị hóa và nhiệt độ bề mặt ở thành phố Long Xuyên

“…Các khu vực có nhiệt độ cao chuyển sang phân bố trên không. Nghiên cứu [23] cho thấy rằng độ che phủ của cây và nhiệt độ có mối tương quan đáng kể, tức là mức độ che phủ cây càng cao, hiệu ứng đảo nhiệt đô thị càng thấp và ngược lại. Nghiên cứu cũng chỉ ra rằng mô hình tương quan giữa nhiệt độ và NDVI là động, có nghĩa là sự thay đổi của NDVI có thể gây ra những thay đổi lớn đối với nhiệt độ.…”

Modeling the Impact and Risk Assessment of Urbanization on Urban Heat Island and Thermal Comfort Level of Beijing City, China (2005–2020)

“…For the estimation of LST and LUC, a set of remote sensing data with a spatial resolution of 30 m was acquired from Landsat 4-5 Thematic Mapper (TM) and Operation Land Imager (OLI, Landsat 8), covering different periods between 2005 and 2020 (Table 1) [32]. The primary goal was to utilize Google Earth Engine (GEE) to identify cloud-free images captured during the same season as each sample year.…”

“…To demonstrate the effectiveness of our algorithm, we divided the total number of pixels by the entries in the primary segment. We then applied Equations ( 1)-( 3) to determine the kappa coefficient [32,40,41].…”

Analysis of Land Use Land Cover and Land Surface Temperature in Karst Area: A Case Study Wonogiri Regency

“…Remote sensing methods and mapping heat energy released by the atmosphere from the earth are methods for measuring LST using satellite image data [8] . A supporting tool to accurately calculate LST is Google Earth Engine [19] . An analysis of LST changes over time and the identification of different temperature patterns in certain areas can be done using Google Earth Engine [20] .…”