Land Surface Temperature Intensity Research Articles

How do disparate urbanization and climate change imprint on urban thermal variations? A comparison between two dynamic cities in Southeast Asia

This study assessed the combined influences of climate change and urbanization on land surface temperature (LST) and surface urban heat island (SUHI) in the Bangkok metropolitan region (BKK) and Ho Chi Minh City metropolitan area (HCM) during 1990–2020. We found climate change evidence from trends and variations of temperature extremes in both cities throughout the past three decades, especially for the significant upward trends of nighttime temperature in HCM (0.23 – 0.3 °C/decade). These cities have been undergoing rapid urbanization, in which HCM has a higher urbanization rate with an annual growth rate of 8.03%/year against BKK (4.26%/year). Landscape metrics have rapidly shifted towards urban aggregation and green space fragmentation along with urbanization. A peer comparison shows that BKK holds a greater urban size and LST intensity, while HCM leads in urban growth and SUHI magnitude. These changes jointly contribute to climbing SUHI intensity, especially the dramatic influence of surface changes. Yet, temperature extremes also play an indispensable role in regulating SUHI magnitude, in which the impact in HCM is considerable compared to the effect in BKK. The research findings provide crucial information for both cities – where incorporation of climate change resilience strategies and SUHI mitigation into the master plans for livable cities are recommended.

Monitoring land surface temperature in Bahir Dar city and its surrounding using Landsat images

Land surface temperature (LST) is the burning issue in the world since it affects climate and environment at local, regional and global level. Mainly it resulted from urbanization and its associated extreme Land-use and Land-cover (LULC) changes. Therefore, monitoring of LULC alteration is a significant component in examining of LST variation and applying sustainable mitigation measures. The research has the objective to analyze the spatial-temporal patterns of LST and its variation with LULC composition in Bahir Dar city and its surrounding from 1987 to 2017 with fifteen-year intervals using Landsat images. Image preprocessing was done to retrieve NDVI, NDBI, LST and LULC, and urban-rural gradient analysis and LST Intensity (LSTI) were computed. As the result shows that urban areas of Bahir Dar city rapidly expanded since 1987. The mean LST values increased to 34.5 °C in 1987 to 37.57 °C in 2002 and decreased to 34.57 °C in 2017. Paved surface and agricultural land exhibited higher LST values whereas waterbody and vegetation experienced lower LST. The result also shows that LST has a positive relationship with NDBI (1987: R2 = 0.51; 2002: R2 = 0.48; and 2017: R2 = 0.4) and negative relationship with NDVI (1987: R2 = 0.24; 2002: R2 = 0.25; and 2017: R2 = 0.33). The LST increased towards sub-urban areas and LSTI was higher in the distance between 4 and 10 km. The results of this study are significant for urban planners to implement sustainable LST mitigation strategies and create a conducive living environment in Bahir Dar city.

The Impacts of Landscape Changes on Annual Mean Land Surface Temperature in the Tropical Mountain City of Sri Lanka: A Case Study of Nuwara Eliya (1996–2017)

Although urbanization has contributed to improving living conditions, it has had negative impacts on the natural environment in urbanized areas. Urbanization has changed the urban landscape and resulted in increasing land surface temperature (LST). Thus, studies related to LST in various urban environments have become popular. However, there are few LST studies focusing on mountain landscapes (i.e., hill stations). Therefore, this study investigated the changes in the landscape and their impacts on LST intensity (LSTI) in the tropical mountain city of Nuwara Eliya, Sri Lanka. The study utilized annual median temperatures extracted from Landsat data collected from 1996 to 2017 based on the Google Earth Engine (GEE) interface. The fractions of built-up (BL), forested (FL) and agricultural (AL) land, were calculated using land use and cover maps based on urban–rural zone (URZ) analysis. The urban–rural margin was demarcated based on the fractions of BL (<10%), and LSTI that were measured using the mean LST difference in the urban–rural zone. Besides, the mixture of land-use types was calculated using the AL/FL and BL/FL fraction ratios, and grid-based density analysis. The results revealed that the BL in all URZs rapidly developed, while AL decreased during the period 1996 to 2017. There was a minimal change in the forest area of the Nuwara Eliya owing to the government’s forest preservation policies. The mean temperature of the study area increased by 2.1 °C from 1996 to 2017. The magnitude of mean LST between urban–rural zones also increased from 1.0 °C (1996) to 3.5 °C (2017). The results also showed that mean LST was positively correlated with the increase and decrease of the BL/FL and AL/FL fraction ratios, respectively. The grid-based analysis showed an increasing, positive relationship between mean LST and density of BL. This indicated that BL density had been a crucial element in increasing LST in the study area. The results of this study will be a useful indicator to introduce improved landscape and urban planning in the future to minimize the negative impact of LST on urban sustainability.

Mapping Mountain Permafrost Landscapes in Siberia Using Landsat Thermal Imagery

Intensive development of South Yakutia, a mountainous area in the Russian sporadic permafrost zone, must be founded on knowledge about regional permafrost conditions. New permafrost maps for mountainous areas in South Yakutia (the Elkon Mountains and the Olekma-Chara Upland) are presented that provide a more detailed and updated description of permafrost distribution in the area than those that were hitherto available. These maps are based on the previously-developed and tested method of detecting permafrost and unfrozen ground using Landsat-5/TM satellite data with relatively high resolution. The method represents a scheme for permafrost identification based on a set of landscape indicators: terrain elevation, slope angle and exposition, vegetation, snow cover, and land surface temperature (LST). A correlation analysis of satellite data to full-scale field data has been carried out for the two areas under consideration. Indicator properties of LST obtained by Landsat-5/TM Band 6 Infrared have been characterized in detail for detection and regional mapping of permafrost. The effect of landscape factors (landscape cryo-indicators) on ground temperature and condition, frozen or unfrozen reflected in LST intensity, is demonstrated.