scholarly journals Simulating the Response of the Surface Urban Heat Environment to Land Use and Land Cover Changes: A Case Study of Wuhan, China

2021 ◽  
Vol 13 (22) ◽  
pp. 4495
Author(s):  
Meiling Gao ◽  
Zhenhong Li ◽  
Zhenyu Tan ◽  
Qi Liu ◽  
Huanfeng Shen

With the rapid process of urbanization, the urban heat island (UHI), the phenomenon where urban regions become hotter than their surroundings, is increasingly aggravated. The UHI is affected by multiple factors overall. However, it is difficult to dissociate the effect of one aspect by widely used approaches such as the remote-sensing-based method. To qualify the response of surface UHI to the land use and land cover (LULC) changes, this study took the numerical land model named u-HRLDAS (urbanized high-resolution land data assimilation system) as the modeling tool to investigate the effect of LULC changes on the UHI from 1980 to 2013 in Wuhan city, China. Firstly, the simulation accuracy of the model was improved, and the summer urban heat environment was simulated for the summer of 2013. Secondly, taking the simulation in 2013 as the control case (CNTL), the LULC in 1980, 1990, and 2000 were replaced by the LULC while the other conditions kept the same as the CNTL to explore the effect of LULC on UHI. The results indicate that the proper configuration of the modeling setup and accurate surface input data are considered important for the simulated results of the u-HRLDAS. The response intensity of UHI to LULC changes after 2000 was stronger than that of before 2000. From the spatial perspective, the part that had the strongest response intensity of land surface temperature to LULC changes was the region between the third ring road and the inner ring road of Wuhan. This study can provide a reference for cognizing the urban heat environment and guide policy making for urban development.

2021 ◽  
Vol 10 (5) ◽  
pp. 272
Author(s):  
Auwalu Faisal Koko ◽  
Wu Yue ◽  
Ghali Abdullahi Abubakar ◽  
Akram Ahmed Noman Alabsi ◽  
Roknisadeh Hamed

Rapid urbanization in cities and urban centers has recently contributed to notable land use/land cover (LULC) changes, affecting both the climate and environment. Therefore, this study seeks to analyze changes in LULC and its spatiotemporal influence on the surface urban heat islands (UHI) in Abuja metropolis, Nigeria. To achieve this, we employed Multi-temporal Landsat data to monitor the study area’s LULC pattern and land surface temperature (LST) over the last 29 years. The study then analyzed the relationship between LULC, LST, and other vital spectral indices comprising NDVI and NDBI using correlation analysis. The results revealed a significant urban expansion with the transformation of 358.3 sq. km of natural surface into built-up areas. It further showed a considerable increase in the mean LST of Abuja metropolis from 30.65 °C in 1990 to 32.69 °C in 2019, with a notable increase of 2.53 °C between 2009 and 2019. The results also indicated an inverse relationship between LST and NDVI and a positive connection between LST and NDBI. This implies that urban expansion and vegetation decrease influences the development of surface UHI through increased LST. Therefore, the study’s findings will significantly help urban-planners and decision-makers implement sustainable land-use strategies and management for the city.


2021 ◽  
Vol 879 (1) ◽  
pp. 012010
Author(s):  
A S Liong ◽  
N Nasrullah ◽  
B Sulistyantara

Abstract Makassar City, the capital of South Sulawesi Province, is the largest metropolitan city in the eastern part of Indonesia, with a population development rate of 1.19% in 2019. An increase in population impacts city development and results in land use and land cover changes. Changes in land use and land cover pattern bring impact to Land Surface Temperature (LST). This study examines land cover’s influence on land surface temperature in Makassar City using multi-temporal satellite data. Land cover and LST data were extracted using Landsat 7 and Landsat 8 over the period of 1999, 2009, and 2019. The result shows that the highest increase in land cover changed was a built-up area of 13.1%, and vegetation decreased by 8.6%. The change in average LST value in the last 20 years was 0.39°C with the highest LST distribution areas was in 30-32°C and 32-34°C classes. The result of LST analysis in 2019 shows that the Urban Heat Island phenomenon has occurred in Makassar in the downtown area and several areas with the densely built-up area. With an overview of the UHI phenomenon in Makassar, the government is expected to raise public awareness of this phenomenon so that preventive actions can be taken, so the effects of UHI do not spread more widely.


2021 ◽  
Vol 283 ◽  
pp. 01038
Author(s):  
Jing Sun ◽  
Jing He

The rapid urbanization process has recently led to significant land use and land cover (LULC) changes, thereby affecting the climate and the environment. The purpose of this study is to analyze the LULC changes in Hefei City, Anhui Province, and their relationship with land surface temperature (LST). To achieve this goal, multitemporal Landsat data were used to monitor the LULC and LST between 2005 and 2015. The study also used correlation analysis to analyze the relationship between LST, LULC, and other spectral indices (NDVI, NDBI, and NDWI). The results show that the built-up land has expanded significantly, transforming from 488.26 km2 in 2005 to 575.64 km2 in 2015. It further shows that the mean LST in Hefei city has increased from 284.0 K in 2005 to 285.86 K in 2015. The results also indicate that there is a positive correlation between LST and NDVI and NDBI, while there is a negative correlation between LST and NDWI. This means that urban expansion and reduced water bodies will lead to an increase in LST.


Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1037
Author(s):  
Mohamed Ali Mohamed

Monitoring the impact of changes in land use/land cover (LULC) and land surface temperature (LST) is of great importance in environmental and urban studies. In this context, this study aimed to analyze the dynamics of LULC and its impact on the spatiotemporal variation of the LST in the two largest urban cities in Syria, Damascus, and Aleppo. To achieve this, LULC changes, normalized difference vegetation index (NDVI), and LST were calculated from multi-temporal Landsat data for the period 2010 to 2018. The study revealed significant changes in LULC, which were represented by a decrease in agricultural land and green areas and an increase in bare areas in both cities. In addition, built-up areas decreased in Aleppo and increased in Damascus during the study period. The temporal and spatial variation of the LST and its distribution pattern was closely related to the effect of changes in LULC as well as to land use conditions in each city. This effect was greater in Aleppo than in Damascus, where Aleppo recorded a higher increase in the mean LST, by about 2 °C, than in Damascus, where it was associated with greater degradation and loss of vegetation cover. In general, there was an increasing trend in the minimum and maximum LST as well as an increasing trend in the mean LST in both cities. The negative linear relationship between LST and NDVI confirms that vegetation cover can help reduce LST in both cities. This study can draw the attention of relevant departments to pay more attention to mitigating the negative impact of LULC changes in order to limit the increase in LST.


2017 ◽  
Vol 49 (1) ◽  
pp. 1 ◽  
Author(s):  
Adi Wibowo ◽  
Khairulmaini Osman Salleh ◽  
Adi Wibowo

As education area, campus or university is full with various activities which have an impact on the existence of land-use or land-cover. The variation of activities dynamically change the shape of land-use or land-cover within the campus area, thus also create variations in Land Surface Temperature (LST). The LST are impacting the coziness of human activity especially when reaches more than 30 oC. This study used the term Urban Heat Signature (UHS) to explain LST in different land-use or land-cover types. The objective of this study is to examine UHS as an Urban Heat Hazard (UHH) based on Universal Temperature Climate Index (UTCI) and Effective Temperature Index (ETI) in University of Indonesia. Thermal bands of Landsat 8 images (the acquisition year 2013-2015) were used to create LST model. A ground data known as Air Surface Temperature (AST) were used to validate the model. The result showed an increased level of maximum temperature during September-October since 2013 until 2014. The maximum temperature was reduced in October 2014, however it increased again in August 2015. The UTCI showed “moderate” and “strong heat stress”, while EFI showed “uncomfortable” and “very uncomfortable” categories during that period. This research concluded that build up area in UI Campus highest temperature on UI campus based on UHS. Range UHS in Campus UI on 2013 (21.8-31.1oC), 2014 (25.0-36.2oC) and 2015 (24.9-38.2oC). This maximum UHS on September (2014 and 2015) put on levelling UTCI included range temperature 32-35oC, with an explanation of sensation temperature is warm and sensation of comfort is Uncomfortable, Psychology with  Increasing Stress Case by Sweating and Blood Flow and Health category is Cardiovascular Embarrassment. This UHS occurs in September will give impact on psychology and health, that’s become the UHH of the living on education area.


Climate ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 71
Author(s):  
Priyanka Kumari ◽  
Sukriti Kapur ◽  
Vishal Garg ◽  
Krishan Kumar

Rapid urbanization and associated land-use changes in cities cause an increase in the demand for electricity by altering the local climate. The present study aims to examine the variations in total energy and cooling energy demand in a calibrated building energy model, caused by urban heat island formation over Delhi. The study used Sentinel-2A multispectral imagery for land use and land cover (LULC) of mapping of Delhi, and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery for land surface temperature (LST) mapping during March 2018. It was observed that regions with dense built-up areas (i.e., with built-up area greater than 90%) had a higher annual land surface temperature (LST), i.e., 293.5 K and urban heat island intensity (UHII) ranging from 0.9 K–5.9 K. In contrast, lower annual values of LST (290K) and UHII (0.0–0.4 K) were observed in regions with high vegetation cover (53%). Statistical analysis reveals that a negative correlation exists between vegetation and nighttime LST, which is further confirmed by linear regression analysis. Energy simulations were performed on a calibrated building model placed at three different sites, identified on the basis of land use and land cover percentage and annual LST. Simulation results showed that the site located in the central part of Delhi displayed higher annual energy consumption (255.21 MWh/y) compared to the site located in the rural periphery (235.69 MWh/y). For all the three sites, the maximum electricity consumption was observed in the summer season, while the minimum was seen in the winter season. The study indicates that UHI formation leads to increased energy consumption in buildings, and thus UHI mitigation measures hold great potential for energy saving in a large city like Delhi.


2016 ◽  
Vol 9 (7) ◽  
Author(s):  
Fei Zhang ◽  
Tashpolat Tiyip ◽  
Hsiangte Kung ◽  
Verner Carl Johnson ◽  
Matthew Maimaitiyiming ◽  
...  

Author(s):  
Y. A. Aina ◽  
E. M. Adam ◽  
F. Ahmed

Urban heat island (UHI) effect is considered to be one of the key indicators of the impacts of urbanization and the climate changes on the environment. Thus, the growing interest in studying the impacts of urbanization on changes in land surface temperature (LST). The literature on LST indicates the need for more studies on the relationship between changes in LST and land use types, especially in the arid environment. This paper examines the spatial and temporal changes in land surface temperature influenced by land use/land cover types in Riyadh, Saudi Arabia. Multi-temporal Landsat images of the study area, 1985, 1995, 2002 and 2015, were processed to derive land surface temperatures. UHI index was computed for the different land use/land cover types (high-density residential, medium-density residential, low-density residential, industrial, vegetation, and desert) in the study area. The results indicate a trend of rising temperatures in all the land use types in the study area. This is probably due to climate change. The industrial area has the highest temperatures among the land use types. The lowest temperatures are found in the vegetation area as expected. There is a need to implement mitigating measures to reduce the effects of rising temperatures in the study area.


Author(s):  
Simil Amir Siddiqui

Urban heat islands (UHI) are areas with elevated temperatures occurring in cities compared to surrounding rural areas. This study realizes the lack of research regarding the trends of UHIs in desert countries and focuses on Doha. The research includes twelve months of two-time periods; 2000-2019. ArcGIS software was used to compute the land surface temperature (LST) of the city using Landsat images. Land use/land cover (LULC) maps were computed to show how the city has evolved in 19 years. 30 field samples were used to verify the accuracy of the LULC. Results showed UHI in Doha did not display similar pattern to that of cities in subtropical and temperate regions. Higher temperatures were prevalent in out-skirts comprising of barren and built-up areas with high population and no vegetation. Comparatively, the main downtown with artificially planted vegetation and shade from skyscrapers created cooler microclimates. The overall LST of greater Doha has increased by 0.7°C from 2000 to 2019. Furthermore %LULC of built up, vegetation, barren land, marsh land and water body were 29%, 4.5%, 58.6%, 2.8% and 5% in 2000 and 56.5 %, 8.2%, 33.2 %, 0% and 2.1% in 2019 respectively. Overall, there was an increase in built-up and vegetation decrease in water and barren areas and complete loss of marshland. Highest temperatures were recorded for marshland area in year 2000 and barren and built in year 2019. Transect profiles showed positive correlation between NDBI and LST and a negative correlation between NDVI and LST.


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