scholarly journals Modeling Spatio-Temporal Land Transformation and Its Associated Impacts on land Surface Temperature (LST)

2020 ◽  
Vol 12 (18) ◽  
pp. 2987 ◽  
Author(s):  
Faisal Mumtaz ◽  
Yu Tao ◽  
Gerrit de Leeuw ◽  
Limin Zhao ◽  
Cheng Fan ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Thermal Environment ◽  
Urban Centers ◽  
Barren Land ◽  
City Regions ◽  
Spatio Temporal

Land use land cover (LULC) of city regions is strongly affected by urbanization and affects the thermal environment of urban centers by influencing the surface temperature of core city areas and their surroundings. These issues are addressed in the current study, which focuses on two provincial capitals in Pakistan, i.e., Lahore and Peshawar. Using Landsat data, LULC is determined with the aim to (a) examine the spatio-temporal changes in LULC over a period of 20 years from 1998 to 2018 using a CA-Markov model, (b) predict the future scenarios of LULC changes for the years 2023 and 2028, and (c) study the evolution of different LULC categories and investigate its impacts on land surface temperature (LST). The results for Peshawar city indicate the significant expansion in vegetation and built-up area replacing barren land. The vegetation cover and urban area of Peshawar have increased by 25.6%, and 16.3% respectively. In contrast, Lahore city urban land has expanded by 11.2% while vegetation cover decreased by (22.6%). These transitions between LULC classes also affect the LST in the study areas. Transformation of vegetation cover and water surface into built-up areas or barren land results in the increase in the LST. In contrast, the transformation of urban areas and barren land into vegetation cover or water results in the decrease in LST. The different LULC evolutions in Lahore and Peshawar clearly indicate their effects on the thermal environment, with an increasing LST trend in Lahore and a decrease in Peshawar. This study provides a baseline reference to urban planners and policymakers for informed decisions.

scholarly journals UNDERSTANDING LINK BETWEEN LAND SURFACE TEMPERATURE AND LANDSCAPE HETEROGENEITY: A SPATIO-TEMPORAL AND INTER-SEASONAL VARIABILITY STUDY ON KABUL CITY, AFGHANISTAN

2019 ◽  
Vol IV-5/W2 ◽  
pp. 57-65 ◽  
Author(s):  
S. Mahmoodi ◽  
K. Dutta ◽  
D. Basu ◽  
S. Agrawal
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Landscape Heterogeneity ◽  
Landsat Images ◽  
Barren Land ◽  
Spatio Temporal ◽  
The Government

Abstract. Satellite imageries were used to study temporal and seasonal patterns of Land Surface Temperature (LST) in Kabul, followed by establishing an interrelation with Land Use Land Cover (LULC) changes occurring in the city. LULC and LST changes were examined based on Landsat Thematic Mapper (TM) and Landsat Operational Land Imager (OLI), Thermal Infrared Sensors (TIRS). LST Maps were derived from the thermal band of Landsat images for decadal study (Winter/Summer; 2008–09 and 2018–19). Visible bands were utilized for supervised LULC classification in the same decade. Results showed that Kabul City expanded rapidly over the study period from 232.28 km2 to 371.08 km2 in one decade (2009–2019). Other land cover classes i.e. barren land, mountains and vegetation, were observed to be converted to urban class i.e. residential, commercial, and industrial. High LST zones of Kabul city consisted of mountains, barren land and urban areas. Notable difference of 3 °C was observed between urban and vegetated lands. This study successfully identified the areas (i.e. district 12, district 13 and district 17) currently affected by rapid urban sprawl. The results also highlighted the changes in LST pattern caused by urbanization. The study will help the government, private sector investors and land planners to develop sustainable land management policies.

scholarly journals Quantifying the Effects of Urban Form on Land Surface Temperature in Subtropical High-Density Urban Areas Using Machine Learning

2019 ◽  
Vol 11 (8) ◽  
pp. 959 ◽  
Author(s):  
Yanwei Sun ◽  
Chao Gao ◽  
Jialin Li ◽  
Run Wang ◽  
Jian Liu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Form ◽  
Urban Areas ◽  
Thermal Environment ◽  
High Density ◽  
Cooling Effects ◽  
Urban Thermal Environment ◽  
The Impact

It is widely acknowledged that urban form significantly affects urban thermal environment, which is a key element to adapt and mitigate extreme high temperature weather in high-density urban areas. However, few studies have discussed the impact of physical urban form features on the land surface temperature (LST) from a perspective of comprehensive urban spatial structures. This study used the ordinary least-squares regression (OLS) and random forest regression (RF) to distinguish the relative contributions of urban form metrics on LST at three observation scales. Results of this study indicate that more than 90% of the LST variations were explained by selected urban form metrics using RF. Effects of the magnitude and direction of urban form metrics on LST varied with the changes of seasons and observation scales. Overall, building morphology and urban ecological infrastructure had dominant effects on LST variations in high-density urban centers. Urban green space and water bodies demonstrated stronger cooling effects, especially in summer. Building density (BD) exhibited significant positive effects on LST, whereas the floor area ratio (FAR) showed a negative influence on LST. The results can be applied to investigate and implement urban thermal environment mitigation planning for city managers and planners.

scholarly journals Retrieval of Land Surface Temperature of Lahore Through Landsat-8 TIRS Data

2019 ◽  
Vol 10 (1) ◽  
pp. 70-77
Author(s):  
Muhammad Nasar -u-Minallah
Keyword(s):  
Radiative Transfer ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Global Climate ◽  
Spectral Radiance ◽  
Landsat 8 ◽  
Barren Land ◽  
Data Continuity

Land surface temperature (LST) is an important parameter in global climate change and urban thermalenvironmental studies. The significance of land surface temperature is being acknowledged gradually and interest isincreasing in developing methodologies for the retrieval of LST from Satellite Remote Sensing (SRS) data. ThermalInfrared Sensor (TIRS) of Landsat-8 is the newest TIR sensor for the Landsat Data Continuity Mission (LDCM),offering two adjacent thermal infrared bands (10, 11), having significant beneficiary for the land surface temperatureinversion. The spectral radiance can be estimated through TIR bands 10 and 11 of Landsat-8 OLI_TIRS satellite image.In the present study, the radiative transfer equation-based method has been employed in estimating LST of Lahore andthe analysis demonstrated that estimated LST has the highest accuracy from the radiative transfer method through band10. Land Surface Emissivity (LSE) was derived with the aid of the NDVI’s threshold technique. The present studyresults show that as the built-up area increases and vegetation cover decreases in urban surface, they are linked toincrease in urban land surface temperature and conversely larger vegetation cover associated with lower urbantemperature. The output exposed that LST was high in built-up and barren land, whereas it was low in the area wherethere were more vegetation cover and water.

scholarly journals Retrieval of Land Surface Temperature of Lahore Through Landsat-8 TIRS Data

2019 ◽  
Vol 10 (1) ◽  
pp. 70-77
Author(s):  
Muhammad Nasar -u-Minallah
Keyword(s):  
Radiative Transfer ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Global Climate ◽  
Spectral Radiance ◽  
Landsat 8 ◽  
Barren Land ◽  
Data Continuity

Land surface temperature (LST) is an important parameter in global climate change and urban thermalenvironmental studies. The significance of land surface temperature is being acknowledged gradually and interest isincreasing in developing methodologies for the retrieval of LST from Satellite Remote Sensing (SRS) data. ThermalInfrared Sensor (TIRS) of Landsat-8 is the newest TIR sensor for the Landsat Data Continuity Mission (LDCM),offering two adjacent thermal infrared bands (10, 11), having significant beneficiary for the land surface temperatureinversion. The spectral radiance can be estimated through TIR bands 10 and 11 of Landsat-8 OLI_TIRS satellite image.In the present study, the radiative transfer equation-based method has been employed in estimating LST of Lahore andthe analysis demonstrated that estimated LST has the highest accuracy from the radiative transfer method through band10. Land Surface Emissivity (LSE) was derived with the aid of the NDVI’s threshold technique. The present studyresults show that as the built-up area increases and vegetation cover decreases in urban surface, they are linked toincrease in urban land surface temperature and conversely larger vegetation cover associated with lower urbantemperature. The output exposed that LST was high in built-up and barren land, whereas it was low in the area wherethere were more vegetation cover and water.

Land Surface High Temperature Monitoring in Belt and Road Communities

2020 ◽  
Author(s):  
Ronghan Xu
Keyword(s):  
High Temperature ◽  
Surface Temperature ◽  
Real Time ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Thermal Environment ◽  
Health And Social Care ◽  
Satellite Sensors ◽  
Belt And Road

<p>Heatwaves are extended periods of extremely hot weather and high temperature that have a major impact on human health, socioeconomics and natural systems. As predicted by climate models, ongoing global warming will potentially increase the incidence, intensity and duration of summertime heatwave events. Nevertheless, heat-related health impacts are largely preventable if populations, health and social care systems and public infrastructure are prepared. Therefore, this is plausible if heatwave events are studies for which heatwave real-time monitoring and assessment are central components. It is well recognized that land surface temperature retrieved by satellite sensors is an important variable associated with heatwaves and surface warming research. Land surface temperature retrieved by satellite sensors can be observed spatially and temporally, adequate for applications needing real-time and continuous measurements in quick response. In this study, Chinese Fengyun satellite data were used to monitor the land surface thermal environment during the heatwave event in Belt and Road communities. Split-window algorithm were applied to retrieve land surface temperature from thermal sensor. Spatial temporal distributions of Land surface high temperature are monitored in West Europe, India, and Australia as examples during their high temperature weather. The result shows that monitoring the real-time heatwave hazards in quick responds help provided information to the decision makers and get insight into the thermal environment characteristics over urban areas.</p>

Remote Sensing-based Spatiotemporal Analysis of Near-Surface Temperatures for Cities Located in Different Climatic Zones

2021 ◽  
Author(s):  
Sriram Jallu ◽  
Poorna Chander Reddy Bommineni ◽  
Roshan Srivastav
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Rural Areas ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Quantitative Relation ◽  
Rapid Urbanization ◽  
Near Surface ◽  
Spatio Temporal

<p>Urbanization has a major impact on the spatio-temporal variation of near-surface temperature for world cities. Recent studies indicate that the understanding of changes in temperature with urbanization has provided greater insights into the effects of Urban Heat Islands (UHI) on various issues such as excessive energy consumption, health hazard and climate change. In this study, spatio-temporal variations of near-surface temperature for India’s three major cities with different climatic conditions are evaluated. In addition, an attempt is made to establish a quantitative relation between land surface temperature (LST) and various geographical indices indicating vegetation cover (NDVI, Normalized Difference Vegetation Index), water surfaces (NDWI, Normalized Difference Water Index), and impervious land (NDBI, Normalized Difference Built-up Index). The dataset is selected for years 2014 to 2020 for three major cities: (i) Chennai (coastal); (ii) Hyderabad (inland); and (ii) Mumbai (coastal). The study uses Landsat – 8 OLI / TIRS images to derive land use/cover types, land surface temperature datasets, NDVI, NDBI, and NDWI. The preliminary evaluations indicate that the maximum contribution towards the UHI is impervious land, and the effect is more prominent in the areas of rapid urbanization. Urban areas relatively have a high temperature compared to the surrounding rural areas, and the effect is more prominent during night times. The analysis derived from the study will be useful for decision-makers or stakeholders to take necessary actions for reducing the effects of UHI and planning for urban sprawl.</p>

scholarly journals Exploring the Variation Trend of Urban Expansion, Land Surface Temperature, and Ecological Quality and Their Interrelationships in Guangzhou, China, from 1987 to 2019

2021 ◽  
Vol 13 (5) ◽  
pp. 1019
Author(s):  
Jianhui Xu ◽  
Yi Zhao ◽  
Caige Sun ◽  
Hanbin Liang ◽  
Ji Yang ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Expansion ◽  
Impervious Surface ◽  
Ecological Quality ◽  
Urban Center ◽  
Urban Centers ◽  
Rapid Urbanization

This study explored the model of urban impervious surface (IS) density, land surface temperature (LST), and comprehensive ecological evaluation index (CEEI) from urban centers to suburbs. The interrelationships between these parameters in Guangzhou from 1987 to 2019 were analyzed using time-series Landsat-5 TM (Thematic Mapper), Landsat-8 OLI (Operational Land Imager), and TIRS (Thermal Infrared Sensor) images. The urban IS densities were calculated in concentric rings using time-series IS fractions, which were used to construct an inverse S-shaped urban IS density function to depict changes in urban form and the spatio-temporal dynamics of urban expansion from the urban center to the suburbs. The results indicated that Guangzhou experienced expansive urban growth, with the patterns of urban spatial structure changing from a single-center to a multi-center structure over the past 32 years. Next, the normalized LST and CEEI in each concentric ring were calculated, and their variation trends from the urban center to the suburbs were modeled using linear and nonlinear functions, respectively. The results showed that the normalized LST had a gradual decreasing trend from the urban center to the suburbs, while the CEEI showed a significant increasing trend. During the 32-year rapid urban development, the normalized LST difference between the urban center and suburbs increased gradually with time, and the CEEI significantly decreased. This indicated that rapid urbanization significantly expanded the impervious surface areas in Guangzhou, leading to an increase in the LST difference between urban centers and suburbs and a deterioration in ecological quality. Finally, the potential interrelationships among urban IS density, normalized LST, and CEEI were also explored using different models. This study revealed that rapid urbanization has produced geographical convergence between several ISs, which may increase the risk of the urban heat island effect and degradation of ecological quality.

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