scholarly journals Urban Design Factors Influencing Surface Urban Heat Island in the High-Density City of Guangzhou Based on the Local Climate Zone

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3459 ◽  
Author(s):  
Yurong Shi ◽  
Yirui Xiang ◽  
Yufeng Zhang
Keyword(s):  
Urban Design ◽  
Land Surface ◽  
High Density ◽  
Heat Island ◽  
Local Climate ◽  
Factors Influencing ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Design Factors ◽  
Local Climate Zone

Surface urban heat island (SUHI) depicts the deteriorating thermal environment in high-density cities and local climate zone (LCZ) classification provides a universal protocol for SUHI identification. In this study, taking the central urbanized area of Guangzhou in the humid subtropical region of China as the study area, the maps or images of LCZ, land surface temperature, SUHI, and urban design factors were achieved using Landsat satellite data, GIS database, and a series of retrieval and classification algorithms, and the urban design factors influencing SUHI were investigated based on 625 samples of LCZs. The results show that on the 18 September 2016 at the local time of 10:51 a.m., the land surface temperature (LST) varied greatly from 26 °C to 40 °C and the SUHI changed with a wide range of −6 °C to 8 °C in the LCZs of the study area. Seven and five urban design factors influencing the summer daytime SUHI were identified for the two dominant LCZs of LCZs 1–5 (LCZ 1 to LCZ 5) and the mixed LCZ (containing at least three types of LCZs), respectively, in which vegetation cover ratio, floor area ratio, ground emissivity, and complete surface area ratio showed negative correlations and building density showed positive correlations. The summer daytime SUHI prediction models were obtained by using the step-wise multiple linear regression, with the performance of R2 of 0.774, RMSE of 0.95 °C, and the d value of 0.91 for the model of LCZs 1–5, and the values of 0.819, 0.81 °C, and 0.94 for the model of the mixed LCZ, indicating that the models can effectively predict the changes of SUHI with LCZs. This study presents a methodology to efficiently achieve a large sample of SUHI and urban design factors of LCZs, and provides information beneficial to the urban designs and regenerations in high-density cities.

scholarly journals Urban Design Factors Influencing Surface Urban Heat Island in the Humid Subtropical Region Based on Local Climate Zone

2019 ◽  
Author(s):  
Yurong Shi ◽  
Yirui Xiang ◽  
Yufeng Zhang
Keyword(s):  
Urban Heat Island ◽  
Urban Design ◽  
Heat Island ◽  
Subtropical Region ◽  
Local Climate ◽  
Factors Influencing ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Design Factors ◽  
Local Climate Zone

Surface urban heat island (SUHI) depicts the deteriorating thermal environment in high-density cities and local climate zone (LCZ) classification provides a universal protocol for SUHI identification. In this study, taking the central urbanized area of Guangzhou in the humid subtropical region of China as the study area, the maps or images of LCZ, land surface temperature (LST), SUHI and urban design factors were achieved by using Landsat satellite data, GIS database and a series of retrieval and classification algorithms, and the urban design factors influencing SUHI were investigated based on 625 samples of LCZs. The results show that in the summer daytime under the clear sky condition, the LST varied greatly from 26 °C to 40 °C and the SUHI changed in a wide range of -6 °C to 8 °C in the LCZs of the study area. Seven and five urban design factors influencing the summer daytime SUHI were identified for the two dominant LCZ of LCZs 1-5 (LCZ 1 to LCZ 5) and the mixed LCZ (containing at least three types of LCZs), respectively. The summer daytime SUHI prediction models were obtained by using the step-wise multiple linear regression, with the performance of R2 of 0.697, RMSE of 1.21 °C, and the d value of 0.81 for the model of LCZs 1-5, and the values of 0.666, 1.66 °C, and 0.76 for the model of the mixed LCZ, indicating that the models can predict the changes of SUHI with LCZs to a large and satisfactory extent. This study presents a methodology to efficiently achieve a large sample of SUHI and urban design factors of LCZs in the largely urbanized cities, and provides information beneficial to the urban designs and regenerations in the humid subtropical region.

scholarly journals Investigations of Surface Urban Heat Island Effect Based on Local Climate Zone Method: A Case of Xi'an

2019 ◽  
Vol 136 ◽  
pp. 05011
Author(s):  
Kaikai Mu ◽  
Yan Liu ◽  
Moyan Zhang ◽  
Bing Han ◽  
Liu Yang
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Urban Form ◽  
Heat Island ◽  
Zone Method ◽  
Climate Zone ◽  
Local Climate ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Local Climate Zone

Urbanization seriously affects the urban climate and the quality of human settlement. Based on Landsat8 remote sensing and building vector data, local climate zone (LCZ) method is employed to study the influences of urban form on land surface temperature (LST) of Xi'an. The results confirmed that the LST of the built-up LCZ is higher than the land cover LCZ. In built-up LCZ, LST is increasing with the increasing of building density. In land cover LCZ, the LST of bare land is the highest. Surface urban heat island (SUHI) of 14 samples in LCZ also been calculated. Highest SUHI intensity is found in low-rise buildings with high density area. LST intensity of water body and forest are lower than others in land cover LCZ.

scholarly journals LINKING THE LOCAL CLIMATE ZONES AND LAND SURFACE TEMPERATURE TO INVESTIGATE THE SURFACE URBAN HEAT ISLAND, A CASE STUDY OF SAN ANTONIO, TEXAS, U.S.

2018 ◽  
Vol IV-3 ◽  
pp. 277-283 ◽  
Author(s):  
Chunhong Zhao
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
San Antonio ◽  
Heat Island ◽  
Climate Zones ◽  
Local Climate ◽  
Local Climate Zones ◽  
Urban Heat

The Local Climate Zones (LCZs) concept was initiated in 2012 to improve the documentation of Urban Heat Island (UHI) observations. Despite the indispensable role and initial aim of LCZs concept in metadata reporting for atmospheric UHI research, its role in surface UHI investigation also needs to be emphasized. This study incorporated LCZs concept to study surface UHI effect for San Antonio, Texas. LCZ map was developed by a GIS-based LCZs classification scheme with the aid of airborne Lidar dataset and other freely available GIS data. Then, the summer LST was calculated based Landsat imagery, which was used to analyse the relations between LST and LCZs and the statistical significance of the differences of LST among the typical LCZs, in order to test if LCZs are able to efficiently facilitate SUHI investigation. The linkage of LCZs and land surface temperature (LST) indicated that the LCZs mapping can be used to compare and investigate the SUHI. Most of the pairs of LCZs illustrated significant differences in average LSTs with considerable significance. The intra-urban temperature comparison among different urban classes contributes to investigate the influence of heterogeneous urban morphology on local climate formation.

scholarly journals Assessment of Changes in Land Use/Land Cover and Land Surface Temperatures and Their Impact on Surface Urban Heat Island Phenomena in the Kathmandu Valley (1988–2018)

2020 ◽  
Vol 9 (12) ◽  
pp. 726
Author(s):  
Md. Omar Sarif ◽  
Bhagawat Rimal ◽  
Nigel E. Stork
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Agricultural Land ◽  
Kathmandu Valley ◽  
Heat Island ◽  
City Center ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
The City ◽  
Normal Difference

More than half of the world’s populations now live in rapidly expanding urban and its surrounding areas. The consequences for Land Use/Land Cover (LULC) dynamics and Surface Urban Heat Island (SUHI) phenomena are poorly understood for many new cities. We explore this issue and their inter-relationship in the Kathmandu Valley, an area of roughly 694 km2, at decadal intervals using April (summer) Landsat images of 1988, 1998, 2008, and 2018. LULC assessment was made using the Support Vector Machine algorithm. In the Kathmandu Valley, most land is either natural vegetation or agricultural land but in the study period there was a rapid expansion of impervious surfaces in urban areas. Impervious surfaces (IL) grew by 113.44 km2 (16.34% of total area), natural vegetation (VL) by 6.07 km2 (0.87% of total area), resulting in the loss of 118.29 km2 area from agricultural land (17.03% of total area) during 1988–2018. At the same time, the average land surface temperature (LST) increased by nearly 5–7 °C in the city and nearly 3–5 °C at the city boundary. For different LULC classes, the highest mean LST increase during 1988–2018 was 7.11 °C for IL with the lowest being 3.18 °C for VL although there were some fluctuations during this time period. While open land only occupies a small proportion of the landscape, it usually had higher mean LST than all other LULC classes. There was a negative relationship both between LST and Normal Difference Vegetation Index (NDVI) and LST and Normal Difference Moisture Index (NDMI), respectively, and a positive relationship between LST and Normal Difference Built-up Index (NDBI). The result of an urban–rural gradient analysis showed there was sharp decrease of mean LST from the city center outwards to about 15 kms because the NDVI also sharply increased, especially in 2008 and 2018, which clearly shows a surface urban heat island effect. Further from the city center, around 20–25 kms, mean LST increased due to increased agriculture activity. The population of Kathmandu Valley was 2.88 million in 2016 and if the growth trend continues then it is predicted to reach 3.85 million by 2035. Consequently, to avoid the critical effects of increasing SUHI in Kathmandu it is essential to improve urban planning including the implementation of green city technologies.

scholarly journals Comparasion of NDBI and NDVI as Indicators of Surface Urban Heat Island Effect in Landsat 8 Imagery: A Case Study of Iasi

2017 ◽  
Vol 11 (2) ◽  
pp. 141-150 ◽  
Author(s):  
Paul Macarof ◽  
Florian Statescu
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Heat Island ◽  
Sensing Technology ◽  
Urban Heat ◽  
Surface Urban Heat Island

Abstract This study compares the normalized difference built-up index (NDBI) and normalized difference vegetation index (NDVI) as indicators of surface urban heat island effects in Landsat-8 OLI imagery by investigating the relationships between the land surface temperature (LST), NDBI and NDVI. The urban heat island (UHI) represents the phenomenon of higher atmospheric and surface temperatures occurring in urban area or metropolitan area than in the surrounding rural areas due to urbanization. With the development of remote sensing technology, it has become an important approach to urban heat island research. Landsat data were used to estimate the LST, NDBI and NDVI from four seasons for Iasi municipality area. This paper indicates than there is a strong linear relationship between LST and NDBI, whereas the relationship between LST and NDVI varies by season. This paper suggests, NDBI is an accurate indicator of surface UHI effects and can be used as a complementary metric to the traditionally applied NDVI.

scholarly journals Spatiotemporal Changes in the Urban Heat Island Intensity of Distinct Local Climate Zones: Case Study of Zhongshan District, Dalian, China

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Jun Han ◽  
Jiatong Liu ◽  
Liang Liu ◽  
Yuanzhi Ye
Keyword(s):  
Urban Heat Island ◽  
High Density ◽  
Urban Heat Island Intensity ◽  
Low Density ◽  
Heat Island ◽  
Climate Zones ◽  
Local Climate ◽  
Island Effect ◽  
Local Climate Zones ◽  
Urban Heat

Intensified due to rapid urbanization and global warming-induced high temperature extremes, the urban heat island effect has become a major environmental concern for urban residents. Scientific methods used to calculate the urban heat island intensity (UHII) and its alleviation have become urgent requirements for urban development. This study is carried out in Zhongshan District, Dalian City, which has a total area of 43.85 km2 and a 27.5 km-long coastline. The mono-window algorithm was used to retrieve the land surface temperatures (LSTs), employing Landsat remote sensing images, meteorological data, and building data from 2003, 2008, 2013, and 2019. In addition, the district was divided into local climate zones (LCZs) based on the estimated intensities and spatiotemporal variations of the heat island effect. The results show that, from 2003 to 2019, LCZs A and D shrank by 3.225 km2 and 0.395 km2, respectively, whereas LCZs B, C, and 1–6 expanded by 0.932 km2, 0.632 km2, and 2.056 km2, respectively. During this period, the maximum and minimum LSTs in Zhongshan increased by 1.365°C and 1.104°C, respectively. The LST and UHII levels of all LCZs peaked in 2019. The average LSTs of LCZs A–C increased by 1.610°C, 0.880°C, and 3.830°C, respectively, and those of LCZs 1–6 increased by 2°C–4°C. The UHIIs of LCZs A, C, and D increased by 0.730, 2.950, and 0.344, respectively, and those of LCZs 1–6 increased from 1.370–2.977 to 3.744–5.379. Overall, the regions with high LSTs are spatiotemporally correlated with high building densities. In this study, the land cover was then classified into four types (LCZs A–D) using visual interpretation and object-oriented classification, including forested land, low vegetation, bare ground, and water. Besides, the buildings were categorized as LCZs 1–6, which, respectively, represented low-density low-rises buildings, low-density high-rises buildings, low-density super high-rises buildings, high-density low-rises buildings, high-density high-rises buildings, and high-density super high-rises buildings.

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