scholarly journals The Urban Heat Island Analysis of Changsha-zhuzhou-xiangtan Urban Agglomeration Aased on Modis Data

2018 ◽  
Vol 53 ◽  
pp. 03045
Author(s):  
Jiao Yuan ◽  
Jingwen Li ◽  
Suxian Ye ◽  
Xiaoqiang Han ◽  
Yao Hu
Keyword(s):  
Urban Heat Island ◽  
Temperature Difference ◽  
Land Surface ◽  
Temporal Distribution ◽  
Maximum Temperature ◽  
Heat Island ◽  
Maximum Temperature Difference ◽  
High Temperature Area ◽  
Urban Heat ◽  
The Difference

Using a spatial resolution of MODIS land 1000m standard products, we can get the Land Surface Temperature.Researching for the Land Surface Temperature including spatial and temporal distribution characteristics influence factors.The results show that Spring,Summer and Autumn temperatures mainly concentrated in the central region,Winter temperature mainly concentrated in the South region.From 2001 to 2015,the maximum temperature difference is summer daytime and the difference is 17.58°C,the minimum temperature difference is autumn daytime and the difference is 11.3°C.According to the thermal field intensity distribution,compared 2005 with 2015,Urban Heat Island intensity gradually increased in 2015,the high temperature area increased and distributed more concentrated,and diffusion weakened from the city to the surrounding,the urban heat field is higher than the thermal field.That index by calculating the thermal landscape,account for a dominant position in the middle of heat distribution,and all types index in 2015 are higher than in 2005.

scholarly journals Quantification of Urban Heat Island-Induced Contribution to Advance in Spring Phenology: A Case Study in Hangzhou, China

2021 ◽  
Vol 13 (18) ◽  
pp. 3684
Author(s):  
Yingying Ji ◽  
Jiaxin Jin ◽  
Wenfeng Zhan ◽  
Fengsheng Guo ◽  
Tao Yan
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Heat Island ◽  
Spring Phenology ◽  
Urban Heat ◽  
The Difference

Plant phenology is one of the key regulators of ecosystem processes, which are sensitive to environmental change. The acceleration of urbanization in recent years has produced substantial impacts on vegetation phenology over urban areas, such as the local warming induced by the urban heat island effect. However, quantitative contributions of the difference of land surface temperature (LST) between urban and rural (ΔLST) and other factors to the difference of spring phenology (i.e., the start of growing season, SOS) between urban and rural (ΔSOS) were rarely reported. Therefore, the objective of this study is to explore impacts of urbanization on SOS and distinguish corresponding contributions. Using Hangzhou, a typical subtropical metropolis, as the study area, vegetation index-based phenology data (MCD12Q2 and MYD13Q1 EVI) and land surface temperature data (MYD11A2 LST) from 2006–2018 were adopted to analyze the urban–rural gradient in phenology characteristics through buffers. Furthermore, we exploratively quantified the contributions of the ΔLST to the ΔSOS based on a temperature contribution separation model. We found that there was a negative coupling between SOS and LST in over 90% of the vegetated areas in Hangzhou. At the sample-point scale, SOS was weakly, but significantly, negatively correlated with LST at the daytime (R2 = 0.2 and p < 0.01 in rural; R2 = 0.14 and p < 0.05 in urban) rather than that at nighttime. Besides, the ΔSOS dominated by the ΔLST contributed more than 70% of the total ΔSOS. We hope this study could help to deepen the understanding of responses of urban ecosystem to intensive human activities.

Characteristics of Land Surface Temperture (LST) within the Third Ring Road of Shenyang

2015 ◽  
Vol 737 ◽  
pp. 913-916
Author(s):  
Zi Qi Zhao ◽  
Li Guang Li ◽  
Hong Bo Wang ◽  
Xian Li Zhao ◽  
Peng Jiang
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Hot Spot ◽  
Source Area ◽  
Heat Island ◽  
Positive Correlation ◽  
Urban Climatology ◽  
The Third ◽  
Urban Heat ◽  
The Difference

Urban heat island (UHI) effect becomes hot spot in the field of urban climatology in the recent decades. Two sampling belts on the Landsat TM/ETM+ image across the center point of main urban area of shenyang were selected along the E-W and S-N directions in order to analyse the characteristics of UHI effect and discuss the relationships between LST and UHI source or sink. The results indicate that for the E-W direction sampling belt, the maximum and minimum LST values were 37.46 °Cand 33.44 °C in 2001 respectively, while those were 34.61 °C and 33.30 °C in 2010. For the S-N direction sampling belt, the corresponding values were 34.53 °C and 29.27 °C in 2001, 34.47 °C and 29.69 °C in 2010. LST fluctuated significantly in the E-W direction sampling belt in 2010 and the difference value was 4.01 °C, so was in the S-N direction sampling belt in 2010 and the difference value was 4.78 °C. LST of the grid was a positive correlation with LST of the UHI source area of grid in 2001 and 2010, so was with that of UHI sink area in 2001 and 2010. LST of grid was a positive correlation with UHI source area.

scholarly journals Cooling Effect of Different Land Cover Types: A Case Study in Xi’an and Xianyang, China

2021 ◽  
Vol 13 (3) ◽  
pp. 1099
Author(s):  
Yuhe Ma ◽  
Mudan Zhao ◽  
Jianbo Li ◽  
Jian Wang ◽  
Lifa Hu
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Cooling Effect ◽  
Heat Island ◽  
Land Cover Types ◽  
Island Effect ◽  
Urban Heat

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.

scholarly journals RELATIONSHIPS BETWEEN LAND USE/LAND COVER AND LAND SURFACE TEMPERATURE IN TABRIZ FROM 2000 TO 2017

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 1041-1044
Author(s):  
A. Tahooni ◽  
A. A. Kakroodi
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Impervious Surface ◽  
Bare Soil ◽  
Heat Island ◽  
Land Use Land Cover ◽  
Urban Heat

Abstract. Urban Heat Island (UHI) refers to the development of higher urban temperatures of an urban area compared to the temperatures of surrounding suburban and rural areas. Highly reflective urban materials to solar radiation present a significantly lower surface temperature and contribute to reducing the sensible heat released in the atmosphere and mitigating the urban heat island. Many studies of the UHI effect have been based on Land Surface Temperature (LST) measurements from remote sensors. The remotely sensed UHI has been termed the surface urban heat island (SUHI) effect. This study examines Tabriz city land use/land cover (LULC) and LST changes using Landsat satellite images between 2000 and 2017. Maximum likelihood classification and single channel methods were used for LULC classification and LST retrieval respectively. Results show that impervious surface has increased 13.79% and bare soil area has decreased 16.2%. The results also revealed bare soil class LST after a constant trend become increasing. It also revealed the impervious surface LST has a decreasing trend between 2000 and 2011 and has a little change. Using materials that have low absorption and high reflectance decrease the effect of heat island considerably.

scholarly journals Ecological impact evaluation of urban heat island in Dhaka city; a spatio-temporal approach

2021 ◽  
Author(s):  
Kazi Jihadur Rashid ◽  
Sumaia Islam ◽  
Mohammad Atiqur Rahman
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Land Surface ◽  
Ecological Impact ◽  
Urban Life ◽  
Heat Island ◽  
Dhaka City ◽  
Ecological Conditions ◽  
Urban Heat ◽  
The Impact

Abstract Urban heat island (UHI) is one of the major causes for deteriorating ecology of the rapidly expanding Dhaka city in the changing climatic conditions. Although researchers have identified, characterized and modeled UHI in the study area, the ecological evaluation of UHI effect has not yet been focused. This study uses land surface normalization techniques such as urban thermal field variance (UTFVI) to quantify the impact of UHI and also identifies vulnerable UHI areas compared to land cover types. Landsat imageries from 1990 to 2020 were used at decadal intervals. Results of the study primarily show that intensified UHI areas have increased spatially from 33.1–40.9% in response to urban growth throughout the period of 1990 to 2020. Extreme surface temperature values above 31°C have also been shown in open soils in under-construction sites for future developmental purposes. UTFVI is categorized into six categories representing UHI intensity in relation to ecological conditions. Finally, comparative analysis between land use/land cover (LULC) with UTFVI shows that the ecological conditions deteriorate as the intensity of UHI increases in the area. The developed areas facing ecological threat have increased from 9.3–19.8% throughout the period. Effective mitigating measures such as increasing green surfaces and planned urbanization practices are crucial in this regard. This study would help policymakers to concentrate on controlling thermal exposure and on preserving sustainable urban life.

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.

Urban heat island estimation from improved selection of urban and rural stations by DTW algorithm

2021 ◽  
Author(s):  
Yonghong Hu ◽  
Gensuo Jia ◽  
Jinlong Ai ◽  
Yong Zhang ◽  
Meiting Hou ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Urban Climate ◽  
Global Scale ◽  
Heat Island ◽  
Climate Effect ◽  
Urban Heat ◽  
The Difference ◽  
Temperature Records ◽  
Dynamic Time ◽  
Selection Of

Abstract Typical urban and rural temperature records are essential for the estimation and comparison of urban heat island effects in different regions, and the key issues are how to identify the typical urban and rural stations. This study tried to analyze the similarity of air temperature sequences by using dynamic time warping algorithm (DTW) to improve the selection of typical stations. We examined the similarity of temperature sequences of 20 stations in Beijing and validated by remote sensing, and the results indicated that DTW algorithm could identify the difference of temperature sequence, and clearly divide them into different groups according to their probability distribution information. The analysis for station pairs with high similarity could provide appropriate classification for typical urban stations (FT, SY, HD, TZ, CY, CP, MTG, BJ, SJS, DX, FS) and typical rural stations (ZT, SDZ, XYL) in Beijing. We also found that some traditional rural stations can’t represent temperature variation in rural surface because of their surrounding environments highly modified by urbanization process in last decades, and they may underestimate the urban climate effect by 1.24℃. DTW algorithm is simple in analysis and application for temperature sequences, and has good potentials in improving urban heat island estimation in regional or global scale by selecting more appropriate temperature records.

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.

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