scholarly journals Evaluation of the Spatial Pattern of the Resolution-Enhanced Thermal Data for Urban Area

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xiao Feng ◽  
Jiyuan Li
Keyword(s):  
Spatial Pattern ◽  
Urban Area ◽  
Land Surface ◽  
Spatial Information ◽  
Thermal Environment ◽  
Accuracy Evaluation ◽  
Different Seasons ◽  
Statistical Aspect ◽  
Urban Heat ◽  
Temporal And Spatial

With the development of urbanization, land surface temperature (LST), as a vital variable for the urban environment, is highly demanded by urban-related studies, especially the LST with both fine temporal and spatial resolutions. Thermal sharpening methods have been developed just under this demand. Until now, there are some thermal sharpening methods proposed especially for urban surface. However, the evaluation of their accuracy still stopped at the level that only considers the statistical aspect, but no spatial information has been included. It is widely acknowledged that the spatial pattern of the thermal environment in an urban area is relatively critical for urban-related studies (e.g., urban heat island studies). Thus, this paper chose three typical methods from the limited number of thermal sharpening methods designed for the urban area and made a comparison between them, together with a newly proposed thermal sharpening method, superresolution-based thermal sharpener (SRTS). These four methods are analyzed by data from different seasons to explore the seasoning impact. Also, the accuracy for different land covers is explored as well. Furthermore, accuracy evaluation was not only taken by statistical variables which are commonly used in other studies; evaluation of the spatial pattern, which is equally important for urban-related studies, was also carried out. This time, the spatial pattern not only was analyzed qualitatively but also has been quantified by some variables for the comparison of accuracy. It is found that all methods obtained lower accuracies for data in winter than for data in other seasons. Linear water features and areas along it are difficult to be detected correctly for most methods.

scholarly journals Characterizing the Hourly Variation of Urban Heat Islands in a Snowy Climate City during Summer

2019 ◽  
Vol 16 (14) ◽  
pp. 2467 ◽  
Author(s):  
Chaobin Yang ◽  
Ranghu Wang ◽  
Shuwen Zhang ◽  
Caoxiang Ji ◽  
Xie Fu
Keyword(s):  
Land Use ◽  
Urban Area ◽  
Air Temperature ◽  
Temporal Variability ◽  
Spatial Information ◽  
Thermal Environment ◽  
Thermal Characteristics ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat

Temporal variation of urban heat island (UHI) intensity is one of the most important themes in UHI studies. However, fine-scale temporal variability of UHI with explicit spatial information is sparse in the literature. Based on the hourly air temperature from 195 meteorological stations during August 2015 in Changchun, China, hourly spatiotemporal patterns of UHI were mapped to explore the temporal variability and the effects of land use on the thermal environment using time series analysis, air temperature profiling, and spatial analysis. The results showed that: (1) high air temperature does not indicate strong UHI intensity. The nighttime UHI intensity (1.51 °C) was much stronger than that in the daytime (0.49 °C). (2) The urban area was the hottest during most of the day except the period from late morning to around 13:00 when there was about a 40% possibility for an “inverse UHI intensity” to appear. Paddy land was the coolest in the daytime, while woodland had the lowest temperature during the nighttime. (3) The rural area had higher warming and cooling rates than the urban area after sunrise and sunset. It appeared that 23 °C was the threshold at which the thermal characteristics of different land use types changed significantly.

scholarly journals Seasonal Variations of the Urban Thermal Environment Effect in a Tropical Coastal City

2017 ◽  
Vol 2017 ◽  
pp. 1-18 ◽  
Author(s):  
Yao Yuan ◽  
Chen Xi ◽  
Qian Jing ◽  
Ndayisaba Felix
Keyword(s):  
Land Surface ◽  
Thermal Environment ◽  
Shenzhen City ◽  
Four Seasons ◽  
Different Seasons ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Autumn And Winter ◽  
Urban Thermal Environment ◽  
The City

Shenzhen city was selected to analyze the Surface Urban Heat Island (SUHI) variations based on land surface temperature (LST) in four different seasons of 2015. UHI intensity (UHII) as an indicator of SUHI was established and the method of density segmentation was utilized to classify the SUHI after LSTs were normalized. The gravity center model of UHII and Moran’s I (a spatial autocorrelation index) were used to analyze the spatiotemporal variations of SUHI. Results indicated that LST was higher in the west than in the east of the city. The values of UHII were higher in spring and summer and lower in autumn and winter. Five profiles were drawn to analyze the distribution of UHII in different seasons, and it was found that the No. 1 path profiles, corresponding to the western urban development axis, had higher UHII than other path profiles. The center of UHII gravity shifts converged in the Longhua, Baoan, and Nanshan Districts throughout the four seasons and Moran’s I values were higher in summer and spring. From the UHII’s spatial distribution pattern analysis, a spatially discontinuous pattern was observed in four seasons; there was a compact pattern of high temperature zones.

scholarly journals RS and GIS Supported Urban LULC and UHI Change Simulation and Assessment

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Pei Liu ◽  
Shoujun Jia ◽  
Ruimei Han ◽  
Yuanping Liu ◽  
Xiaofeng Lu ◽  
...  
Keyword(s):  
Land Surface ◽  
Thermal Environment ◽  
Urban Expansion ◽  
Dynamic Change ◽  
Urban Sustainability ◽  
Remotely Sensed Data ◽  
Rapid Urbanization ◽  
Urban Heat ◽  
High Level ◽  
The Impact

Rapid urbanization has become a major urban sustainability concern due to environmental impacts, such as the development of urban heat island (UHI) and the reduction of urban security states. To date, most research on urban sustainability development has focused on dynamic change monitoring or UHI state characterization, while there is little literature on UHI change analysis. In addition, there has been little research on the impact of land use and land cover changes (LULCCs) on UHI, especially simulates future trends of LULCCs, UHI change, and dynamic relationship of LULCCs and UHI. The purpose of this research is to design a remote sensing-based framework that investigates and analyzes how the LULCCs in the process of urbanization affected thermal environment. In order to assess and predict the impact of LULCCs on urban heat environment, multitemporal remotely sensed data from 1986 to 2016 were selected as source data, and Geographic Information System (GIS) methods such as the CA-Markov model were employed to construct the proposed framework. The results showed that (1) there has been a substantial strength of urban expansion during the 40-year study period, (2) the farthest distance urban center of gravity moves from north-northeast (NEE) to west-southwest (WSW) direction, (3) the dominate temperature was middle level, sub-high level, and high level in the research area, (4) there was a higher changing frequency and range from east to west, and (5) there was a significant negative correlation between land surface temperature and vegetation and significant positive correlation between temperature and human settlement.

scholarly journals Impact of urbanization on thermal environment of Chengdu-Chongqing Urban Agglomeration under complex terrain

2021 ◽  
Author(s):  
Si Chen ◽  
Zhenghui Xie ◽  
Jinbo Xie ◽  
Bin Liu ◽  
Binghao Jia ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Urban Area ◽  
Complex Terrain ◽  
Thermal Environment ◽  
Urban Agglomeration ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
Island Effect ◽  
The Future ◽  
Urban Heat

Abstract. Located in the mountainous area of southwest China, the Chengdu-Chongqing Urban Agglomeration (CCUA) was rapidly urbanized in the last four decades, has led to a three-fold urban area expansion, thereby affecting the weather and climate. To investigate the urbanization effects on the thermal environment in the CCUA under the complex terrain, we conducted the simulations using the advanced Weather Research and Forecasting (WRF V4.1.5) model together with the combining land-use scenarios and terrain conditions. We observed that the WRF model reproduces the general synoptic summer weather pattern, particularly for the thermal environment. It was shown that the expansion of the urban area changed the underlying surface's thermal properties, leading to the urban heat island effect, enhanced by the complex terrain further. The simulation with the future scenario shows that the implementation of idealized measures including returning farmland to forests, expanding rivers and lakes can reduce the urban heat island effect and regulate the urban ecosystem. Therefore, the urban planning policy can has potential to provide feasible suggestions to best manage the thermal environment of the future city toward improving the livelihood of the people in the environment.

scholarly journals A Methodology for Comparing the Surface Urban Heat Island in Selected Urban Agglomerations Around the World from Sentinel-3 SLSTR Data

2020 ◽  
Vol 12 (12) ◽  
pp. 2052 ◽  
Author(s):  
José Antonio Sobrino ◽  
Itziar Irakulis
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Urban Area ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Heat Island ◽  
Urban Agglomerations ◽  
The World ◽  
Urban Heat ◽  
Surface Urban Heat Island

Retrieval of land surface temperature (LST) from satellite data allows to estimate the surface urban heat island (SUHI) as the difference between the LST obtained in the urban area and the LST of its surroundings. However, this definition depends on the selection of the urban and surroundings references, which translates into greater difficulty in comparing SUHI values in different urban agglomerations across the world. In order to avoid this problem, a methodology is proposed that allows reliable quantification of the SUHI. The urban reference is obtained from the European Space Agency Climate Change Initiative Land Cover and three surroundings references are considered; that is, the urban adjacent (Su), the future adjacent (Sf), and the peri-urban (Sp), which are obtained from mathematical expressions that depend exclusively on the urban area. In addition, two formulations of SUHI are considered: SUHIMAX and SUHIMEAN, which evaluate the maximum and average SUHI of the urban area for each of the three surrounding references. As the urban population growth phenomenon is a world-scale problem, this methodology has been applied to 71 urban agglomerations around the world using LST data obtained from the sea and land surface temperature radiometer (SLSTR) on board Sentinel-3A. The results show average values of SUHIMEAN of (1.8 ± 0.9) °C, (2.6 ± 1.3) °C, and (3.1 ± 1.7) °C for Su, Sf, and Sp, respectively, and an average difference between SUHIMAX and SUHIMEAN of (3.1 ± 1.1) °C. To complete the study, two additional indices have been considered: the Urban Thermal Field Variation Index (UFTVI) and the Discomfort Index (DI), which proved to be essential for understanding the SUHI phenomenon and its consequences on the quality of life of the inhabitants.

Quantitative Analysis on Steel Framed Roof’s Temperature Effect

2014 ◽  
Vol 584-586 ◽  
pp. 517-520
Author(s):  
Jie Ying Xiao ◽  
Liu Xi Yu ◽  
Na Ji ◽  
Xing Li
Keyword(s):  
Land Surface ◽  
High Speed ◽  
Thermal Environment ◽  
Heat Island ◽  
City Environment ◽  
Landsat Tm Image ◽  
Island Effect ◽  
Tm Image ◽  
Urban Heat ◽  
The Relationship

With the high speed urbanization process during last two decades, city underlaying surface area and structure changed rapidly, which resulted in urban heat island effect and a series of thermal environment effect.This topic has been received widespread attention from many researchers. Among all kinds of underlaying surfaces, steel framed roof, as a kind of widely used building material, was found playing an important role on contribution to warm regional thermal environment. So it is necessary to study the relationship between steel framed roof and temperature. Based on analyzing Landsat TM image of Shijiazhuang city by remote sensing software, we found that steel framed roof can warm city environment 2-4℃, its area ratio and land surface temperature have a quadratic curve fitting with correlation of 0.7898.

scholarly journals Combined Effects of the Surface Urban Heat Island with Landscape Composition and Configuration Based on Remote Sensing: A Case Study of Shanghai, China

2019 ◽  
Vol 11 (10) ◽  
pp. 2890 ◽  
Author(s):  
Hongyu Du ◽  
Jinquan Ai ◽  
Yongli Cai ◽  
Hong Jiang ◽  
Pudong Liu
Keyword(s):  
Remote Sensing ◽  
Urban Heat Island ◽  
Land Surface ◽  
Surface Coverage ◽  
Agricultural Land ◽  
Thermal Environment ◽  
Landscape Patterns ◽  
Heat Island ◽  
Rapid Urbanization ◽  
Urban Heat

Rapid urbanization leads to changes in surface coverage and landscape patterns. This results in urban heat island (UHI) effects and a series of negative ecological consequences. Considering this concern and taking Shanghai as an example, this paper concentrates on the effects of surface coverage and landscape patterns on urban land surface temperature (LST). The research is based on quantitative retrieval of remote sensing data with consideration of methods in multiple disciplines, including landscape ecology, geographic information systems, and statistical analysis. It concludes that, over time, the thermal environment of Shanghai is becoming critical. The average LST ranking of different surface coverage is as follows: Construction land (CL) > bare land (BL) > green land (GL) > agricultural land (AL) > water body (WB). LST varies significantly with the type of surface coverage. CL contributes the most to the UHI, while WB and GL have obvious mitigation effects on the UHI. The large area, low degree of landscape fragmentation, and complex outlines lead to low LST rankings for GL, WB, and AL and a high LST ranking for CL. The conclusions indicate that CL should be broken down by GL and WB into discrete pieces to effectively mitigate UHI effects. The research reveals UHI features and changes in Shanghai over the years and provides practical advice that can be used by urban planning authorities to mitigate UHI.

scholarly journals Influencing Factors and Quality Evaluation of Urban Thermal Environment Based on Artificial Neural Network

2021 ◽  
Vol 39 (1) ◽  
pp. 128-136
Author(s):  
Liangwei Zhao ◽  
Xiaowei Li ◽  
Xuguang Chai
Keyword(s):  
Neural Network ◽  
Influencing Factors ◽  
Bp Neural Network ◽  
Land Surface ◽  
Quality Evaluation ◽  
Thermal Environment ◽  
Island Effect ◽  
Urban Heat ◽  
Urban Thermal Environment ◽  
Mlr Model

To alleviate the urban heat island effect that is getting increasingly serious these days, the research on the monitoring, simulation, and regulation of the thermal environment of cities has become a necessity. Aiming at figuring out the correlations between influencing factors and giving accurate quality evaluation of urban thermal environment, this study extracted 10 influencing factors of urban thermal environment and gave their influence, and then performed the Land Surface Temperature (LST) retrieval of a target city. After that, this paper constructed a Multiple Linear Regression (MLR) model and explored the law of the numerical changes of the influencing factors of urban thermal environment. At last, this paper also built a BP neural network to predict the quality evaluation of urban thermal environment and used experimental results to prove the effectiveness of the proposed algorithm and model.

scholarly journals LANDSCAPE SPATIAL PATTERN INDICES AND SOUNDSCAPE PERCEPTION IN A MULTI-FUNCTIONAL URBAN AREA, GERMANY

2014 ◽  
Vol 22 (3) ◽  
pp. 208-218 ◽  
Author(s):  
Jiang Liu ◽  
Jian Kang ◽  
Holger Behm ◽  
Tao Luo
Keyword(s):  
Spatial Pattern ◽  
Urban Area ◽  
Planning Process ◽  
Spatial Scales ◽  
Shape Index ◽  
Vegetation Density ◽  
Acoustic Environment ◽  
Spatial And Temporal Scales ◽  
Significant Relationships ◽  
Temporal And Spatial

Soundscape research could provide more information about urban acoustic environment, which should be integrated into urban management. The aim of this study is to test how landscape spatial pattern could affect soundscape perception. Soundscape data on specifically defined spatial and temporal scales were observed and evaluated in a multi-functional urban area in Rostock, Germany. The results show that urban soundscapes were characterised by artificial sounds (human, mechanical and traffic sounds) overwhelming the natural ones (biological and geophysical sounds). Major sound categories were normally mutual exclusive and dynamic on temporal scale, and have different spatial distribution on spatial scale. However, biological and traffic sounds seem to be co-existing on both temporal and spatial scales. Significant relationships were found existing between perception of major sound categories and a number of landscape spatial pattern indices, among which vegetation density (NDVI), landscape shape index (LSI) and largest patch index (LPI) showed the most effective indicating ability. The research indicated that soundscape concepts could be applied into landscape and urban planning process through the quantitative landscape indices to achieve a better urban acoustic environment.

scholarly journals Monitoring the Detailed Dynamics of Regional Thermal Environment in a Developing Urban Agglomeration

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1197 ◽  
Author(s):  
Yue Liu ◽  
Hui Li ◽  
Peng Gao ◽  
Cheng Zhong
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Temporal Dynamics ◽  
Thermal Environment ◽  
Urban Heat Islands ◽  
Heat Island ◽  
Heat Islands ◽  
Inner Cities ◽  
Urban Heat ◽  
Moderate Resolution Imaging Spectroradiometer

Many studies have revealed the characteristics and spatial-temporal dynamics of the thermal environment in specific cities or urban agglomerations (UA), as well as the associated determining factors. However, few studies focus on the changing relationships (the difference, distance, interaction, etc.) among inner cities’ heat islands in a UA, which represent not only the detailed dynamics of regional thermal environment (RTE), but also the changing competition and cooperation among cities in a developing UA. In this study, we used Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products to map and analyze the detailed dynamics of the Beijing-Tianjin-Hebei (BTH) UA thermal environment. From 2001 to 2015, the mean surface urban heat island intensity (SUHII) of the BTH increased significantly, and the surface urban heat islands (SUHIs) in the southern BTH have rapidly increased, expanded and connected, eventually forming a large heat islands agglomeration. According to correlation analysis, urban sprawl probably led to the expansion and enhance of SUHIs in the south plain, while the forest has significantly alleviated urban heat island effect in northern mountains. The results expose the detailed evolution process of BTH thermal environment, and the changing relationships among the inner cities. In a developing UA, mitigation solutions (e.g., ecological corridors or controlling energy consumption) are in demand to stop the formation of a great heat region.

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