scholarly journals Effect of Land Use/Cover Changes on Urban Cool Island Phenomenon in Seville, Spain

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3040
Author(s):  
Eulalia Jadraque Gago ◽  
Saioa Etxebarria Berrizbeitia ◽  
Rosalía Pacheco Torres ◽  
Tariq Muneer
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Green Space ◽  
Behavior Pattern ◽  
Linear Regression Analysis ◽  
Negative Relationship ◽  
Impervious Surface ◽  
Mitigation Strategies ◽  
Cultivated Land ◽  
Time Periods

This paper analyses Seville’s surface urban heat island (SUHI) phenomenon, comparing spatial and temporal patterns of land surface temperature (LST) during July 1987, 2000 and 2017. Landsat data captured throughout three July months were analyzed for the different years, techniques of geographic information systems, ecological variables and geospatial approaches and used to carry out the analysis. The results indicate that from 1987 to 2017, the averaged LST has increased by 9.1 °C in the studied area. The urban areas are colder than their surroundings, suggesting the role of baresoil and cultivated land in the reversal of the SUHI phenomenon. The results show that a fraction of green space has a high unstandardized coefficient (β) through the three time periods. A decreasing trend is also observed in the standardized β “fraction of impervious surface” in the three time periods. The linear regression analysis shows a negative relationship of mean LST with impervious surface fraction due to the presence of shadows projected by buildings, and a positive relationship with green space fraction caused by the influence of baresoil and cultivated land that inverts the LST behavior pattern. The study concludes that there is a need to implement SUHI mitigation strategies during the initial phases of engineering projects where the origin of this problem can be acted upon, since the process of creating streets and public space offers a valuable opportunity to restore the environmental quality and diminish the effects generated by climate change.

scholarly journals THE EFFECT OF GREEN SPACE ON THE LAND SURFACE TEMPERATURE IN HUE CITY

2018 ◽  
Vol 55 (4C) ◽  
pp. 129
Author(s):  
Nguyen Bac Giang
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Green Space ◽  
Satellite Image ◽  
Urban Green Space ◽  
Landsat 8 ◽  
Urban Green ◽  
Study Results

This paper presents the analysis of the effect of urban green space types on land surface temperature in Hue city. Data are collected with temperature monitoring results from each green space type and the interpretation of surface temperature based on Landsat 8 satellite image data to determine temperatures at different times of the year. Results showed that there was a significant correlation between types of urban green space and the surface temperature. Types of green space with a large area and vegetation indexes have a greater effect on temperature than areas with a smaller green space do. Green space types including forest green space, dedicated green space and agriculture green space have the most effect on the surface temperature. The forest area has the greatest influence on the temperature with a temperature difference of more than 1.6 degrees Celsius at 9:00 in the daytime. Besides, the results extracted from satellite images also show that the area of urban green space going to be reduced makes a contribution to increase the surface temperature of urban areas. The study results have established foundation for planning the green spaces in climate change challenges in Hue City.

scholarly journals Comparative Study of Factors Contributing to Land Surface Temperature in High-Density Built Environments in Megacities Using Satellite Imagery

2021 ◽  
Vol 13 (24) ◽  
pp. 13706
Author(s):  
Frankie Fanjie Zeng ◽  
Jiajun Feng ◽  
Yuanzhi Zhang ◽  
Jin Yeu Tsou ◽  
Tengfei Xue ◽  
...  
Keyword(s):  
Land Use ◽  
Hong Kong ◽  
Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Linear Regression Analysis ◽  
Large Area ◽  
Combination Strategy ◽  
International Airport ◽  
Artificial Heat

In this study, the root sources contributing to the urban heat island (UHI) effect between megacities, such as Hong Kong and Shenzhen, were integrated and compared using satellite remote sensing data. Classification and multilayer perceptron regression tree (CARTMLP) algorithms were used to classify land use. The radiative transfer equation method was applied to retrieve the land surface temperatures (LSTs) in the study area. Multiple linear regression analysis was applied to determine the relationship between land-use types and UHIs. The experimental results show a large area of relatively high temperature dispersed within Shenzhen, and comparatively small areas highly centralized in Hong Kong, with the retrieved LST in Hong Kong lower than that in Shenzhen. In addition, the surface temperature of large complex buildings decorated with high-albedo materials in Hong Kong was higher than in Shenzhen (e.g., Hong Kong International Airport, 25.12 °C; Shenzhen Bao’an International Airport, 23.38 °C), with artificial heat being an important contributor to these differences. These results also imply that high-albedo materials are sufficient to alleviate high temperatures. These findings are integrated to propose an organic combination strategy for reducing UHI effects in urban areas in megacities worldwide, such as Hong Kong and Shenzhen in China.

scholarly journals Assessing the quantitative relationships between the impervious surface area and surface heat island effect during urban expansion

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11854
Author(s):  
Xiaoliang Ma ◽  
Shuangyun Peng
Keyword(s):  
Spatial Distribution ◽  
Surface Area ◽  
Land Surface ◽  
Green Space ◽  
Urban Expansion ◽  
Remote Sensing Data ◽  
Impervious Surface ◽  
Water Bodies ◽  
Heat Island ◽  
Impervious Surface Area

As an important component of underlying urban surfaces, the distribution pattern and density of the impervious surface area (ISA) play an important role in the generation of surface urban heat island (SUHI) effects. However, the quantitative and localized exploration of the ISA’s influence on SUHIs in the process of urban expansion from the perspective of temporal and spatial changes is still not clear. Based on multisource remote sensing data, the SUHI effect of urban expansion is revealed by using geospatial analysis methods such as profile, difference and regression analysis. The results show the following: (1) urban expansion plays a significant role in aggravating SUHIs. Overall, the ISA and land surface temperature (LST) have obvious consistency in terms of spatial distribution patterns. However, local spatial differentiation is significant. The areas with the highest LST were not concentrated in the downtown area with the highest ISA but were scattered in the cultivated land and exposed surface areas under development in the northern part of the city. (2) In general, the ISA can explain the spatial distribution of LST well, there is an obvious positive correlation between them, and the quadratic polynomial function is the best fitting model between them. (3) The density and spatial allocation of ecological elements, such as green space and water bodies, play an important role in alleviating SUHIs. This study found that the urban center with the highest ISA coverage rate has no significant SUHI due to the reasonable allocation of green space and water bodies. The research results can provide a scientific basis for future urban planning and ecological environment construction.

scholarly journals Analyzing the Urban Heat Island Characteristics and Mitigation Strategies in Eight Arid and Semi-Arid Cities

2020 ◽  
Author(s):  
Ammar Abulibdeh
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Urban Areas ◽  
Mitigation Strategies ◽  
The Other ◽  
Heat Island ◽  
Green Areas ◽  
Urban Heat ◽  
Semi Arid Region ◽  
Semi Arid

The aim of the study is two fold: first, the study analyzes the formation of the urban heat island (UHI) in eight different cities in arid and semi-arid region. The analysis is based on land cover / land use (LCLU) classification (urban, green, and bare areas). Second, the study synthesizes the mitigation strategies to reduce the land surface temperature (LST) and hence the UHI effects in the arid and semi-arid cities. The study found that the bare areas have the highest mean LST compared to the urban and green areas. Furthermore, the study found that the LST varies in each of the LCLU categories and hence some areas of the three categories have LST lower or higher than the other categories and hence not always one category has the highest LST compared to the other categories. The outcomes of this study may have key implications for urban planners seeking to mitigate urban heat island effects in arid and semi-arid urban areas.

scholarly journals Remote Sensing-Based Quantification of the Relationships between Land Use Land Cover Changes and Surface Temperature over the Lower Himalayan Region

2019 ◽  
Vol 11 (19) ◽  
pp. 5492 ◽  
Author(s):  
Ullah ◽  
Tahir ◽  
Akbar ◽  
Hassan ◽  
Dewan ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Linear Regression Analysis ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Total Study Area

Population growth and population inflow from other regions has caused urbanization which altered land use land cover (LULC) in the lower Himalayan regions of Pakistan. This LULC change increased the land surface temperature (LST) in the region. LULC and LST changes were assessed for the period of 1990–2017 using Landsat data and the support vector machine (SVM) method. A combined cellular automata and artificial neural network (CA-ANN) prediction model was used for simulation of LULC changes for the period of 2032 and 2047 using transition potential matrix obtained from the data years of 2002 and 2017. The accuracy of the CA-ANN model was validated using simulated and classified images of 2017 with correctness value of 70% using validation modules in QGIS. The thermal bands of Landsat images from the years 1990, 2002 and 2017 were used for LST derivation. LST acquired for this period was then modeled for 2032 and 2047 using urban indices (UI) and linear regression analysis. The SVM land cover classification results showed a 5.75% and 4.22% increase in built-up area and bare soil respectively, while vegetation declined by 9.88% during 1990–2017. The results of LST for LULC classes showed that the built-up area had the highest mean LST as compared to other classes. The future projection of LULC and LST showed that the built-up area may increase by 12.48% and 14.65% in 2032 and 2047, respectively, of the total LULC area which was ~11% in 2017. Similarly, the area with temperature above 30 °C could be 44.01% and 58.02% in 2032 and 2047, respectively, of the total study area which was 18.64% in 2017. This study identified major challenges for urban planners to mitigate the urban heat island (UHI) phenomenon. In order to address the UHI in the study area, an urban planner might focus on urban plantation and decentralization of urban areas.

scholarly journals Persebaran Fenomena Suhu Tinggi melalui Kerapatan Vegetasi dan Pertumbuhan Bangunan serta Distribusi Suhu Permukaan

2020 ◽  
Vol 17 (2) ◽  
pp. 56-62
Author(s):  
Eggy Arya Giofandi
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Urban Areas ◽  
Green Space ◽  
Initial Temperature ◽  
Landsat 8 ◽  
Heat Island ◽  
Surrounding Area ◽  
Urban Heat ◽  
The City

Urban heat island is one of the events where the temperature in the metropolitan area is warmer than the surrounding area. Indonesia is located in a tropical climate making several cities potentially increase in temperature during the dry season. As a representative, the City of Pekanbaru is one of the cities with infrastructure growth that is fast including on the island of Sumatra. Population growth and high enthusiastic of residents to find work in the city made land on the edge of the city built up. This makes the green space less and less with the uneven distribution of green space in the city of Pekanbaru. The number of buildings that exist makes the temperature rise in urban areas with an initial temperature of 29oC to 36oC. temperature increases occurred throughout the year with the hottest peaks of temperatures reaching 37oC on April 15, 2013. Whereas in 2009 there was a decrease in temperature with levels ranging from 27oC. This makes the city of Pekanbaru one of the hottest cities in Indonesia. This study uses Landsat 5 imagery for 2000 and 2009, and Landsat 8 for 2018 with the Land Surface Temperature (LST) method and Normalized Difference Built-up Index (NDBI) which are useful to explain the urban heat island distribution (UHI) in Pekanbaru City

scholarly journals A 30-meter resolution dataset of China's urban impervious surface area and green space fractions, 2000–2018

2020 ◽  
Author(s):  
Wenhui Kuang ◽  
Shu Zhang ◽  
Xiaoyong Li ◽  
Dengsheng Lu
Keyword(s):  
Land Use ◽  
Surface Area ◽  
Urban Areas ◽  
Green Space ◽  
Impervious Surface ◽  
Urban Land ◽  
Google Earth ◽  
Urban Land Use ◽  
Impervious Surface Area ◽  
Urban Impervious Surface

Abstract. Urban impervious surface area (UISA) and urban green space (UGS) are two core components of cities for characterizing urban environments. Although several global or national urban land use/cover products such as Globeland30 and FROM-GLC are available, they cannot effectively delineate the complex intra-urban land cover components. Here we proposed a new approach to map fractional UISA and UGS in China using Google Earth Engine (GEE) based on multiple data sources. The first step is to extract the vector boundaries of urban areas from China's Land Use/cover Dataset (CLUD). The UISA was retrieved using the logistic regression from the Landsat-derived annual maximum Normalized Difference Vegetation Index (NDVI). The UGS was developed through linear calibration between reference UGS from high spatial resolution image and the normalized NDVI. Thus, the China's UISA and UGS fraction datasets (CLUD-Urban) at 30-meter resolution are generated from 2000 to 2018. The overall accuracy of national urban areas is over 92 %. The root mean square errors of UISA and UGS fractions are 0.10 and 0.14, respectively. The datasets indicate that total urban area of China was 7.10 ×104 km2 in 2018, with average fractions of 70.70 % for UISA and 26.54 % for UGS. The UISA and UGS increased with unprecedented annual rates of 1,492.63 km2/yr and 400.43 km2/yr during 2000–2018. CLUD-Urban can enhance our understanding of urbanization impacts on ecological and urban dwellers’ environments, and can be used in such applications as urban planning, urban environmental studies and practices. The datasets can be downloaded from https://doi.org/10.5281/zenodo.3778424 (Kuang et al., 2020).

scholarly journals Evaluation of the Equity and Regional Management of Some Urban Green Space Ecosystem Services: A Case Study of Main Urban Area of Xi’an City

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 813
Author(s):  
Hui Dang ◽  
Jing Li ◽  
Yumeng Zhang ◽  
Zixiang Zhou
Keyword(s):  
Ecosystem Services ◽  
Carbon Sequestration ◽  
Urban Areas ◽  
Green Space ◽  
Well Being ◽  
Urban Green Space ◽  
Green Spaces ◽  
Deposition Flux ◽  
Urban Green ◽  
Xi’An City

Urban green spaces can provide many types of ecosystem services for residents. An imbalance in the pattern of green spaces leads to an inequality of the benefits of such spaces. Given the current situation of environmental problems and the basic geographical conditions of Xi’an City, this study evaluated and mapped four kinds of ecosystem services from the perspective of equity: biodiversity, carbon sequestration, air purification, and climate regulation. Regionalization with dynamically constrained agglomerative clustering and partitioning (REDCAP) was used to obtain the partition groups of ecosystem services. The results indicate that first, the complexity of the urban green space community is low, and the level of biodiversity needs to be improved. The dry deposition flux of particulate matter (PM2.5) decreases from north to south, and green spaces enhance the adsorption of PM2.5. Carbon sequestration in the south and east is higher than that in the north and west, respectively. The average surface temperature in green spaces is lower than that in other urban areas. Second, urban green space resources in the study area are unevenly distributed. Therefore, ecosystem services in different areas are inequitable. Finally, based on the regionalization of integrated ecosystem services, an ecosystem services cluster was developed. This included 913 grid spaces, 12 partitions, and 5 clusters, which can provide a reference for distinct levels of ecosystem services management. This can assist urban managers who can use these indicators of ecosystem service levels for planning and guiding the overall development pattern of green spaces. The benefits would be a maximization of the ecological functions of green spaces, an improvement of the sustainable development of the city, and an improvement of people’s well-being.

scholarly journals Socioeconomic Differences in Walking Time of Children and Adolescents to Public Green Spaces in Urban Areas—Results of the German Environmental Survey (2014–2017)

2021 ◽  
Vol 18 (5) ◽  
pp. 2326
Author(s):  
Julia Rehling ◽  
Christiane Bunge ◽  
Julia Waldhauer ◽  
André Conrad
Keyword(s):  
Young People ◽  
Children And Adolescents ◽  
Urban Areas ◽  
Green Space ◽  
Positive Impact ◽  
Green Spaces ◽  
Environmental Survey ◽  
Urban Green Spaces ◽  
Public Green Space ◽  
Walking Time

Public green spaces have a high potential for a positive impact on people’s health and wellbeing, especially in urban areas. Studies on environmental justice indicate socially unequal access possibilities to urban green spaces. This article presents results on associations between individual socioeconomic position (SEP) and walking time from home to public green spaces in young people living in urban areas with more than 20,000 inhabitants in Germany. Data were derived from the German Environmental Survey for Children and Adolescents 2014–2017 (GerES V), the environmental module of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS Wave 2). The sample comprises 1149 participants aged 3 to 17 years. A total of 51.5% of the participants reach a public green space on foot within five and 72.8% within ten minutes from home. The lower the participant’s SEP, the longer the walking time. Logistic regression models controlling for age group, sex, migration background, and region of residence show that participants with a low SEP have a significantly higher risk (odds ratio = 1.98; 95% confidence interval: 1.31–2.99) of needing more than ten minutes to walk from home to a public green space than participants with a high SEP. GerES V data indicate that young people living in urban areas in Germany do not equally benefit from the health-promoting potential of green spaces, which is an important aspect of environmental health inequalities.

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