scholarly journals Relationships between land cover and the surface urban heat island: seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures

2013 ◽  
Vol 29 (1) ◽  
pp. 153-167 ◽  
Author(s):  
Weiqi Zhou ◽  
Yuguo Qian ◽  
Xiaoma Li ◽  
Weifeng Li ◽  
Lijian Han
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Seasonal Variability ◽  
Land Surface ◽  
Heat Island ◽  
Land Cover Data ◽  
Thematic Resolution ◽  
Land Surface Temperatures ◽  
Urban Heat ◽  
Surface Urban Heat Island

scholarly journals Effect of Land Cover Fractions on Changes in Surface Urban Heat Islands Using Landsat Time-Series Images

2019 ◽  
Vol 16 (6) ◽  
pp. 971 ◽  
Author(s):  
Tao Chen ◽  
Anchang Sun ◽  
Ruiqing Niu
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Urban Heat Island Intensity ◽  
Heat Island ◽  
Impervious Surfaces ◽  
Heat Islands ◽  
Urban Heat ◽  
Surface Urban Heat Island

Man-made materials now cover a dominant proportion of urban areas, and such conditions not only change the absorption of solar radiation, but also the allocation of the solar radiation and cause the surface urban heat island effect, which is considered a serious problem associated with the deterioration of urban environments. Although numerous studies have been performed on surface urban heat islands, only a few have focused on the effect of land cover changes on surface urban heat islands over a long time period. Using six Landsat image scenes of the Metropolitan Development Area of Wuhan, our experiment (1) applied a mapping method for normalized land surface temperatures with three land cover fractions, which were impervious surfaces, non-chlorophyllous vegetation and soil and vegetation fractions, and (2) performed a fitting analysis of fierce change areas in the surface urban heat island intensity based on a time trajectory. Thematic thermal maps were drawn to analyze the distribution of and variations in the surface urban heat island in the study area. A Multiple Endmember Spectral Mixture Analysis was used to extract the land cover fraction information. Then, six ternary triangle contour graphics were drawn based on the land surface temperature and land cover fraction information. A time trajectory was created to summarize the changing characteristics of the surface urban heat island intensity. A fitting analysis was conducted for areas showing fierce changes in the urban heat intensity. Our results revealed that impervious surfaces had the largest impacts on surface urban heat island intensity, followed by the non-chlorophyllous vegetation and soil fraction. Moreover, the results indicated that the vegetation fraction can alleviate the occurrence of surface urban heat islands. These results reveal the impact of the land cover fractions on surface urban heat islands. Urban expansion generates impervious artificial objects that replace pervious natural objects, which causes an increase in land surface temperature and results in a surface urban heat island.

Bi-temporal Monitoring the Spatial Pattern and Variations of the Surface Urban Heat Island in three Chinese Coastal Megacities: A Comparative Study of Guangzhou, Hangzhou, and Shanghai.

2020 ◽  
Author(s):  
Fei Liu
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Hot Spots ◽  
Land Surface ◽  
Urban Expansion ◽  
Spatial Regression ◽  
Heat Island ◽  
Thermal Environments ◽  
Urban Heat ◽  
Surface Urban Heat Island

<p>The side-effect of booming urbanization on the ecosystem and climate system has been continuously exacerbating. The coastal metropolises are located at the interface between land and ocean, unavoidably influenced by multiple aspects of the terrestrial environments, aquatic ecosystems, and urban developments. Thus, the environmental health of coastal metropolis should be more concerned. In this study, targeting Guangzhou, Hangzhou, and Shanghai, an attempt was made to evaluate the spatiotemporal patterns and variations of surface urban heat island (SUHI) in three coastal metropolises of China based on Landsat-derived land surface temperatures (LST) and land cover data. The results indicate that overall, within a nearly 15-year interval, the extents of hot spots in three metropolises were significantly expanded, the spatial patterns of SUHI have been transformed from monocentric to polycentric high-LST clusters, which were identical to the trend of urban expansion. However,  these three metropolises possess distinct features in terms of the thermal layouts and land cover/use composition. Although the total area of SUHI hot spots in Shanghai has surged, the intensity of some hot spots has been a shrink. Besides, the interactions and associations between SUHI and urban development were investigated using spatial regression analysis. The urban composition and configuration considerably affected the intensity of SUHI. Terrain morphology constrained the SUHI. Prolific population growth had a continuing effect on SUHI formation. The proportion of forests displayed a consistently critical influence on easing the adverse of SUHI. Additionally, it is essential to appropriately consider the impacts of water in the comparative analysis of different thermal environments. However, water might be treated as a time-invariant factor and have a limited effect on the bi-temporal comparison for each metropolis. These findings suggest the policy-makers and urban planners should balance and optimize the land cover/use configurations with accommodating the increasing population, reasonably maximize the reservations of the greenbelt and green space under improving the utilization of urban infrastructures and constructions.</p>

scholarly journals Machine Learning Simulation of Land Cover Impact on Surface Urban Heat Island Surrounding Park Areas

2021 ◽  
Vol 13 (22) ◽  
pp. 12678
Author(s):  
Dakota McCarty ◽  
Jaekyung Lee ◽  
Hyun Woo Kim
Keyword(s):  
Machine Learning ◽  
Land Cover ◽  
Urban Heat Island ◽  
Land Surface ◽  
Heat Island ◽  
Land Use Land Cover ◽  
Island Effect ◽  
Land Surface Temperatures ◽  
Urban Heat ◽  
The City

The urban heat island effect has been studied extensively by many researchers around the world with the process of urbanization coming about as one of the major culprits of the increasing urban land surface temperatures. Over the past 20 years, the city of Dallas, Texas, has consistently been one of the fastest growing cities in the United States and has faced rapid urbanization and great amounts of urban sprawl, leading to an increase in built-up surface area. In this study, we utilize Landsat 8 satellite images, Geographic Information System (GIS) technologies, land use/land cover (LULC) data, and a state-of-the-art methodology combining machine learning algorithms (eXtreme Gradient Boosted models, or XGBoost) and a modern game theoretic-based approach (Shapley Additive exPlanation, or SHAP values) to investigate how different land use/land cover classifications impact the land surface temperature and park cooling effects in the city of Dallas. We conclude that green spaces, residential, and commercial/office spaces have the largest impacts on Land Surface Temperatures (LST) as well as the Park’s Cooling Intensity (PCI). Additionally, we have found that the extent and direction of influence of these categories depends heavily on the surrounding area. By using SHAP values we can describe these interactions in greater detail than previous studies. These results will provide an important reference for future urban and park placement planning to minimize the urban heat island effect, especially in sprawling cities.

scholarly journals The Use of Land Cover Indices for Rapid Surface Urban Heat Island Detection from Multi-Temporal Landsat Imageries

2021 ◽  
Vol 10 (6) ◽  
pp. 416
Author(s):  
Nagihan Aslan ◽  
Dilek Koc-San
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Heat Island ◽  
Landsat Images ◽  
Multi Temporal ◽  
Urban Heat ◽  
Surface Urban Heat Island

The aims of this study were to determine surface urban heat island (SUHI) effects and to analyze the land use/land cover (LULC) and land surface temperature (LST) changes for 11 time periods from the years 2002 to 2020 using Landsat time series images. Bursa, which is the fourth largest metropolitan city in Turkey, was selected as the study area, and Landsat multi-temporal images of the summer season were used. Firstly, the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), modified normalized difference water index (MNDWI) and index-based built-up index (IBI) were created using the bands of Landsat images, and LULC classes were determined by applying automatic thresholding. The LST values were calculated using thermal images and SUHI effects were determined. The results show that NDVI, SAVI, MNDWI and IBI indices can be used effectively for the determination of the urban, vegetation and water LULC classes for SUHI studies, with overall classification accuracies between 89.60% and 95.90% for the used images. According to the obtained results, generally the LST values increased for almost all land cover areas between the years 2002 and 2020. The SUHI magnitudes were computed by using two methods, and it was found that there was an important increase in the 18-year time period.

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 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.

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