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 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 Urban Heat Island in Kathmandu, Nepal: Evaluating Relationship between NDVI and LST from 2000 to 2018

2019 ◽  
Vol 8 (1) ◽  
pp. 17-29
Author(s):  
Bijesh Mishra ◽  
Jeremy Sandifer ◽  
Buddhi Raj Gyawali
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Surface Characteristics ◽  
Heat Island ◽  
Rate Of Increase ◽  
Urban Heat

The term “urban heat island” (UHI) describes increased surface and atmospheric temperatures in an urban core relative to surrounding non-urbanized areas. Although the phenomenon has been studied to a great extent throughout the world, it is less understood for Kathmandu, Nepal. This study used the Moderate Resolution Imaging Spectro-radiometer (MODIS) 8-day product (MOD11A2) to evaluate land surface temperatures (LSTs), the MODIS-derived Normalized Difference Vegetation Index (NDVI) 16-day product (MOD13Q1) to quantify land surface characteristics, and the MODIS annual land cover classification product (MCD12Q1) to identify major land cover classes. We evaluated the spatial correlation between significant changes in LSTs and NDVI between 2000–2018. Overall, urban (permanently developed areas) LSTs were consistently greater than non-urban (forests and dynamic agriculture lands) LSTs; however, the rate of increase in temperature was higher outside the central Kathmandu developed urban area. Furthermore, significant changes in NDVI values over time were more widespread and not always spatially coincident with significant changes in LST values, particularly for forested land areas. These results provide insight into systematic planning of open and green areas, construction of new infrastructure in peripheral areas, and highlight the challenges in applying traditional UHI conceptual models to rapidly developing urban areas such as Kathmandu, Nepal.

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 Surface Urban Heat Island Assessment of a Cold Desert City: A Case Study over the Isfahan Metropolitan Area of Iran

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1368
Author(s):  
Alireza Karimi ◽  
Pir Mohammad ◽  
Sadaf Gachkar ◽  
Darya Gachkar ◽  
Antonio García-Martínez ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Metropolitan Area ◽  
Negative Correlation ◽  
Land Surface ◽  
Vegetation Index ◽  
Urban Heat Islands ◽  
Heat Island ◽  
Cold Desert ◽  
Urban Heat ◽  
Surface Urban Heat Island

This study investigates the diurnal, seasonal, monthly and temporal variation of land surface temperature (LST) and surface urban heat island intensity (SUHII) over the Isfahan metropolitan area, Iran, during 2003–2019 using MODIS data. It also examines the driving factors of SUHII like cropland, built-up areas (BI), the urban–rural difference in enhanced vegetation index (ΔEVI), evapotranspiration (ΔET), and white sky albedo (ΔWSA). The results reveal the presence of urban cool islands during the daytime and urban heat islands at night. The maximum SUHII was observed at 22:30 pm, while the minimum was at 10:30 am. The summer months (June to September) show higher SUHII compared to the winter months (February to May). The daytime SUHII demonstrates a robust positive correlation with cropland and ΔWSA, and a negative correlation with ΔET, ΔEVI, and BI. The nighttime SUHII displays a negative correlation with ΔET and ΔEVI.

scholarly journals The localization of urban heat island in the Katowice conurbation (Poland) using the combination of land surface temperature, Normalized Difference Vegetation Index and Normalized Difference Built-up Index

2021 ◽  
Vol 94 (1) ◽  
pp. 111-129
Author(s):  
Ádám Nádudvari
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
High Surface ◽  
Temperature Measurements ◽  
Heat Island ◽  
Urban Heat

The localization of Surface Urban Heat Island (SUHI) as a potential heat risk for the urban population was evaluated. The paper aimed to propose an approach to quantify and localize (SUHI) based on Landsat series TM, ETM+, OLI satellite imageries from the period 1996-2018 and recognize the Atmospheric Urban Heat Island (AUHI) effects from long term temperature measurements. Using the theoretical relation between the Normalized Difference Built-up Index (NDBI), the Normalized Difference Vegetation Index (NDVI) and the LST (Land Surface Temperature), SUHIintensity and SUHIrisk maps were created from the combination of LST, NDVI, NDBI using threshold values to localize urban heat island in the Katowice conurbation. Negative values of SUHI intensity characterize areas where there is no vegetation, highly built-up areas, and areas with high surface temperatures. The urban grow – revealed from SUHI – and global climate change are acting together to strengthen the global AUHI effect in the region as the temperature measurements were indicated.

scholarly journals Hubungan Kerapatan Vegetasi dan Bangunan terhadap UHI (Urban Heat Island) di Kota Magelang

Ruang ◽  
2019 ◽  
Vol 5 (2) ◽  
pp. 83
Author(s):  
Febriyan Riyadi ◽  
Sri Rahayu
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Least Square ◽  
Heat Island ◽  
Ordinary Least Square ◽  
Urban Heat

Urban Heat Island (UHI) adalah fenomena dimana suatu wilayah perkotaan lebih panas daripada wilayah disekitarnya. Faktor utama yang mempengaruhi terjadinya UHI adalah terjadinya konversi tutupan lahan vegetasi menjadi daerah terbangun akibat perkembangan kota. Hal tersebut mengakibatkan peningkatan suhu permukaan, dikarenakan kerapatan vegetasi yang berkurang dan meningkatnya kerapatan bangunan. Analisis yang digunakan adalah klasifikasi tak terbimbing untuk melihat perubahan tutupan lahan, analisis NDVI (Normalized Difference Vegetation Index) untuk mengetahui perubahan vegetasi, analisis NDBI (Normalized Difference Vegetation Index) untuk mengetahui perubahan kerapatan bangunan, serta menggunakan LST (Land Surface Temperature) untuk mengetahui suhu permukaan suatu kota dan OLS (Ordinary Least Square) merupakan permodelan regresi berganda pada aplikasi ArcGis  digunakan untuk mengetahui hubungan antar variabel tersebut. Hasil dalam penelitian ini menunjukkan bahwa suhu rata-rata Kota Magelang pada tahun 2000 sebesar 22,58°C meningkat menjadi 27,11°C pada tahun 2016. Artinya suhu rata-rata Kota Magelang mengalami kenaikan sebesar 4,53°C. Hubungan antara kerapatan bangunan (x1) dan kerapatan vegetasi (x2) terhadap suhu permukaan (y) diketahui melalui formula OLS yang dihasilkan yaitu Y= 5,61 X1 – 1,34 X2 + 2,4.Hal ini berarti jika kerapatan bangunan meningkat dan kerapatan vegetasi berkurang, maka suhu permukaan meningkat.

scholarly journals The Urban Heat Island in an Urban Context: A Case Study of Mashhad, Iran

2019 ◽  
Vol 16 (3) ◽  
pp. 313 ◽  
Author(s):  
Marzie Naserikia ◽  
Elyas Asadi Shamsabadi ◽  
Mojtaba Rafieian ◽  
Walter Leal Filho
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Weather Conditions ◽  
Heat Island ◽  
Urban Heat ◽  
Semi Arid

In this study, the spatio-temporal changes of urban heat island (UHI) in a mega city located in a semi-arid region and the relationships with normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI) are appraised using Landsat TM/OLI images with the help of ENVI and ArcGIS software. The results reveal that the relationships between NDBI, NDVI and land surface temperature (LST) varied by year in the study area and they are not suitable indices to study the land surface temperature in arid and semi-arid regions. The study also highlights the importance of weather conditions when appraising the relationship of these indices with land surface temperature. Overall, it can be concluded that LST in arid and steppe regions is most influenced by barren soil. As a result, built-up areas surrounded by soil or bituminous asphalt experience higher land surface temperatures compared to densely built-up areas. Therefore, apart from setting-up more green areas, an effective way to reduce the intensity of UHI in these regions is to develop the use of cool and smart pavements. The experiences from this paper may be of use to cities, many of which are struggling to adapt to a changing climate.

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