scholarly journals Satellite Image Fusion to Detect Changing Surface Permeability and Emerging Urban Heat Islands in a Fast-Growing City

2018 ◽  
Author(s):  
Rajchandar Padmanaban ◽  
Pedro Cabral ◽  
Avit K Bhowmik
Keyword(s):  
Surface Temperature ◽  
Image Fusion ◽  
Land Surface ◽  
Large Scale ◽  
Vegetation Index ◽  
Satellite Image ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat ◽  
Surface Permeability

Rapid and extensive urbanization has adversely impacted humans and ecological entities in the recent decades through a decrease in surface permeability and the emergence of urban heat islands (UHI). While detailed and continuous assessments of surface permeability and UHI are crucial for urban planning and management of landuse zones, they have mostly involved time consuming and expensive field studies, and single sensor derived large scale aerial and satellite imageries. We demonstrated the advantage of fusing imageries from multiple sensors for landuse and landcover (LULC) change assessments as well as for assessing surface permeability and UHI emergence in Tirunelveli, Tamilnadu, India. Cartosat-2 and Landsat-7 ETM+ imageries from 2007 and 2017 were fused and classified using a Rotation Forest (RF), while surface permeability and temperature were quantified using Soil-Adjusted Vegetation Index (SAVI) and Land Surface Temperature (LST) index, respectively. Fused images exhibited higher classification accuracies than non-fused images, i.e. overall kappa coefficient values 0.83 and 0.75, respectively. We observed an overall increase of 20 km2 (45%) in the coverage of urban (dry, real estate plots and built-up) areas, while a decrease of 27 km2 (37%) for vegetated (cropland and forest) areas in Tirunelveli between 2007 and 2017. The SAVI values indicated an extensive decrease in surface permeability for Tirunelveli overall (0.4) and also for almost all LULC zones. The LST values exhibited an associated overall increase (1.30C) of surface temperature in Tirunelveli with the highest increase (2.40C) for urban built-up areas between 2007 and 2017. The SAVI-LST combined metric depicted the Southeastern built-up areas in Tirunelveli as a potential UHI hotspot, while a caution for the Western riparian zone for UHI emergence in 2017. Our results provide important metrics for surface permeability and UHI monitoring, and inform urban and zonal planning authorities about the advantages of satellite image fusion.

scholarly journals Night Thermal Unmixing for the Study of Microscale Surface Urban Heat Islands with TRISHNA-Like Data

2019 ◽  
Vol 11 (12) ◽  
pp. 1449 ◽  
Author(s):  
Carlos Granero-Belinchon ◽  
Aurelie Michel ◽  
Jean-Pierre Lagouarde ◽  
Jose A. Sobrino ◽  
Xavier Briottet
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Image Resolution ◽  
Urban Heat Islands ◽  
Land Uses ◽  
Regression Kriging ◽  
Heat Islands ◽  
Urban Heat ◽  
Land Covers ◽  
The City

Urban Heat Islands (UHIs) at the surface and canopy levels are major issues in urban planification and development. For this reason, the comprehension and quantification of the influence that the different land-uses/land-covers have on UHIs is of particular importance. In order to perform a detailed thermal characterisation of the city, measures covering the whole scenario (city and surroundings) and with a recurrent revisit are needed. In addition, a resolution of tens of meters is needed to characterise the urban heterogeneities. Spaceborne remote sensing meets the first and the second requirements but the Land Surface Temperature (LST) resolutions remain too rough compared to the urban object scale. Thermal unmixing techniques have been developed in recent years, allowing LST images during day at the desired scales. However, while LST gives information of surface urban heat islands (SUHIs), canopy UHIs and SUHIs are more correlated during the night, hence the development of thermal unmixing methods for night LSTs is necessary. This article proposes to adapt four empirical unmixing methods of the literature, Disaggregation of radiometric surface Temperature (DisTrad), High-resolution Urban Thermal Sharpener (HUTS), Area-To-Point Regression Kriging (ATPRK), and Adaptive Area-To-Point Regression Kriging (AATPRK), to unmix night LSTs. These methods are based on given relationships between LST and reflective indices, and on invariance hypotheses of these relationships across resolutions. Then, a comparative study of the performances of the different techniques is carried out on TRISHNA synthesized images of Madrid. Since TRISHNA is a mission in preparation, the synthesis of the images has been done according to the planned specification of the satellite and from initial Aircraft Hyperspectral Scanner (AHS) data of the city obtained during the DESIREX 2008 capaign. Thus, the coarse initial resolution is 60 m and the finer post-unmixing one is 20 m. In this article, we show that: (1) AATPRK is the most performant unmixing technique when applied on night LST, with the other three techniques being undesirable for night applications at TRISHNA resolutions. This can be explained by the local application of AATPRK. (2) ATPRK and DisTrad do not improve significantly the LST image resolution. (3) HUTS, which depends on albedo measures, misestimates the LST, leading to the worst temperature unmixing. (4) The two main factors explaining the obtained performances are the local/global application of the method and the reflective indices used in the LST-index relationship.

scholarly journals Multi-Temporal Land Surface Temperature and Vegetation Greenness in Urban Green Spaces of Puebla, Mexico

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 155
Author(s):  
Filoteo Gomez-Martinez ◽  
Kirsten M. de Beurs ◽  
Jennifer Koch ◽  
Jeffrey Widener
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Population Expansion ◽  
Urban Heat Islands ◽  
Green Spaces ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Urban Heat

The urban heat island (UHI) effect is a global problem that is likely to grow as a result of urban population expansion. Multiple studies conclude that green spaces and waterbodies can reduce urban heat islands. However, previous studies often treat urban green spaces (UGSs) as static or limit the number of green spaces investigated within a city. Cognizant of these shortcomings, Landsat derived vegetation and land surface temperature (LST) metrics for 80 urban green spaces in Puebla, Mexico, over a 34-year (1986–2019) and a 20-year (2000–2019) period were studied. To create a photo library, 73 of these green spaces were visited and the available land cover types were recorded. Green spaces with Indian laurel were found to be much greener and vegetation index values remained relatively stable compared to green spaces with mixed vegetation cover. Similarly, green spaces with large waterbodies were cooler than those without water. These results show that larger green spaces were significantly cooler (p < 0.01) and that size can explain almost 30% of temperature variability. Furthermore, green spaces with higher vegetation index values were significantly cooler (p < 0.01), and the relationship between greenness and temperature strengthened over time.

scholarly journals Study of the Parameters of Urban Heat Islands on the Irkutsk Region Territory According to Remote Sensing Data

2020 ◽  
Vol 34 ◽  
pp. 131-140
Author(s):  
E. N. Sutyrina ◽  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Dimensional Structure ◽  
Heat Islands ◽  
Irkutsk Region ◽  
Urban Heat ◽  
The Difference ◽  
The City

The investigation is aimed to determine the boundaries and intensity of urban heat islands in the Irkutsk region and assess the change in these parameters over a long-term period. The formation of an urban heat island is an example of anthropogenic influence on the urban climate. Land surface temperature and its spatial and temporal variations can be used to study urban heat islands, since the difference between the land surface temperature within the city and its surroundings is the result of the transformation of the underlying surface, heat capacity and three-dimensional structure of urban buildings in the process of urbanization. In order to study the phenomenon of urban heat islands of cities of the Irkutsk region, the land surface temperature data reconstructed from AVHRR-based thermal infrared imagery for 1998-2019 was used. As a result of the study, multi-temporal maps showing the urban heat islands of the agglomeration of Irkutsk-Angarsk-Shelekhov and the city of Bratsk were obtained. The investigated heat islands are characterized by a significant diurnal dynamic, so the difference in temperature values between the city and the suburbs in summer daytime reached 8-10 °C, in the evening and at night in summer this parameter decreases to 3-5 °C. The dimensions of the urban heat islands of the cities under investigation in the daytime exceed the dimensions of these heat anomalies in the evening and at night. Interannual variability in the intensity of urban heat islands did not show statistically significant trends from 1998 to 2019, the areas of urban heat islands increased significantly over the study period. The observed increase in area was probably associated with the development of the cities under study, with the transformation of landscapes and a decrease in the density of vegetation in the suburbs. In order to assess the contribution of the lack of vegetation to the formation of the urban heat islands in summer daytime, the values of the land surface temperature were compared with the values of the vegetation index NDVI. An analysis of the relationships between these parameters found that daytime land surface temperature was in close inverse relationship with the NDVI value, while this relationship was less pronounced at night and in the evening.

scholarly journals Assessing the Effects of Land-Use Types in Surface Urban Heat Islands for Developing Comfortable Living in Hanoi City

2018 ◽  
Vol 10 (12) ◽  
pp. 1965 ◽  
Author(s):  
Nguyen Thanh Hoan ◽  
Yuei-An Liou ◽  
Kim-Anh Nguyen ◽  
Ram Sharma ◽  
Duy-Phien Tran ◽  
...  
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Landsat 8 ◽  
Heat Islands ◽  
Land Use Types ◽  
Urban Heat ◽  
Negative Impacts ◽  
The Individual

Hanoi City of Vietnam changes quickly, especially after its state implemented its Master Plan 2030 for the city’s sustainable development in 2011. Then, a number of environmental issues are brought up in response to the master plan’s implementation. Among the issues, the Urban Heat Island (UHI) effect that tends to cause negative impacts on people’s heath becomes one major problem for exploitation to seek for mitigation solutions. In this paper, we investigate the land surface thermal signatures among different land-use types in Hanoi. The surface UHI (SUHI) that characterizes the consequences of the UHI effect is also studied and quantified. Note that our SUHI is defined as the magnitude of temperature differentials between any two land-use types (a more general way than that typically proposed in the literature), including urban and suburban. Relationships between main land-use types in terms of composition, percentage coverage, surface temperature, and SUHI in inner Hanoi in the recent two years 2016 and 2017, were proposed and examined. High correlations were found between the percentage coverage of the land-use types and the land surface temperature (LST). Then, a regression model for estimating the intensity of SUHI from the Landsat 8 imagery was derived, through analyzing the correlation between land-use composition and LST for the year 2017. The model was validated successfully for the prediction of the SUHI for another hot day in 2016. For example, the transformation of a chosen area of 161 ha (1.61 km2) from vegetation to built-up between two years, 2016 and 2017, can result in enhanced thermal contrast by 3.3 °C. The function of the vegetation to lower the LST in a hot environment is evident. The results of this study suggest that the newly developed model provides an opportunity for urban planners and designers to develop measures for adjusting the LST, and for mitigating the consequent effects of UHIs by managing the land use composition and percentage coverage of the individual land-use type.

scholarly journals The Spatiotemporal Implications of Urbanization for Urban Heat Islands in Beijing: A Predictive Approach Based on CA–Markov Modeling (2004–2050)

2021 ◽  
Vol 13 (22) ◽  
pp. 4697
Author(s):  
Muhammad Amir Siddique ◽  
Yu Wang ◽  
Ninghan Xu ◽  
Nadeem Ullah ◽  
Peng Zeng
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Single Channel ◽  
Urban Ecosystems ◽  
Landscape Composition ◽  
Urban Heat Islands ◽  
Markov Modeling ◽  
Heat Islands ◽  
Urban Heat ◽  
Vegetation Water

The rapid increase in infrastructural development in populated areas has had numerous adverse impacts. The rise in land surface temperature (LST) and its associated damage to urban ecological systems result from urban development. Understanding the current and future LST phenomenon and its relationship to landscape composition and land use/cover (LUC) changes is critical to developing policies to mitigate the disastrous impacts of urban heat islands (UHIs) on urban ecosystems. Using remote sensing and GIS data, this study assessed the multi-scale relationship of LUCC and LST of the cosmopolitan exponentially growing area of Beijing, China. We investigated the impacts of LUC on LST in urban agglomeration for a time series (2004–2019) of Landsat data using Classification and Regression Trees (CART) and a single channel algorithm (SCA), respectively. We built a CA–Markov model to forecast future (2025 and 2050) LUCC and LST spatial patterns. Our results indicate that the cumulative changes in an urban area (UA) increased by about 908.15 km2 (5%), and 11% of vegetation area (VA) decreased from 2004 to 2019. The correlation coefficient of LUCC including vegetation, water bodies, and built-up areas with LST had values of r = −0.155 (p > 0.419), −0.809 (p = 0.000), and 0.526 (p = 0.003), respectively. The results surrounding future forecasts revealed an estimated 2309.55 km2 (14%) decrease in vegetation (urban and forest), while an expansion of 1194.78 km2 (8%) was predicted for a built-up area from 2019 to 2050. This decrease in vegetation cover and expansion of settlements would likely cause a rise of about ~5.74 °C to ~9.66 °C in temperature. These findings strongly support the hypothesis that LST is directly related to the vegetation index. In conclusion, the estimated overall increase of 7.5 °C in LST was predicted from 2019–2050, which is alarming for the urban community’s environmental health. The present results provide insight into sustainable environmental development through effective urban planning of Beijing and other urban hotspots.

scholarly journals Assessment of Urban Heat Islands Based on the Relationship Between Land Surface Temperature and Land Use/Land Cover in Greater Doha

2020 ◽  
Author(s):  
Simil Amir Siddiqui
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Land Use Land Cover ◽  
Heat Islands ◽  
Urban Heat ◽  
The City

Urban heat islands (UHI) are areas with elevated temperatures occurring in cities compared to surrounding rural areas. This study realizes the lack of research regarding the trends of UHIs in desert countries and focuses on Doha. The research includes twelve months of two-time periods; 2000-2019. ArcGIS software was used to compute the land surface temperature (LST) of the city using Landsat images. Land use/land cover (LULC) maps were computed to show how the city has evolved in 19 years. 30 field samples were used to verify the accuracy of the LULC. Results showed UHI in Doha did not display similar pattern to that of cities in subtropical and temperate regions. Higher temperatures were prevalent in out-skirts comprising of barren and built-up areas with high population and no vegetation. Comparatively, the main downtown with artificially planted vegetation and shade from skyscrapers created cooler microclimates. The overall LST of greater Doha has increased by 0.7°C from 2000 to 2019. Furthermore %LULC of built up, vegetation, barren land, marsh land and water body were 29%, 4.5%, 58.6%, 2.8% and 5% in 2000 and 56.5 %, 8.2%, 33.2 %, 0% and 2.1% in 2019 respectively. Overall, there was an increase in built-up and vegetation decrease in water and barren areas and complete loss of marshland. Highest temperatures were recorded for marshland area in year 2000 and barren and built in year 2019. Transect profiles showed positive correlation between NDBI and LST and a negative correlation between NDVI and LST.

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