Impact of Urban Land Cover Types on Surface Temperature

2021 ◽  
Author(s):  
Marzie Naserikia ◽  
Melissa Hart ◽  
Negin Nazarian
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Climatic Conditions ◽  
Landsat 8 ◽  
Local Climate ◽  
Land Cover Types ◽  
Cooling Effects

<p>The conversion of natural land to built-up surfaces has been widely documented as the main determinant of warming across urban areas. However, uncertainties remain regarding which primary land cover variables control urban heat in different climatic conditions at a global scale. While there is a very little understanding of how the cooling effects of vegetation cover vary over different cities, there is a deep knowledge gap in realizing how other land covers (such as soil, water, and built-up areas) are associated with urban warming and how this relationship is varied in different background climates. Accordingly, using a high spatial resolution dataset, a global synthetic investigation is needed to find the underlying factors influencing intra-urban temperature variability in various climates. To address this shortcoming, this study focuses on exploring the relationship between land surface temperature and land cover in different cities (using Landsat 8 imagery) and aims to investigate the effects of these land cover types on thermal environments in different climatic backgrounds. Preliminary analysis shows that different land cover types have different roles in different climate classes due to their various surface characteristics and in particular, the performance of green spaces to reduce LST is highly dependent on its background climate. For example, the efficiency of vegetation cover to reduce urban surface warming in temperate and tropical climates is more than that in arid and semi-arid areas. In this climate class, since baren soil is the main contributor to the intensity of LST, increasing the area of a green space presents an effective method to mitigate the adverse effects of local warming. Our findings provide helpful information for future urban climate-sensitive planning oriented at mitigating local climate warming in cities.</p>

scholarly journals Land Surface Temperature Retrieval from LANDSAT-8 Thermal Infrared Sensor Data and Validation with Infrared Thermometer Camera

2018 ◽  
Vol 7 (4.20) ◽  
pp. 608 ◽  
Author(s):  
Muhammad Mejbel Salih ◽  
Oday Zakariya Jasim ◽  
Khalid I. Hassoon ◽  
Aysar Jameel Abdalkadhum
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Infrared Sensor ◽  
Infrared Thermometer ◽  
Ground Truth Data ◽  
Land Cover Types

This paper illustrates a proposed method for the retrieval of land surface temperature (LST) from the two thermal bands of the LANDSAT-8 data. LANDSAT-8, the latest satellite from Landsat series, launched on 11 February 2013, using LANDSAT-8 Operational Line Imager and Thermal Infrared Sensor (OLI & TIRS) satellite data. LANDSAT-8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12 bits. In this search a trial has been made to estimate LST over Al-Hashimiya district, south of Babylon province, middle of Iraq. Two dates images acquired on 2nd &18th of March 2018 to retrieve LST and compare them with ground truth data from infrared thermometer camera (all the measurements contacted with target by using type-k thermocouple) at the same time of images capture. The results showed that the rivers had a higher LST which is different to the other land cover types, of less than 3.47 C ◦, and the LST different for vegetation and residential area were less than 0.4 C ◦ with correlation coefficient of the two bands 10 and 11 Rbnad10= 0.70, Rband11 = 0.89 respectively, for the imaged acquired on the 2nd of march 2018 and Rband10= 0.70 and Rband11 = 0.72 on the 18th of march 2018. These results confirm that the proposed approach is effective for the retrieval of LST from the LANDSAT-8 Thermal bands, and the IR thermometer camera data which is an effective way to validate and improve the performance of LST retrieval. Generally the results show that the closer measurement taken from the scene center time, a better quality to classify the land cover. The purpose of this study is to assess the use of LANDSAT-8 data to specify temperature differences in land cover and compare the relationship between land surface temperature and land cover types.   

scholarly journals Impact of urban environment on land surface temperature in local climate zones

2021 ◽  
Vol 333 ◽  
pp. 02008
Author(s):  
Anna Gosteva ◽  
Sofia Ilina ◽  
Aleksandra Matuzko
Keyword(s):  
Surface Temperature ◽  
Urban Environment ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Landsat 8 ◽  
Local Climate ◽  
Spatial Coverage ◽  
Artificial Environment ◽  
Local Climate Zones

The replacement of the natural landscape by artificial environment has led to changes in the ecosystem and physical properties of the surface, such as heat storage capacity, and thermal conductivity properties. These changes increase the difficulty of heat transfer between urban areas and the environment. Land surface temperature (LST) images from various satellites are widely used to represent urban thermal environments, which are more convenient and intuitive way. LST maps provide full spatial coverage, which distinguishes them from air temperature data obtained from meteorological stations. The study of LST according to the Landsat 8 data of Krasnoyarsk city over the past 10 years allowed the authors to talk about the observation of constant seasonal urban heat islands (UHI). For a more detailed consideration of the urban environment, this study further considers urban landscapes, thus the idea of local climate zone (LCZ) is introduced to study these diverse impacts in addition to the traditional map of LST. And analysis of the interaction of UHI and LCZ.

scholarly journals Local Climate Zones and Thermal Characteristics in Riyadh City, Saudi Arabia

2021 ◽  
Vol 13 (22) ◽  
pp. 4526
Author(s):  
Ali S. Alghamdi ◽  
Ahmed Ibrahim Alzhrani ◽  
Humud Hadi Alanazi
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Thermal Characteristics ◽  
Arid Climate ◽  
Landsat 8 ◽  
Design Strategies ◽  
Local Climate ◽  
Riyadh City ◽  
Local Climate Zones

Using the local climate zone (LCZ) framework and multiple Earth observation input features, an LCZ classification was developed and established for Riyadh City in 2017. Four land-cover-type and four urban-type LCZs were identified in the city with an overall accuracy of 87%. The bare soil/sand (LCZ-F) class was found to be the largest LCZ class, which was within the nature of arid climate cities. Other land-cover LCZs had a lower coverage percentage (each class with <7%). The compact low-rise (LCZ-3) class was the largest urban type, as urban development in arid climate cities tends to extend horizontally. The daytime surface thermal characteristics of the developed LCZs were analyzed at seasonal timescales using land surface temperature (LST) estimated from multiple Landsat 8 satellite images (June 2017–May 2018). The highest daytime mean LST was found over large low-rise (LCZ-8) class areas throughout the year. This class was the only urban-type LCZ class that demonstrated a positive LST departure from the overall mean LST across seasons. Other urban-type LCZ classes showed lower LSTs and negative deviations from the overall mean LSTs. The overall thermal results suggested the presence of the surface urban heat island sink phenomenon as urban areas experienced lower LSTs than their surroundings. Thermal results demonstrated that the magnitudes of LST differences among LCZs were considerably dependent on the way the region of interest/analysis was defined. This was related to the types of LCZ classes presented in the study area and the spatial distribution and abundance of these LCZ classes. The developed LCZ classification and thermal results have several potential applications in different areas including planning and urban design strategies and urban health-related studies.

scholarly journals A COMPARATIVE STUDY OF LAND SURFACE TEMPERATURE WITH DIFFERENT INDICES ON HETEROGENEOUS LAND COVER USING LANDSAT 8 DATA

2018 ◽  
Vol XLII-5 ◽  
pp. 389-394 ◽  
Author(s):  
R. Bala ◽  
R. Prasad ◽  
V. P. Yadav ◽  
J. Sharma
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Sensor Data ◽  
Landsat 8 ◽  
Temperature Relation

<p><strong>Abstract.</strong> The temperature rise in urban areas has become a major environmental concern. Hence, the study of Land surface temperature (LST) in urban areas is important to understand the behaviour of different land covers on temperature. Relation of LST with different indices is required to study LST in urban areas using satellite data. The present study focuses on the relation of LST with the selected indices based on different land cover using Landsat 8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) data in Varanasi, India. A regression analysis was done between LST and Normalized Difference Vegetation index (NDVI), Normalized Difference Soil Index (NDSI), Normalized Difference Built-up Index (NDBI) and Normalized Difference Water Index (NDWI). The non-linear relations of LST with NDVI and NDWI were observed, whereas NDBI and NDSI were found to show positive linear relation with LST. The correlation of LST with NDSI was found better than NDBI. Further analysis was done by choosing 25 pure pixels from each land cover of water, vegetation, bare soil and urban areas to determine the behaviour of indices on LST for each land cover. The investigation shows that NDSI and NDBI can be effectively used for study of LST in urban areas. However, NDBI can explain urban LST in the better way for the regions without water body.</p>

scholarly journals Mapping Land Surface Temperature Developments in Functional Urban Areas across Europe

2021 ◽  
Vol 13 (11) ◽  
pp. 2111
Author(s):  
Anna Hellings ◽  
Andreas Rienow
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat ◽  
Cooling Effects ◽  
Development Paths

Unsustainable development paths have reached critical levels in Europe. In recent years, in cities, urbanization has been contributing to the intensification of urban heat islands. To analyze the development of surface urban heat islands (SUHI) in Europe in the last few years, the present study combines the land surface temperature (LST) from MODIS with the urban classes of the CORINE land cover data within 617 functional urban areas (FUAs). Urban and industrial uses have significantly higher LST than green urban areas across all years (about 4 to 6 °C), as do agricultural areas within cities. Besides land cover, location also influences LST differences. While, e.g., Bolzano (Italy) shows particularly large LST differences (>6 °C) between the core and the commuting zone, this effect is hardly visible in Porto (Portugal) and Madrid (Spain) (<2.5 °C). Cities of moderate climates show increasing differences between a city and its commuting zones with rising LST (r = 0.68), i.e., less cooling effects at night.

scholarly journals Spatial Distribution of Surface Temperature and Land Cover: A Study Concerning Sardinia, Italy

2020 ◽  
Vol 12 (8) ◽  
pp. 3186 ◽  
Author(s):  
Sabrina Lai ◽  
Federica Leone ◽  
Corrado Zoppi
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Spatial Data ◽  
Land Surface ◽  
Urban Areas ◽  
Regional Scale ◽  
Landsat 8 ◽  
Policy Recommendations ◽  
Mediterranean Shrubs ◽  
Land Covers

Land surface temperature (LST) is a key climate variable that has been studied mainly at the urban scale and in the context of urban heat islands. By analyzing the connection between LST and land cover, this study shows the potential of LST to analyze the relation between urbanization and heating phenomena at the regional level. Land cover data, drawn from Copernicus, and LST, retrieved from Landsat 8 satellite images, are analyzed through a methodology that couples GIS and regression analysis. By looking at the Italian island of Sardinia as a case study, this research shows that urbanization and the spatial dynamics of heating phenomena are closely connected, and that intensively farmed areas behave quite similarly to urban areas, whereas forests are the most effective land covers in mitigating LST, followed by areas covered with Mediterranean shrubs. This leads to key policy recommendations that decision-makers could implement to mitigate LST at the regional scale and that can, in principle, be exported to regions with similar climate and land covers. The significance of this study can be summed up in its novel approach to analyzing the relationship between LST and land covers that uses freely available spatial data and, therefore, can easily be replicated in other regional contexts to derive appropriate policy recommendations.

scholarly journals Land Surface Temperature Retrieval from LANDSAT-8 Ther-mal Infrared Sensor Data and Validation with Infrared Ther-mometer Camera

2018 ◽  
Vol 7 (4.20) ◽  
pp. 601
Author(s):  
Muhammad Mejbel Salih ◽  
Oday Zakariya Jasim ◽  
Khalid I. Hassoon ◽  
Aysar Jameel Abdalkadhum
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Ground Truth ◽  
Sensor Data ◽  
Landsat 8 ◽  
Infrared Sensor ◽  
Ground Truth Data ◽  
Land Cover Types

This paper illustrates a proposed method for the retrieval of land surface temperature (LST) from the two thermal bands of the LAND-SAT-8 data. LANDSAT-8, the latest satellite from Landsat series, launched on 11 February 2013, using LANDSAT-8 Operational Line Imager and Thermal Infrared Sensor (OLI & TIRS) satellite data. LANDSAT-8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12 bits. In this search a trial has been made to estimate LST over Al-Hashimiya district, south of Babylon province, middle of Iraq. Two dates images acquired on 2nd &18th of March 2018 to retrieve LST and compare them with ground truth data from infrared thermometer camera (all the meas-urements contacted with target by using type-k thermocouple) at the same time of images capture. The results showed that the rivers had a higher LST which is different to the other land cover types, of less than 3.47 C ◦, and the LST different for vegetation and residential area were less than 0.4 C ◦ with correlation coefficient of the two bands 10 and 11 Rbnad10= 0.70, Rband11 = 0.89 respectively, for the im-aged acquired on the 2nd of march 2018 and Rband10= 0.70 and Rband11 = 0.72 on the 18th of march 2018. These results confirm that the proposed approach is effective for the retrieval of LST from the LANDSAT-8 Thermal bands, and the IR thermometer camera data which is an effective way to validate and improve the performance of LST retrieval. Generally the results show that the closer measure-ment taken from the scene center time, a better quality to classify the land cover. The purpose of this study is to assess the use of LAND-SAT-8 data to specify temperature differences in land cover and compare the relationship between land surface temperature and land cover types.

scholarly journals THE GEO-SPATIAL APPROACH TO DETECT THE CHANGE IN VEGETATION AND LAND SURFACE TEMPERATURE (LST) AFTER FORMATION OF ROHINGYA SETTLEMENTS IN BANGLADESH

2021 ◽  
Vol 12 (2) ◽  
pp. 288-241
Author(s):  
Mahdi Mansur Mahi ◽  
Md. Shahriar Sharif ◽  
Rhyme Rubayet Rudra ◽  
Md. Nazmul Haque
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Vegetation Density ◽  
Tree Plantation

The goal of this study is to examine the effects of Rohingya Influx specially on vegetation land cover and LST in Teknaf Peninsula, Cox’s Bazar, Bangladesh over time. For doing so, the research followed three steps. Firstly, the primary and secondary data were collected from prescribed sources like LANDSAT 8 images from Earth Explorer (USGS) and the Shapefiles were collected from secondary sources. Then, Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) functions are explored in geospatial environment to assess the effect of deforestation on the region. Finally, A correlation is shown between LST and NDVI for making a decision from the environmental perspective. The findings state that, the region around the Rohingya Camps progressively lost its vegetation density as a result of increasing deforestation. According to this analysis, there was 87.87 % vegetation cover in 2013, which gradually decreased before the Rohingya Invasion in 2017. After the incident in 2018, vegetation cover drops to 75.67 %. Similarly, area with no vegetation increased more rapidly than others. The outcome showed that the transition in land cover was quicker and more noticeable in recent time. As a result, the LST has been increasing over the years. According to the study, there were around 8.71 % of areas with high temperatures in 2013, which increased to 36.86 % in 2020. It indicates that a large quantity of vegetation has been lost as a result of deforestation, and the LST of this region has changed dramatically. Furthermore, data was examined by Union to assess the individual effect from 5 Rohingya camps, and it was discovered that the situation in Teknaf Union is terrible, while the situation in Baharchhara Union is comparably better. Finally, the results of the research encourage an extensive regional environmental policy to eradicate this problem. To recompense the loss of nature govt. and responsible department should take necessary steps like hill conservation or tree plantation.

scholarly journals Developing land-cover driver model for estimating the intensity of surface urban heat islands using landsat 8 satellite imagery

2019 ◽  
Vol 41 (3) ◽  
pp. 201-215 ◽  
Author(s):  
Nguyen Thanh Hoan ◽  
Nguyen Van Dung ◽  
Ho Le Thu ◽  
Hoa Thuy Quynh
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Landsat 8 ◽  
Moving Window ◽  
Land Cover Types ◽  
Heat Islands ◽  
Urban Heat

It is of utmost importance to understand and monitor the impact of urban heat islands on ecosystems and overall human health in the context of climate change and global warming. This research was conducted in a tropical city, Hanoi, with a major objective of assessing the quantitative relationships between the composition of the main land-cover types and surface urban heat island phenomenon. In this research, we analyzed the correlation between land-cover composition, percentage coverage of the land cover types, and land surface temperature for different moving window sizes or urban land management units. Landsat 8 OLI (Operational Land Imager) satellite data was utilized for preparing land-cover composition datasets in inner Hanoi by employing the unsupervised image clustering method. High-resolution (30m) land surface temperature maps were generated for different days of the years 2016 and 2017 using Landsat 8 TIRS (Thermal Infrared Sensor) images. High correlations were observed between percentage coverage of the land-cover types and land surface temperature considering different window sizes. A new model for estimating the intensity of surface urban heat islands from Landsat 8 imagery is developed, through recursively analyzing the correlation between land-cover composition and land surface temperature at different moving window sizes. This land-cover composition-driven model could predict land surface temperature efficiently not only in the case of different window sizes but also on different days. The newly developed model in this research provides a wonderful opportunity for urban planners and designers to take measures for adjusting land surface temperature and the associated effects of surface urban heat islands by managing the land cover composition and percentage coverage of the individual land-cover types.

scholarly journals Land Use/Land Cover Change With Impact On Land Surface Temperature: A Case Study Of Mkda Planning Area, West Bengal, India

2020 ◽  
Vol 13 (4) ◽  
pp. 43-53
Author(s):  
Samrin Fatema ◽  
Dr. Abhisek Chakrabarty
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Landsat 8 ◽  
Hard Material ◽  
Local Climate ◽  
Landsat 7 ◽  
Multi Temporal

The type of surface influences the temperature of a surface. If it is made of concrete or another hard material, the temperature will be higher. Hence it is essential to study the land surface temperature (LST) of urban areas. The LST is an important parameter in the estimation of radiation budgets and heat balance and is a controlling factor of dynamic climate changes. In this work, we made an effort to identify the LST of the Midnapore Kharagpur Development Authority planning region. Multi-temporal images acquired by Landsat 7 ETM+, Landsat 5 TM and Landsat 8 using OLI sensors on 3 May 2001, 7 May 2011 and 29 May 2019, respectively, were corrected for radiometric and geometric errors and processed to extract LULC classes and LST. Thermal remote sensing can be used to monitor the temperature and local climate of urban areas. This study has shown that the temperature varies across the surface according to land use. It was found that the urbanized area increased from 6.79% (40.39 sq. km) to 11.6% (69.2 sq. km) between 2001 and 2011 and from 11.6% (69.2 sq. km) to 17.22 % (102.79 sq. km) between 2011 and 2019. The LST study has shown that there has been a tremendous change in the spatial pattern of the temperature between 2001 and 2019. Whereas in 2001 the highest temperature did not exceed 34°C, by 2019 it had increased by nearly 8°C, reaching 41.29°C. So, the findings of this study are significant.

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