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Assessing Local Climate Change by Spatiotemporal Seasonal LST and Six Land Indices, and Their Interrelationships with SUHI and Hot-Spot Dynamics: A Case Study of Prayagraj City, India (1987-2018)

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REMOTE SENSING 2023年第1期15卷 179-179页

作者： Sarif, Md. Omar Gupta, Rajan Dev Murayama, Yuji Lovely Profess Univ Dept Geog Phagwara 144411 India Motilal Nehru Natl Inst Technol Allahabad Civil Engn Dept Prayagraj 211004 India Univ Tsukuba Fac Life & Environm Sci 1-1-1 Tennodai Tsukuba Ibaraki 3058572 Japan

LST has been fluctuating more quickly, resulting in the degradation of the climate and human life on a local-global scale. The main aim of this study is to examine SUHI formation and hotspot identification over Prayagraj city of India using seasonal Landsat imageries of 1987-2018. The interrelationship between six land indices (NDBI, EBBI, NDMI, NDVI, NDWI, and SAVI) and LST (using a mono-window algorithm) was investigated by analyzing correlation coefficients and directional profiling. NDVI dynamics showed that the forested area observed lower LST by 2.25-4.8 degrees C than the rest of the city landscape. NDBI dynamics showed that the built-up area kept higher LST by 1.8-3.9 degrees C than the rest of the city landscape (except sand/bare soils). SUHI was intensified in the city center to rural/suburban sites by 0.398-4.016 degrees C in summer and 0.45-2.24 degrees C in winter. Getis-Ord G(i)* statistics indicated a remarkable loss of areal coverage of very cold, cold, and cool classes in summer and winter. MODIS night-time LST data showed strong SUHI formation at night in summer and winter. This study is expected to assist in unfolding the composition of the landscape for mitigating thermal anomalies and restoring environmental viability.

关键词： LST mono-window algorithm land indices correlation coefficients directional profiling SUHI hotspots (Getis-Ord G(i)* statistics) MODIS night-time LST Prayagraj city

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Cross-Comparison between Sun-Synchronized and Geostationary Satellite-Derived Land Surface Temperature: A Case Study in Hong Kong

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REMOTE SENSING 2022年第18期14卷 4444-4444页

作者： Adeniran, Ibrahim Ademola Zhu, Rui Yang, Jinxin Zhu, Xiaolin Wong, Man Sing Hong Kong Polytech Univ Dept Land Surveying & Geoinformat Hong Kong Peoples R China Guangzhou Univ Sch Geog & Remote Sensing Guangzhou 510006 Peoples R China

Harmonization of satellite imagery provides a good opportunity for studying land surface temperature (LST) as well as the urban heat island effect. However, it is challenging to use the harmonized data for the study of LST due to the systematic bias between the LSTs from different satellites, which is highly influenced by sensor differences and the compatibility of LST retrieval algorithms. To fill this research gap, this study proposes the comparison of different LST images retrieved from various satellites that focus on Hong Kong, China, by applying diverse retrieval algorithms. LST images generated from Landsat-8 using the mono-window algorithm (MWA(L8)) and split-window algorithm (SWA(L8)) would be compared with the LST estimations from Sentinel-3 SLSTR and Himawari-8 using the split-window algorithm (SWA(S3) and SWA(H8)). Intercomparison will also be performed through segregated groups of different land use classes both during the daytime and nighttime. Results indicate that there is a significant difference among the quantitative distribution of the LST data generated from these three satellites, with average bias of up to -1.80 K when SWA(H8) was compared with MWA(L8), despite having similar spatial patterns of the LST images. The findings also suggest that retrieval algorithms and the dominant land use class in the study area would affect the accuracy of image-fusion techniques. The results from the day and nighttime comparisons revealed that there is a significant difference between day and nighttime LSTs, with nighttime LSTs from different satellite sensors more consistent than the daytime LSTs. This emphasizes the need to incorporate as much night-time LST data as available when predicting or optimizing fine-scale LSTs in the nighttime, so as to minimize the bias. The framework designed by this study will serve as a guideline towards efficient spatial optimization and harmonized use of LSTs when utilizing different satellite images associated with an arra

关键词： land surface temperature mono-window algorithm split-window algorithm Landsat-8 Himawari-8

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Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018

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REMOTE SENSING 2020年第13期12卷 2105-2105页

作者： Liao, Haijun Liu, Qiao Zhong, Yan Lu, Xuyang Chinese Acad Sci Inst Mt Hazards & Environm Chengdu 610041 Peoples R China Univ Chinese Acad Sci Coll Resources & Environm Beijing 100049 Peoples R China

Glacier surface temperature (GST) is influenced by both the energy flux from the atmosphere above and the thermal dynamics at the ice-water-debris interfaces. However, previous studies on GST are inadequate in time series research and mountain glacier surface temperature retrieval. We evaluate the GST variability at Hailuogou glacier, a temperate glacier located in Southeastern Tibetan Plateau, from 1990 to 2018. We utilized a modified mono-window algorithm to calculate the GST using the Landsat 8 thermal infrared sensor (TIRS) band 10 data and Landsat 5 thematic mapper (TM) band 6 data. Three essential parameters, including the emissivity of ice and snow, atmospheric transmittance, and effective mean atmospheric temperature, were employed in the GST algorithm. The remotely-sensed temperatures were compared with two other single-channel algorithms to validate GST algorithm's accuracy. Results from different algorithms showed a good agreement, with a mean difference of about 0.6 celcius. Our results showed that the GST of the Hailuogou glacier, both in the upper debris-free part and the lower debris-covered tongue, has experienced a slightly increasing trend at a rate of 0.054 celcius a(-1)during the past decades. Atmospheric warming, expanding debris cover in the lower part, and a darkening debris-free accumulation area are the main causes of the warming of the glacier surface.

关键词： glacier surface temperature (GST) remote sensing mono-window algorithm glacier change debris-covered glaciers

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Assessment of spatio-temporal changes in land use and land cover, urban sprawl, and land surface temperature in and around Vijayawada city, India

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ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY 2020年第4期22卷 3079-3095页

作者： Vani, M. Prasad, P. Rama Chandra Int Inst Informat Technol Hyderabad Lab Spatial Informat Hyderabad 500032 Telangana India

The urban agglomeration is the unplanned growth of a city into its surrounding peri/rural areas causing unsustainable exploitation of natural resources. This leads to an increase in the land surface temperature that in turn results in climatic issues ranging from local to global scales. In the current study, an attempt has been made to map the urban growth and its associated land surface temperature variations in and around Vijayawada city of Andhra Pradesh state, India. Temporal Landsat satellite images from 4 years, viz. 1990, 2000, 2010, and 2018, were used to generate land use/land cover maps with four major classes such as built-up, vegetation, water body, and others. Change detection and transition of the natural land cover to man-made land use were statistically computed for the study area. Sprawl analysis of the city was carried out by generating multiple buffer rings over the study region to evaluate the urban density and annual urban growth rate. Shannon's entropy was employed to identify the nature of city expansion. The seasonal variation of the land surface temperature was studied using mono-window algorithm. The temperature variation over individual classes was computed with the aid of a self-designed random point method. Results showed a steady increasing trend in the urban density and land surface temperature with the distinct formation of a heat island over the city, especially during winters throughout the study period. The settlement area has increased from 28.20 km(2) in 1990 to 138.01 km(2) in 2018. The directional growth analysis captured the pattern of city growth as tentacle-type development in conjunction with infill development. The sprawl happening around Vijayawada ignores the depletion of natural resources, leading to anomalies in the land surface temperature.

关键词： Sprawl pattern Change detection Entropy Growth metric mono-window algorithm

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Relationship between land surface temperature and urbanization in Vilnius district

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2021年第8期193卷 472-472页

作者： Mirsanjari, Mir Mehrdad Mohammadyari, Fatemeh Visockiene, Jurate Suziedelyte Zarandian, Ardavan Malayer Univ Dept Environm Sci Malayer Iran Malayer Univ Fac Nat Resources Malayer Iran Vilnius Gediminas Tech Univ Dept Geodesy & Cadaster Sauletekio Av 11 LT-10223 Vilnius Lithuania Res Ctr Environm & Sustainable Dev RCESD Dept Environm Tehran Iran

The present study aims to evaluate the effect of vegetation on land surface temperature (LST) in different land uses and covers in Vilnius district in 1999 and 2019. To that end, in addition to mono-window and split-window algorithms that help estimate the LST, the variables digital elevation model (DEM), slope, heat load index (HLI), distances from the road and the water, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI) affecting the surface temperature were used. Furthermore, the random forest regression (RFR) method was applied to evaluate the effect of the mentioned variables on the LST. The performance model was also assessed by using the mean absolute (MAE), mean squared (MSE), and root mean square error (RMSE). Based on the results, NDVI and NDWI indexes had the greatest impact on the temperature of Vilnius city, respectively. The study area images were categorized as built-up area, cropland, semi-forest land, dense forest land, water bodies, pastures, and green urban areas. It was found that the pastures in 1999 and the built-up class in 2019 received the highest temperature from the land surface and that the classes characterized by natural land cover such as forest land and agricultural and water bodies had a relatively low surface temperature. NDVI response curves in both 1999 and 2019 indicated that the higher the density of vegetation on the land surface, the lower the surface temperature. A lower rate of urbanization, a higher density of vegetation and consequently, a lower the temperature of the land surface were recorded for 1999 in comparison with 2019. Therefore, urbanization was demonstrated to play a significant role in changes in LULC and the increase in LST.

关键词： Land surface temperature Split-window algorithm mono-window algorithm Random forest regression NDVI Land use

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Cool island effects of urban remnant natural mountains for cooling communities: A case study of Guiyang, China

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SUSTAINABLE CITIES AND SOCIETY 2021年 71卷 102983-102983页

作者： Chen, Xintong Wang, Zhitai Bao, Yu Guizhou Univ Coll Forestry Guiyang 550025 Guizhou Peoples R China

With the rapid development of urbanization, abundant cone-shaped or tower-shaped karst peaks and peak forests were surrounded by human-dominated urban matrix, forming urban remnant natural mountains (URNMs). URNMs, as the precious ecological resources, could provide a variety of ecosystem services in cities. In order to explore the cool island effects of URNMs, taking the built-up area of the Guiyang city center as the study area and the URNMs as the research object, the cool island effects of URNMs and factors that influence their cooling amplitudes were analyzed through a land surface temperature (LST) inversion with the mono-window algorithm and buffer, correlation and regression analyses. Results showed that : (1) URNMs were the main contributing source to LST reduction, which had cool island effects on their surrounding communities, (2) the average cooling distance was approximately 170 m, and the cooling range was 0.2-2.5 degrees C, (3) the landscape structure and patch density of the surrounding buffer matrix had a significant influence on mountain cool island (MCI) intensity in the range of 330 m. Results of this study could provide guidance for urban planners and policy makers to protect and manage URNMs and improve urban community spatial planning to alleviate urban heat island effect.

关键词： Urban remnant natural mountains mono-window algorithm Cool island effect Mountainous

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EFFECTS OF CLOUD ON LAND SURFACE TEMPERATURE (LST) CHANGE IN THERMAL INFRARED REMOTE SENSING IMAGES: A CASE STUDY OF LANDSAT 8 DATA

EFFECTS OF CLOUD ON LAND SURFACE TEMPERATURE (LST) CHANGE IN...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Abbasi, Bilawal Qin, Zhihao Du, Wenhui Li, Shifeng Fan, Jinlong Zhao, Shuhe Chinese Acad Agr Sci Inst Agroresources & Reg Planning MOA Key Lab Agr Remote Sensing Beijing 100081 Peoples R China Natl Satellite Meteorol Ctr Beijing 100081 Peoples R China Nanjing Univ Sch Geog & Oceanog Sci Nanjing 210023 Peoples R China

ISBN: (纸本)9781728163741

Clouds exert a great influence on land surface temperature (LST). It remains unclear how clouds affect the LST change in satellite images. The focus of the study is to examine the effects of cloud on LST change in Landsat 8 images over various ground surface types, cloud sizes and seasonal scales. The difference between solar and satellite geometry over the images provides the possible way to identify the impact of cloud in Landsat 8 images. The shadow of cloud represents the true effects of cloud on LST change. Using the available mono-window algorithm, we were able to retrieve the L ST of the shadow for the analysis of the cloud effects. Four typical ground surfaces were selected for the analysis: desert/bare surface, vegetation, urban and water covered area. The L ST difference between the shadow and its nearby clear-sky region represents the effects of cloud on L ST change in the corresponding ground surface. The results indicated that the, highest L ST difference was observed over dessert/barren land in the magnitude of 8.28 degrees C. Moreover, when the cloud size relatively smaller or larger the effect on LST slightly varies. The summer season has the most remarkable effect of cloud on LST change. The water surface has the lowest LST difference in overall cloud analysis. These change of LST under cloud in various conditions can be helpful for the studies which are focus on LST estimation during cloudy conditions.

关键词： Land surface temperature Cloud Landsat 8 data mono-window algorithm

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Analysis of Urban Green Spaces and Surface Temperature Using Quantitative Remote Sensing Technology in Bangkok 5

Analysis of Urban Green Spaces and Surface Temperature Using...

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Conference on Remote Sensing Technologies and Applications in Urban Environments V held at SPIE Remote Sensing Conference

作者： Itiritipha, Fareda Wu, Falin Gantumur, Byambakhuu Lkhagva, Otgonbayar Beihang Univ Sch Instrumentat & Optoelect Engn SNARS Lab Beijing 100191 Peoples R China Natl Univ Mongolia Sch Arts & Sci Dept Geog Ulan Bator 14200 Mongolia

ISBN: (数字)9781510638846

ISBN: (纸本)9781510638846;9781510638839

Bangkok Metropolitan Administration (BMA) is the capital city of Thailand In recent years, city surface has been changed greatly by rapid urbanization. Many green spaces in the urban area are destroyed and replaced with the commercial area. It can have effect on the climate and weather that could lead to the Urban Heat Island (UHI). This research analyzes the correlation between Urban Green Spaces (UGS) and Land Surface Temperature (LST) using quantitative remote sensing technology in BMA. More than five years of Landsat-5 TM and Landsat-8 images are used to study urban temperature. The LST, UGS and their correlation of whole area of BMA are analyzed. The LST is retrieved from mono-window algorithm, which used only one thermal band. Several indices of UGS, including the Normalized Difference Vegetation Index (NDVI), and measurement of vegetation cover percentage are also used to study on UGS. The result showed that from 2008 to 2018 LST is increased while UGS is decreased. In addition, Pearson product-moment correlation coefficient is used to analyze the linear correlation between UGS and LST. The correlation between LST and NDVI indicates the negative correlation. The average correlation coefficient is -0.44. That can imply that the higher vegetated area, the LST was lower. To get more detail relationship between LST and UGS, three typical regional areas are selected to study. LST contour is used to analyze LST and HERCULES system is used to classify land cover. The result showed that firstly, the density of tree affect LST. Secondly, the location of the public park is important. Thirdly, water bodies help to decrease LST. The results of this study have key implications for BMA sustainable urban planning and development;to mitigate UHI effects it is important to not only increase canopy cover or the size of UGS, but also to optimize their spatial configuration.

关键词： Urban Green Spaces Urban Heat Island Land Surface Temperature mono-window algorithm TM images

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Evaluating the spatial distribution and the intensity of urban heat island using remote sensing, case study of Isfahan city in Iran

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SUSTAINABLE CITIES AND SOCIETY 2019年 45卷 686-692页

作者： Shirani-Bidabadi, Niloufar Nasrabadi, Touraj Faryadi, Shahrzad Larijani, Adnan Roodposhti, Majid Shadman Univ Alabama Civil & Environm Engn 01 Sparkman Dr Huntsville AL 35899 USA Univ Tehran Coll Engn Sch Environm Tehran Iran Isfahan Univ Technol Dept Min Esfahan Iran Univ Tasmania Sch Technol Environm & Design Discipline Geog & Spatial Sci Churchill Ave Hobart Tas 7005 Australia

In recent years, urbanization has widely been developed and resulted in great loss of natural resources on earth and many other consequences such as temperature rise which exposes the cities to a phenomenon called heat island. Urban heat island (UHI) can be identified and analyzed by thermal remote sensing. In the present study, satellite images of Landsat 7 ETM + (1999 and 2006) and Landsat 8 (2013 and 2016) were used to retrieve the land surface temperature (LST) of Isfahan in Iran by means of the mono-window algorithm. Analysis of thermal levels showed an increase in the minimum temperature of 2016 compared to 1999. Furthermore, the results revealed that the heat island ratio (URI) in Isfahan in four different years followed a rising trend, moving from 0.16 in 1999 to 0.3 in 2016. The findings of this study indicated that the areas influenced by UHI are often in northern and southern parts of the city where vegetation cover is very sparse, the land is arid, and industrialization and regional settlements are booming.

关键词： Urban heat island Remote sensing mono-window algorithm Land surface temperature Isfahan

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Characterization of thermal environment over heterogeneous surface of National Capital Region (NCR), India using LANDSAT-8 sensor for regional planning studies

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URBAN CLIMATE 2018年 24卷 1-18页

作者： Hoang Thi Hang Rahman, Atiqur Jamia Millia Islamia Dept Geog New Delhi India

Land surface temperature (LST) is an essential indicator of the Earth's surface energy budget. It is essential for urban micro-climate change studies and acts as a controlling variable in climatic models. The present study, LST retrieves with the improved mono-window algorithm from the Landsat-8 Thermal Infrared Sensor Band 10. The proportion of vegetation cover coupled with Normalized Difference Vegetation Index (NDVI) used for the estimation of emissivity. The derived emissivity and surface temperature over different ground features have compared with field observation as well as those in the literature and found in an accepted range (error of around 1-2%). Herein, results show that the spatial distribution of surface temperature was significantly affected by landscape characteristics. The built-up and commercial/industrial areas display higher surface temperature in comparison with surrounding other vegetated lands. Whereas, the cooling effect towards the surrounding urban built-up area are found increasing in the vegetated area, and inside the green zones. A strong correlation is observed between the LST with NDVI over different land cover and land use (LCLU) classes. The Geoinformation technique provides a practical-based theoretical model of the land characterization of an urban thermal environment which assists in regional planning and decision-making process.

关键词： Land surface temperature Emissivity Landsat 8 mono-window algorithm NDVI NCR-India

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