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Conference on Atmospheric and Environmental Remote Sensing Data Processing and Utilization VI - Readiness for GEOSS IV

作者： Guo Jianmao Li, Xujie Zhu, Bin Zhou Yexian CMA Inst Plateau Meteoril Chengdu 610071 Peoples R China Nanjing Univ Informat Sci & Technol Nanjing 210044 Jiangsu Peoples R China

ISBN: (纸本)9780819483072

The land surface temperature is an important parameter to hydrology and meteorology, it affects the exchange of sensible and latent heats between atmosphere, sea and land, and it can not be lack in many research fields. To retrieve land surface temperature exactly and quantificationally will promote the development of research areas such as drought forecasting crop yield estimating numerical weather forecast, global climate change and carbon balance. Therefore, retrieval of land surface temperature using thermal infrared remote sensing becomes one of the most important tasks in quantificational remote sensing study. The TM images are used in this article, which were recorded in June 11, 2001 over Nakchu area in Tibetan Plateau, to calculate the land surface temperature. The natural surface is classified based on information of remote sensing (snow, water and other land surface) and relevant information of geography, then the emissivity can be dealt with by each surface type in different way. Last, the land surface temperature is inversed by mono-window algorithm. The result show that the derived regional distributions of the the land surface temperature for the whole mesoscale area is agreed with the land surface status very well.

关键词： landsat TM thermal band land surface temperature mono-window algorithm land surface emissivity

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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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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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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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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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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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Evaluation of spatio-temporal variability in Land Surface Temperature: A case study of Zonguldak, Turkey

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2016年第1期188卷 30-30页

作者： Sekertekin, Aliihsan Kutoglu, Senol Hakan Kaya, Sinasi Bulent Ecevit Univ Dept Geomat Engn Fac Engn TR-67100 Zonguldak Turkey Cukurova Univ Dept Geomat Engn Ceyhan Engn Fac TR-01330 Adana Turkey Istanbul Tech Univ Dept Geomat Engn TR-34469 Istanbul Turkey

The aim of this study is to analyze spatiotemporal variability in Land Surface Temperature (LST) in and around the city of Zonguldak as a result of the growing urbanization and industrialization during the last decade. Three Landsat 5 data and one Landsat 8 data acquired on different dates were exploited in acquiring LST maps utilizing mono-window algorithm. The outcomes obtained from this study indicate that there exists a significant temperature rise in the region for the time period between 1986 and 2015. Some cross sections were selected in order to examine the relationship between the land use and LST changes in more detail. The mean LST difference between 1986 and 2015 in ERDEMIR iron and steel plant (6.8 degrees C), forestland (3 degrees C), city and town centers (4.2 degrees C), municipal rubbish tip (-3.9 degrees C), coal dump site (12.2 degrees C), and power plants' region (7 degrees C) were presented. In addition, the results indicated that the mean LST difference be-tween forestland and city centers was approximately 5 degrees C, and the difference between forestland and industrial enterprises was almost 8 degrees C for all years. Spatiotemporal variability in LST in Zonguldak was examined in that study and due to the increase in LST, policy makers and urban planners should consider LST and urban heat island parameters for sustainable development.

关键词： Land Surface Temperature (LST) Landsat mono-window algorithm Spatio-temporal variability Zonguldak

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Comparison of Three algorithms for the Retrieval of Land Surface Temperature from Landsat 8 Images

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SENSORS 2019年第22期19卷 5049-5049页

作者： Wang, Lei Lu, Yao Yao, Yunlong Northeast Forestry Univ Coll Wildlife Resources Harbin 150040 Heilongjiang Peoples R China Key Lab Garden Plant Germplasm Dev & Landscape Ec Harbin 150040 Heilongjiang Peoples R China Heilongjiang Univ Sci & Technol Coll Architectural Engn Harbin 150022 Heilongjiang Peoples R China

The successful launch of the Landsat 8 satellite provides important data for the monitoring of urban heat island effects. Since the Landsat 8 TIRS data has two thermal infrared bands, it is suitable for many algorithms to retrieve the land surface temperature (LST). However, the selection of algorithms for retrieving the LST, the acquisition of algorithm input parameters, and the verification of the results are problems without obvious solutions. Taking Changchun City as an example, this paper used the mono-window algorithm (MWA), the split window algorithm (SWA), and the single-channel (SC) method to extract the LST from the Landsat 8 image and compared the three algorithms in terms of input parameters, accuracy, and sensitivity. The results show that all three algorithms can achieve good results in retrieving the LST. The SWA is the least sensitive to the error of the input parameters. The MWA and the SC method are sensitive to the error of the input parameters, and compared with the error of the LSE, these two algorithms are more sensitive to the error of atmospheric water vapor content. In addition, the MWA is also very sensitive to the error of the effective mean atmospheric temperature.

关键词： Landsat 8 TIR data land surface temperature mono-window algorithm split window algorithm single-channel method sensitivity analysis

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