scholarly journals Downscale MODIS Land Surface Temperature Based on Three Different Models to Analyze Surface Urban Heat Island: A Case Study of Hangzhou

2020 ◽  
Vol 12 (13) ◽  
pp. 2134 ◽  
Author(s):  
Rui Wang ◽  
Weijun Gao ◽  
Wangchongyu Peng
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landsat 8 ◽  
Heat Island ◽  
Time Dimension ◽  
Urban Heat ◽  
Surface Urban Heat Island

Remote sensing technology plays an increasingly important role in land surface temperature (LST) research. However, various remote sensing data have spatial–temporal scales contradictions. In order to address this problem in LST research, the current study downscaled LST based on three different models (multiple linear regression (MLR), thermal sharpen (TsHARP) and random forest (RF)) from 1 km to 100 m to analyze surface urban heat island (SUHI) in daytime (10:30 a.m.) and nighttime (10:30 p.m.) of four seasons, based on Moderate Resolution Imaging Spectroradiometer (MODIS)/LST products and Landsat 8 Operational Land Imager (OLI). This research used an area (25 × 25 km) of Hangzhou with high spatial heterogeneity as the study area. R2 and RMSE were introduced to evaluate the conversion accuracy. Finally, we compared with similarly retrieved LST to verify the feasibility of the method. The results indicated the following. (1) The RF model was the most suitable to downscale MODIS/LST. The MLR model and the TsHARP model were not applicable for downscaling studies in highly heterogeneous regions. (2) From the time dimension, the prediction precision in summer and winter was clearly higher than that in spring and autumn, and that at night was generally higher than during the day. (3) The SUHI range at night was smaller than that during the day, and was mainly concentrated in the urban center. The SUHI of the research region was strongest in autumn and weakest in winter. (4) The validation results of the error distribution histogram indicated that the MODIS/LST downscaling method based on the RF model is feasible in highly heterogeneous regions.

scholarly journals A Methodology for Comparing the Surface Urban Heat Island in Selected Urban Agglomerations Around the World from Sentinel-3 SLSTR Data

2020 ◽  
Vol 12 (12) ◽  
pp. 2052 ◽  
Author(s):  
José Antonio Sobrino ◽  
Itziar Irakulis
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Urban Area ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Heat Island ◽  
Urban Agglomerations ◽  
The World ◽  
Urban Heat ◽  
Surface Urban Heat Island

Retrieval of land surface temperature (LST) from satellite data allows to estimate the surface urban heat island (SUHI) as the difference between the LST obtained in the urban area and the LST of its surroundings. However, this definition depends on the selection of the urban and surroundings references, which translates into greater difficulty in comparing SUHI values in different urban agglomerations across the world. In order to avoid this problem, a methodology is proposed that allows reliable quantification of the SUHI. The urban reference is obtained from the European Space Agency Climate Change Initiative Land Cover and three surroundings references are considered; that is, the urban adjacent (Su), the future adjacent (Sf), and the peri-urban (Sp), which are obtained from mathematical expressions that depend exclusively on the urban area. In addition, two formulations of SUHI are considered: SUHIMAX and SUHIMEAN, which evaluate the maximum and average SUHI of the urban area for each of the three surrounding references. As the urban population growth phenomenon is a world-scale problem, this methodology has been applied to 71 urban agglomerations around the world using LST data obtained from the sea and land surface temperature radiometer (SLSTR) on board Sentinel-3A. The results show average values of SUHIMEAN of (1.8 ± 0.9) °C, (2.6 ± 1.3) °C, and (3.1 ± 1.7) °C for Su, Sf, and Sp, respectively, and an average difference between SUHIMAX and SUHIMEAN of (3.1 ± 1.1) °C. To complete the study, two additional indices have been considered: the Urban Thermal Field Variation Index (UFTVI) and the Discomfort Index (DI), which proved to be essential for understanding the SUHI phenomenon and its consequences on the quality of life of the inhabitants.

scholarly journals Identifikasi Urban Heat Island di Kota Solok menggunakan Algoritma Landsat-8 OLI Landsurface Temperature

2018 ◽  
Vol 19 (1) ◽  
pp. 31
Author(s):  
Adenan Yandra Nofrizal
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landsat 8 ◽  
Heat Island ◽  
Landsat 8 Oli ◽  
Urban Heat

Pembangunan yang terjadi di Kota Solok akan menyebabkan terjadinya perubahan penggunaan lahan. Perubahan penggunaan lahan yang terjadi dengan meningkatnya lahan terbangun akan menyebabkan naiknya suhu permukaan (surface temperature) yang dapat menyebabkan terjadinya urban heat island. Penelitian ini bertujuan untuk mengetahui suhu permukaan yang ada di Kota Solok dan daerah fenomena urban heat island dan hubungan antara perubahan penggunaan lahan terhadap suhu permukaan yang menyebabkan terjadinya urban heat island di daerah Kota Solok. Metode yang digunakan dalam penelitian ini yaitu dengan menggunakan salah satu model Land Surface Temperature untuk mengetahui suhu permukaan dengan menggunakan aplikasi pengolahan citra digital selain itu juga menggunakan metode Object Base Image Analyst (OBIA) untuk mendapatkan penggunaan lahan yang ada di Kota Solok. Dengan menggunakan metode yang digunakan akan didapatkan suhu permukaan yang ada di Kota Solok dan daerah fenomena Urban Heat Island serta hubungannya penggunaan lahan dengan suhu permukaan.Kata Kunci : Suhu Permukaan, OBIA, Penggunaan Lahan

scholarly journals A study of urban heat island of Banda Aceh City, Indonesia based on land use/cover changes and land surface temperature

2019 ◽  
Vol 8 (1) ◽  
pp. 41-51 ◽  
Author(s):  
Ashfa Achmad ◽  
Laina Hilma Sari ◽  
Ichwana Ramli
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Planning Process ◽  
Sustainable Urban Development ◽  
Heat Island ◽  
Urban Heat ◽  
Banda Aceh

This article described the spatial and temporal of land surface temperature (LST) patterns in Banda Aceh City, Indonesia, in the context of urban heat island (UHI) phenomenon. Landsat imaginary in 1998 and 2018 was used in this study, which represents the conditions before and after the tsunami. Geographic Information System (GIS) and Remote Sensing (RS) technique were used for data analysis. The 1998 and 2018 LUC maps were derived from remote sensing satellite images using a supervised classification method (maximum likelihood). Both LUC maps contained five categories, namely built-up area, vegetation, water body, vacant land, and wet land. The 1998 LUC map had a kappa coefficient 0.91, while the 2018 LUC map had 0.84. It was found that the built-up area increased by 100%, while the vegetation category fell 50%. The overall mean LST in the study area increased 5.90C between 1998 and 2018, with the highest mean increase in the built-up area category. The study recommends that LST should be taken into consideration in urban planning process to realize sustainable urban development. It also emphasizes the importance of optimizing the availability of green open space to reduce UHI effects and helps in improving the quality of the urban environment. 

scholarly journals IDENTIFYING THE LOCAL SURFACE URBAN HEAT ISLAND THROUGH THE MORPHOLOGY OF THE LAND SURFACE TEMPERATURE

2016 ◽  
Vol III-2 ◽  
pp. 69-75
Author(s):  
Jiong Wang ◽  
Qingming Zhan ◽  
Yinghui Xiao
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Temporal Dynamics ◽  
Satellite Image ◽  
Local Scale ◽  
Heat Island ◽  
Urban Heat ◽  
Surface Urban Heat Island

Current characterization of the Land Surface Temperature (LST) at city scale insufficiently supports efficient mitigations and adaptations of the Surface Urban Heat Island (SUHI) at local scale. This research intends to delineate the LST variation at local scale where mitigations and adaptations are more feasible. At the local scale, the research helps to identify the local SUHI (LSUHI) at different levels. The concept complies with the planning and design conventions that urban problems are treated with respect to hierarchies or priorities. Technically, the MODerate-resolution Imaging Spectroradiometer satellite image products are used. The continuous and smooth latent LST is first recovered from the raw images. The Multi-Scale Shape Index (MSSI) is then applied to the latent LST to extract morphological indicators. The local scale variation of the LST is quantified by the indicators such that the LSUHI can be identified morphologically. The results are promising. It can potentially be extended to investigate the temporal dynamics of the LST and LSUHI. This research serves to the application of remote sensing, pattern analysis, urban microclimate study, and urban planning at least at 2 levels: (1) it extends the understanding of the SUHI to the local scale, and (2) the characterization at local scale facilitates problem identification and support mitigations and adaptations more efficiently.

scholarly journals IDENTIFYING THE LOCAL SURFACE URBAN HEAT ISLAND THROUGH THE MORPHOLOGY OF THE LAND SURFACE TEMPERATURE

2016 ◽  
Vol III-2 ◽  
pp. 69-75 ◽  
Author(s):  
Jiong Wang ◽  
Qingming Zhan ◽  
Yinghui Xiao
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Temporal Dynamics ◽  
Satellite Image ◽  
Local Scale ◽  
Heat Island ◽  
Urban Heat ◽  
Surface Urban Heat Island

Current characterization of the Land Surface Temperature (LST) at city scale insufficiently supports efficient mitigations and adaptations of the Surface Urban Heat Island (SUHI) at local scale. This research intends to delineate the LST variation at local scale where mitigations and adaptations are more feasible. At the local scale, the research helps to identify the local SUHI (LSUHI) at different levels. The concept complies with the planning and design conventions that urban problems are treated with respect to hierarchies or priorities. Technically, the MODerate-resolution Imaging Spectroradiometer satellite image products are used. The continuous and smooth latent LST is first recovered from the raw images. The Multi-Scale Shape Index (MSSI) is then applied to the latent LST to extract morphological indicators. The local scale variation of the LST is quantified by the indicators such that the LSUHI can be identified morphologically. The results are promising. It can potentially be extended to investigate the temporal dynamics of the LST and LSUHI. This research serves to the application of remote sensing, pattern analysis, urban microclimate study, and urban planning at least at 2 levels: (1) it extends the understanding of the SUHI to the local scale, and (2) the characterization at local scale facilitates problem identification and support mitigations and adaptations more efficiently.

Sign in / Sign up

Export Citation Format

Share Document