scholarly journals THE EFFECT OF GREEN SPACE ON THE LAND SURFACE TEMPERATURE IN HUE CITY

2018 ◽  
Vol 55 (4C) ◽  
pp. 129
Author(s):  
Nguyen Bac Giang
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Green Space ◽  
Satellite Image ◽  
Urban Green Space ◽  
Landsat 8 ◽  
Urban Green ◽  
Study Results

This paper presents the analysis of the effect of urban green space types on land surface temperature in Hue city. Data are collected with temperature monitoring results from each green space type and the interpretation of surface temperature based on Landsat 8 satellite image data to determine temperatures at different times of the year. Results showed that there was a significant correlation between types of urban green space and the surface temperature. Types of green space with a large area and vegetation indexes have a greater effect on temperature than areas with a smaller green space do. Green space types including forest green space, dedicated green space and agriculture green space have the most effect on the surface temperature. The forest area has the greatest influence on the temperature with a temperature difference of more than 1.6 degrees Celsius at 9:00 in the daytime. Besides, the results extracted from satellite images also show that the area of urban green space going to be reduced makes a contribution to increase the surface temperature of urban areas. The study results have established foundation for planning the green spaces in climate change challenges in Hue City.

Separate and combined effects of 3D building features and urban green space on land surface temperature

2021 ◽  
Vol 295 ◽  
pp. 113116
Author(s):  
Bo Yuan ◽  
Liang Zhou ◽  
Xuewei Dang ◽  
Dongqi Sun ◽  
Fengning Hu ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Green Space ◽  
Urban Green Space ◽  
Combined Effects ◽  
Urban Green

scholarly journals Urban Green Space Growth Impact on Surface Temperature Distribution

2018 ◽  
Vol 3 (10) ◽  
pp. 198-207
Author(s):  
Siti Nor Afzan Buyadi ◽  
Wan Mohd Naim Wan Mohd ◽  
Alamah Misni
Keyword(s):  
Urban Development ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Green Space ◽  
Publishing House ◽  
Urban Green Space ◽  
Mature Trees ◽  
Commercial Development ◽  
Urban Green

Trees and vegetation play a vital role to mitigate urban heat island (UHI) effects. Land use, vegetation growth detection and land surface temperature (LST) maps of two different dates are generated from Landsat 5 TM (1991 and 2009) in the city of Shah Alam. The conversion of natural green areas into residential and commercial development significantly increases the LST. The result reveals that mature trees in urban green space help to mitigate the effects of UHI as well as to sustain the urban development. Keywords: trees; land surface temperature (LST); urban; development. eISSN 2514-751X © 2018. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/aje-bs.v3i10.327

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 Pemetaan Wilayah Lahan Basah Berdasarkan Data Penginderaan Jauh Optik Dan Radar

2020 ◽  
Vol 4 (2) ◽  
pp. 48-61
Author(s):  
Rian Nurtyawan ◽  
Ervan Muktamar Hendarna
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Satellite Image ◽  
Soil Surface ◽  
Landsat 8 ◽  
Optical Remote Sensing ◽  
Radar Sensing

ABSTRAKPada umumnya lahan basah dikelola menjadi area pertanian ataupun perkebunan. Fungsi lahan basah memiliki fungsi ekologis seperti pengendali banjir, pencegah intrusi air laut, erosi, pencemaran, dan pengendali iklim global. Data pengindraan jauh yang digunakan pengelolaan lahan basah yaitu pengindraan jauh optik dan radar. Tujuan dari penelitian ini adalah mengeksplorasi korelasi potensial dari data optik dan radar untuk mengamati dinamika pada kawasan lahan basah tersebut dan melakukan pemetaan. Metode yang digunakan pada pengindraan jauh optik yaitu LST (Land Surface Temperature) berdasarkan Citra Satelit Landsat-8 dan metode yang digunakan pada pengindraan jauh radar yaitu estimasi kelembaban tanah berdasarkan Citra Satelit Sentinel-1A. Hasil pengamatan dinamika dan pemetaan pada wilayah Kabupaten Bandung Raya memiliki nilai kelembaban tanah tertinggi pada Bulan Mei dengan nilai kelembapan tanah tanah rata-rata sebesar 20,9 % pada polarisasi VH. Suhu permukaan tanah terendah terjadi pada bulan Mei dengan nilai suhu rata-rata sebesar 19.5 °C. Kolerasi antara nilai kelembapan tanah tanah dan suhu permukaan tanah pada wilayah Kabupaten Bandung Raya berdasarkan metode koefisien determinasi sebesar R2=0.705 didapatkan bahwa semakin tinggi nilai kelembapan tanah tanah maka nilai suhu permukaan tanah akan semakin rendah.Kata kunci: Kawasan lahan basah, Pengindraan Jauh Optik, Pengindraan Jauh Radar, Pengamatan Dinamika, Pemetaan. ABSTRACTIn general wetlands managed become an area of agriculture or plantations. The extent of wetland that has been used can be damaged if it is not managed properly and integrated.. The purpose of this research is to explore the potential correlations between several parameters of optical and radar data to observe the dynamics of wetlands area and mapping the wetlands area. The methodology that was used in optical remote sensing is LST (Land Surface Temperature) based on Landsat-8 Satellite Image and the method used in remote radar sensing is estimation of soil moisture based on Sentinel-1A Satellite Image. The result of the observation in the area and mapping the dynamics in Bandung Raya District had the highest soil moisture values in May with 27% of soil water level in VH polarization and 78.1% in VV polarization and the lowest value in each month is 11.8% and the highest soil surface temperature in August with a value 37.9 ° C and the minimum value 19 ° C..Keywords: Wetland Area, Optical Remote Sensing, Remote Radar Sensing, Dynamics Observation, Mapping.

scholarly journals An assessment of the Relationship between Vegetation (Forest Density Cover) Built-Up Area and City Land Surface Temperature, Generated by LANDSAT-8 OLI/ Thermal band - A Case study of Dehradun, India

2021 ◽  
Vol 16 (3) ◽  
Author(s):  
Rajeev Shankhwar ◽  
Rajlakshmi Datta ◽  
Navendra Uniyal
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Forest Cover ◽  
Past Research ◽  
Present Condition ◽  
Landsat 8 ◽  
Forest Density ◽  
Open Land

Dehradun city is the capital of Uttarakhand state of India. Evidence from the past research and literature [e.g. CDP 2007, Singh et al 2013, Gupta et al 2014] shows that in the late 80s, Dehradun city was much greener compared to the present condition. In the current study, we tried to identify the correlation between land surface temperature (LST) with Forest cover density classes (FCDC) and built-up area with open land. The current study reveals that there is a relationship between FCDC and LST in the study area. The range of LST recorded is between 32.07 to 43.99 °C. Among all the classes, minimum LST record in VDF class is 32.07°C and maximum LST record in built-up area 43.99°C. The present study shows the importance of vegetation cover in urban areas to reduce LST, air temperature and maintain the urban microclimate as well as to help reduce air pollution.

scholarly journals Extents of Predictors for Land Surface Temperature Using Multiple Regression Model

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
R. M. Yuvaraj
Keyword(s):  
Surface Temperature ◽  
Regression Model ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Climate Models ◽  
Multiple Linear Regression Model ◽  
Multiple Regression Model ◽  
Landsat 8 ◽  
Study Region

Land surface temperature (LST) is a key factor in numerous areas such as climate change, land use/land cover in the urban areas, and heat balance and is also a significant participant in the creation of climate models. Landsat data has given numerous possibilities to understand the land processes by means of remote sensing. The present study has been performed to identify the LST of the study region using Landsat 8 OLI/TIRS satellite images for two time periods in order to compare the data. The study also attempted to identify and predict the role and importance of NDVI, NDBI, and the slope of the region on LST. The study concludes that the maximum and minimum temperatures of 40.44 C and 20.78 C were recorded during the November month whereas the maximum and minimum LST for month March has increased to 42.44 C and 24.57 C respectively. The result indicates that LST is inversely proportional to NDVI (−6.369) and slope (−0.077) whereas LST is directly proportional to NDBI (+14.74). Multiple linear regression model has been applied to calculate the extents of NDVI, NDBI, and slope on the LST. It concludes that the increase in vegetation and slope would result in slight decrease in temperature whereas the increase in built-up will result in a huge increase in temperature.

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