scholarly journals Effect of Land Surface Temperature on Urban Heat Island in Varanasi City, India

J ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 420-429
Author(s):  
Amit Kumar ◽  
Vivek Agarwal ◽  
Lalit Pal ◽  
Surendra Kumar Chandniha ◽  
Vishal Mishra
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Sustainable Urban Development ◽  
Landsat 8 ◽  
Heat Island ◽  
Impervious Cover ◽  
Green Cover ◽  
Urban Heat

Crucial changes in urban climate can be witnessed due to rapid urbanisation of cities across the world. It is important to find a balance between urban expansion and thermal environment quality to guarantee sustainable urban development. Thus, it is a major research priority to study the urban heat island (UHI) in various fields, i.e., climate change urban ecology, urban climatology, urban planning, mitigation and management, urban geography, etc. The present study highlighted the interrelationship between land surface temperature (LST) and the abundance of impervious cover and green cover in the Varanasi city of Uttar Pradesh, India. For this purpose, we used various GIS and remote-sensing techniques. Landsat 8 images, land-use–land-cover pattern including urban/rural gradients, and grid- and metric-based multi-resolution techniques were used for the analysis. From the study, it was noticed that LST, density of impervious cover, and density of green cover were correlated significantly, and an urban gradient existed over the entire city, depicting a typical UHI profile. It was also concluded that the orientation, randomness, and aggregation of impervious cover and green cover have a strong correlation with LST. From this study, it is recommended that, when planning urban extension, spatial variation of impervious cover and green cover are designed properly to ensure the comfort of all living beings as per the ecological point of view.

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 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 Pemetaan Fenomena Urban Heat Island Di Kota Kendari Dengan Menggunakan Citra Resolusi Menengah

2021 ◽  
Vol 5 (1) ◽  
pp. 33
Author(s):  
Fatimah Wardana ◽  
Laode Muh. Golok Jaya ◽  
Fitra Saleh ◽  
Jufri Karim
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Landsat 8 ◽  
Density Level ◽  
Heat Island ◽  
Landsat 8 Oli ◽  
Urban Heat

Abstrak: Fenomena Urban Heat Island dapat dipetakan dengan parameter Suhu Permukaan Tanah (SPT) dan indeks kerapatan vegetasi (NDVI). Penelitian ini bertujuan untuk menganalisis Urban Heat Island di Kota Kendari menggunakan Landsat 8 OLI/TIRS dan menganalisis kondisi eksisting sebaran fenomena Urban Heat Island di Kota Kendari. Proses dilakukan dengan mengolah data citra Landsat 8 OLI/TIRS perekaman 30 Agustus 2017. Analisis dilakukan dengan menggunakan algoritma Syariz untuk penentuan SPT yang kemudian dikorelasikan dengan nilai NDVI yang dihasilkan dari kaliberasi band 4 dan band 5 pada citra Landsat 8 OLI/TIRS. Hasil penelitian ini menunjukkan suhu permukaan tanah di kota Kendari berkisar antara 15,27 hingga 33,34. Dimana suhu 15 hingga 22adalah suhu daerah yang tidak terdeteksi atau tertutup awan. Persebaran suhu didominasi suhu antara 23-27 dengan luas 21.492,46 Ha atau 81,02% dari luas wilayah, dengan wilayah yang teridentifikasi sebagaui daerah UHI dengan suhu diantara 28-33 seluas 2.968,57 Ha atau 11,01% dari total luas wilayah Kota Kendari. Nilai korelasi antara SPT dan NDVI berada pada angka -0,66 yang berarti bahwa tingkat kerapatan vegetasi berbanding terbalik dengnan nilai suhu permukaan tanah atau semakin rendah indeks kerapatan vegetasinya, maka semakin tinggi suhu permukaan tanahnya.Kata kunci: Urban Heat Island, suhu permukaan tanah, Landsat 8, NDVIAbstract: The Urban Heat Island phenomenon can be mapped with the parameters of Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI). This study aims to analyze Urban Heat Island in Kendari City using Landsat 8 OLI / TIRS and analyze the existing conditions of the distribution of the Urban Heat Island phenomenon in Kendari City. The process is done by processing Landsat 8 OLI / TIRS image recording data on August 30, 2017. The analysis carried out using the Syariz algorithm to determine LST which is then correlated with NDVI values resulting from band 4 and band 5 in Landsat 8 OLI / TIRS images. The results showed that the  land surface temperature in Kendari ranged from 15.27°C to 33.34°C. The 15 to 22°C is the temperature of the clouded or undetected area. The temperature distribution is dominated by temperatures between 23-27 ° C with an area of 21,492.46 Ha or  81.02% of the total area, with areas identified as UHI are the areas with temperatures between 28-33 ° C with an area of 2,968.57 Ha or 11.01% of the total area of  Kendari City. The correlation value between SPT and NDVI is at -0.66, which means that the vegetation density level is inversely proportional to the value of the land surface temperature value or the lower the vegetation index value, the higher the surface temperature of the land.Keywords: Urban Heat Island, land surface temperature, Landsat 8, NDVI

scholarly journals MODEL KEKRITISAN INDEKS LINGKUNGAN DENGAN ALGORITMA URBAN HEAT ISLAND DI KOTA SEMARANG

2017 ◽  
Vol 19 (1) ◽  
pp. 45 ◽  
Author(s):  
Bandi Sasmito ◽  
Andri Suprayogi
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Heat Island ◽  
Urban Heat ◽  
Criticality Index

<p align="center"> <strong>ABSTRAK</strong></p><p class="JudulABSInd"><span lang="IN"> </span></p><p class="abstrak"><span lang="IN">Pembangunan infrastruktur di Kota Semarang berkembang sangat pesat sebagai pusat bisnis, ekonomi, industri, hiburan, dan pendidikan. Pembangunan memberikan dampak positif bagi masyarakat kota, namun terdapat juga dampak negatif yang terjadi yaitu penurunan kualitas lingkungan. Meningkatnya suhu udara adalah salah satu dampak dari penurunan kualitas lingkungan. Puncak atap dan dinding dari gedung bertingkat, tempat parkir, jalan, dan trotoar cenderung memiliki albedo yang rendah. Permukaan rendah albedo menyerap energi panas radiasi matahari lebih tinggi dari objek sekitarnya. Akibatnya, jumlah kelebihan energi panas menumpuk di sekitarnya menjadi pulau-pulau panas atau <em>Urban Heat Island</em> (UHI). Penelitian ini bertujuan untuk mendeteksi terjadinya fenomena kekritisan lingkungan akibat UHI dengan menganalisis suhu permukaan dan sebaran vegetasi di wilayah studi. Ada dua langkah metode dalam penelitian ini, pertama adalah membuat peta sebaran suhu permukaan tanah dan peta sebaran kerapatan vegetasi di tahun 2013 sampai 2016. Peta suhu permukaan dibuat dengan model algoritma <em>Land Surface Temperature</em> (LST) dan sebaran vegetasi adalah dengan algoritma <em>Normalized Difference Vegetation Index</em> (NDVI). LST didapatkan dengan mengolah Citra Landsat-8 band TIRS (<em>Thermal Infrared Red Sensor</em>), sedangkan NDVI  didapatkan dengan mengolah Citra Landsat-8 band OLI (<em>Operation Land Imager</em>). Langkah kedua adalah membuat peta kekritisan lingkungan dengan algoritma ECI (<em>Environmental Criticality Index</em>). ECI didapatkan dari nilai LST dibagi NDVI yang direntangkan histogram spektralnya menjadi 8 bit. </span>Melalui<span lang="IN"> hasil penelitian ini dapat disimpulkan bahwa suhu permukaan di Kota Semarang meningkat dan sebaran kelas suhu tinggi meluas setiap tahun. Kekritisan lingkungan akibat UHI terdeteksi di pusat kota, yaitu wilayah Utara Kota Semarang.</span></p><p class="abstrak"><strong><span lang="IN">Kata kunci</span></strong><span lang="IN">: </span><em><span lang="IN">Urban Heat Island</span></em><span lang="IN"> (UHI), </span><em><span lang="IN">Land Surface Temperature</span></em><span lang="IN"> (LST), <em>Normalized Difference Vegetation Index</em> (NDVI)</span><span lang="IN">, </span><em><span lang="IN">Environmental Criticality Index</span></em><span lang="IN"> (ECI)</span></p><p align="center"><strong><br /></strong></p><p align="center"><strong><em>ABSTRACT</em></strong></p><p class="Abstrakeng">Infrastructure in Semarang City developes rapidly as a center of business, economics, industry, entertainment, and education. Development gives positive impact to citizen, however environmental degradation as the negative impact also occured. Temperatures rising is one of environmental degradation impact. Roof top and wall of a building, parking lot, road, and sidewalk tend to have a low albedo. The low surface albedo absorbs thermal energy from solar radiation higher than the surrounding objects. As a result, the amount of excess heat accumulate in the vicinity into heat islands or Urban Heat Island (UHI). This study aims to detect the occurrence of environmental criticality due to UHI phenomenon by analyzing the surface temperature and the distribution of vegetation in the study area. There are two steps in this research, first step is to create land surface temperature distribution map and vegetation density distribution map in the year of 2013 to 2016. The surface temperature map created by Land Surface Temperature (LST) algorithm model and vegetation distribution created by Normalized Difference Vegetation Index (NDVI) algorithm. LST is obtained by processing Landsat-8 band TIRS (Thermal Infrared Sensor Red), while the NDVI obtained by processing Landsat-8 band OLI (Operation Land Imager). The second step is to create environmental criticality map with  ECI (Environmental Criticality Index) algorithm. ECI is obtained from LST value divided by NDVI spectral histogram stretched to 8 bits. From this research, can be concluded that the heat coverage in Semarang City increase and distribution of vegetation density index spread every year. Environmental criticality due to UHI occurred in downtown area, specifically in the northern side of Semarang City.</p><p><strong><em>Keywords</em></strong><em>:</em><em>   </em><em>Urban Heat Island</em> (UHI), <em>Land Surface Temperature</em> (LST), <em>Normalized Difference Vegetation Index</em> (NDVI), <em>Environmental Criticality Index</em> (ECI)</p><p align="center"><strong><em><br /></em></strong></p><p> </p>

scholarly journals Cooling Effect of Different Land Cover Types: A Case Study in Xi’an and Xianyang, China

2021 ◽  
Vol 13 (3) ◽  
pp. 1099
Author(s):  
Yuhe Ma ◽  
Mudan Zhao ◽  
Jianbo Li ◽  
Jian Wang ◽  
Lifa Hu
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Cooling Effect ◽  
Heat Island ◽  
Land Cover Types ◽  
Island Effect ◽  
Urban Heat

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.

scholarly journals RELATIONSHIPS BETWEEN LAND USE/LAND COVER AND LAND SURFACE TEMPERATURE IN TABRIZ FROM 2000 TO 2017

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 1041-1044
Author(s):  
A. Tahooni ◽  
A. A. Kakroodi
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Impervious Surface ◽  
Bare Soil ◽  
Heat Island ◽  
Land Use Land Cover ◽  
Urban Heat

Abstract. Urban Heat Island (UHI) refers to the development of higher urban temperatures of an urban area compared to the temperatures of surrounding suburban and rural areas. Highly reflective urban materials to solar radiation present a significantly lower surface temperature and contribute to reducing the sensible heat released in the atmosphere and mitigating the urban heat island. Many studies of the UHI effect have been based on Land Surface Temperature (LST) measurements from remote sensors. The remotely sensed UHI has been termed the surface urban heat island (SUHI) effect. This study examines Tabriz city land use/land cover (LULC) and LST changes using Landsat satellite images between 2000 and 2017. Maximum likelihood classification and single channel methods were used for LULC classification and LST retrieval respectively. Results show that impervious surface has increased 13.79% and bare soil area has decreased 16.2%. The results also revealed bare soil class LST after a constant trend become increasing. It also revealed the impervious surface LST has a decreasing trend between 2000 and 2011 and has a little change. Using materials that have low absorption and high reflectance decrease the effect of heat island considerably.

scholarly journals LINKING THE LOCAL CLIMATE ZONES AND LAND SURFACE TEMPERATURE TO INVESTIGATE THE SURFACE URBAN HEAT ISLAND, A CASE STUDY OF SAN ANTONIO, TEXAS, U.S.

2018 ◽  
Vol IV-3 ◽  
pp. 277-283 ◽  
Author(s):  
Chunhong Zhao
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
San Antonio ◽  
Heat Island ◽  
Climate Zones ◽  
Local Climate ◽  
Local Climate Zones ◽  
Urban Heat

The Local Climate Zones (LCZs) concept was initiated in 2012 to improve the documentation of Urban Heat Island (UHI) observations. Despite the indispensable role and initial aim of LCZs concept in metadata reporting for atmospheric UHI research, its role in surface UHI investigation also needs to be emphasized. This study incorporated LCZs concept to study surface UHI effect for San Antonio, Texas. LCZ map was developed by a GIS-based LCZs classification scheme with the aid of airborne Lidar dataset and other freely available GIS data. Then, the summer LST was calculated based Landsat imagery, which was used to analyse the relations between LST and LCZs and the statistical significance of the differences of LST among the typical LCZs, in order to test if LCZs are able to efficiently facilitate SUHI investigation. The linkage of LCZs and land surface temperature (LST) indicated that the LCZs mapping can be used to compare and investigate the SUHI. Most of the pairs of LCZs illustrated significant differences in average LSTs with considerable significance. The intra-urban temperature comparison among different urban classes contributes to investigate the influence of heterogeneous urban morphology on local climate formation.

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