scholarly journals URBANIZATION AND IT IMPACTS TO LAND SURFACE TEMPERATURE ON SMALL MEDIUM SIZE CITY FOR YEAR 1991, 2011 AND 2018: CASE STUDY KOTA KINABALU

2020 ◽  
Vol 6 (1) ◽  
pp. 58-76
Author(s):  
Ricky Anak Kemarau ◽  
Oliver Valentine Eboy
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Hot Spot ◽  
Medium Size ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Urban Heat ◽  
Landsat 5 Tm

Transformation of land cover vegetation toward urban areas causes the temperature at urban higher to compare to suburban and rural areas, namely urban heat island (UHI) effect. The UHI has a negative impact, such a stroke heat, air pollution, green gasses emission, and electric consumption. UHI studies at a tropical country still limited due to the containment of cloud cover. Besides that, studies only focus on big cities which have residents above than 2 million. The outcome this studied important to enhance our knowledge of urban heat effect at small-medium cities and guidelines to policymaker and urban planner to discover there has effectively taken to decrease the effect of urban heat at the hot spot area. The main goal of this research about to discovered influence of urban growth and selected urban index, namely the Normalized Difference Built Index (NDBI) to LST. NDBI is an index which denotes intensity of urban built up. In the first step, we generate the LST and NDBI from Landsat 8 OLI at year 2018 and Landsat 5 TM for the year 2011 and 1991. Second, we applied the unsupervised classification of Landsat 8 OLI and Landsat 5 TM to generate the land cover maps for the years 1991, 2011, and 2018. Third of our method to examine the relationship between Land surface temperature (LST) and NDBI.  The higher value NDBI is a hot spot, and the low value is a cold spot. In the last step, we applied for Change Detection analysis using GIS to examine the land cover change between 1991 and 2018.  Our results show the higher the value of NDBI and LST at the centre of the city and the lowest value at vegetation land cover. The transformation of land cover vegetation to urban increase at countryside area and out-of-town and significantly increase of distribution of UHI. On another hand, the shows positive relationships between LST and NDBI. The output of the study provides a guideline for policymakers and town designers to develop to toward city zero carbon, sustainable and health.

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 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 Developing land-cover driver model for estimating the intensity of surface urban heat islands using landsat 8 satellite imagery

2019 ◽  
Vol 41 (3) ◽  
pp. 201-215 ◽  
Author(s):  
Nguyen Thanh Hoan ◽  
Nguyen Van Dung ◽  
Ho Le Thu ◽  
Hoa Thuy Quynh
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Landsat 8 ◽  
Moving Window ◽  
Land Cover Types ◽  
Heat Islands ◽  
Urban Heat

It is of utmost importance to understand and monitor the impact of urban heat islands on ecosystems and overall human health in the context of climate change and global warming. This research was conducted in a tropical city, Hanoi, with a major objective of assessing the quantitative relationships between the composition of the main land-cover types and surface urban heat island phenomenon. In this research, we analyzed the correlation between land-cover composition, percentage coverage of the land cover types, and land surface temperature for different moving window sizes or urban land management units. Landsat 8 OLI (Operational Land Imager) satellite data was utilized for preparing land-cover composition datasets in inner Hanoi by employing the unsupervised image clustering method. High-resolution (30m) land surface temperature maps were generated for different days of the years 2016 and 2017 using Landsat 8 TIRS (Thermal Infrared Sensor) images. High correlations were observed between percentage coverage of the land-cover types and land surface temperature considering different window sizes. A new model for estimating the intensity of surface urban heat islands from Landsat 8 imagery is developed, through recursively analyzing the correlation between land-cover composition and land surface temperature at different moving window sizes. This land-cover composition-driven model could predict land surface temperature efficiently not only in the case of different window sizes but also on different days. The newly developed model in this research provides a wonderful opportunity for urban planners and designers to take measures for adjusting land surface temperature and the associated effects of surface urban heat islands by managing the land cover composition and percentage coverage of the individual land-cover types.

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 Land Surface Temperature Retrieval from LANDSAT-8 Thermal Infrared Sensor Data and Validation with Infrared Thermometer Camera

2018 ◽  
Vol 7 (4.20) ◽  
pp. 608 ◽  
Author(s):  
Muhammad Mejbel Salih ◽  
Oday Zakariya Jasim ◽  
Khalid I. Hassoon ◽  
Aysar Jameel Abdalkadhum
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Infrared Sensor ◽  
Infrared Thermometer ◽  
Ground Truth Data ◽  
Land Cover Types

This paper illustrates a proposed method for the retrieval of land surface temperature (LST) from the two thermal bands of the LANDSAT-8 data. LANDSAT-8, the latest satellite from Landsat series, launched on 11 February 2013, using LANDSAT-8 Operational Line Imager and Thermal Infrared Sensor (OLI & TIRS) satellite data. LANDSAT-8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12 bits. In this search a trial has been made to estimate LST over Al-Hashimiya district, south of Babylon province, middle of Iraq. Two dates images acquired on 2nd &18th of March 2018 to retrieve LST and compare them with ground truth data from infrared thermometer camera (all the measurements contacted with target by using type-k thermocouple) at the same time of images capture. The results showed that the rivers had a higher LST which is different to the other land cover types, of less than 3.47 C ◦, and the LST different for vegetation and residential area were less than 0.4 C ◦ with correlation coefficient of the two bands 10 and 11 Rbnad10= 0.70, Rband11 = 0.89 respectively, for the imaged acquired on the 2nd of march 2018 and Rband10= 0.70 and Rband11 = 0.72 on the 18th of march 2018. These results confirm that the proposed approach is effective for the retrieval of LST from the LANDSAT-8 Thermal bands, and the IR thermometer camera data which is an effective way to validate and improve the performance of LST retrieval. Generally the results show that the closer measurement taken from the scene center time, a better quality to classify the land cover. The purpose of this study is to assess the use of LANDSAT-8 data to specify temperature differences in land cover and compare the relationship between land surface temperature and land cover types.   

scholarly journals Thermal Remote Sensing: A tool to Determine Temporal Land Surface Temperature in Hawassa City, Ethiopia

2020 ◽  
Author(s):  
Mikias Biazen Molla
Keyword(s):  
Remote Sensing ◽  
Standard Deviation ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Thermal Remote Sensing ◽  
The City

Abstract This investigation was conducted for the estimation of the temporal land surface temperature value using thermal remote sensing of Landsat-8 (OLI) Data in Hawassa City Administration, Ethiopia. Satellite datasets of Landsat-7 (ETM+) for 22nd March 2002 and Landsat-8 (OLI) of 22nd March 2019 were taken for this study. Different algorisms were used to estimate the Normalized Difference Vegetation Index threshold from the Red and Near-Infrared band and the ground earth's surface emissivity esteem is legitimately recovered from the thermal infrared by coordinating with the outcome got from MODIS information. The land use land cover map of the city was prepared with better accuracy using the on-screen classification technique. The spatial distribution of surface temperature of the city range from 6.62°C to 22.54°C with a mean of 14.58°C and a standard deviation of 11.25 in the year of march 22nd 2002. The LST result derived from Landsat 8 for March 22nd, 2019, ranges from 11.97°C to 35.5°C with a mean of 23.735 °C and a standard deviation of 16.64. In both years the higher LST values correspond to built-up/settlement and bare/open lands of the city; whereas, lower LST values were observed in vegetation (trees/woodlot, shrubs, and grass forested) area. Urban expansion (built-up area roads, and another impervious surface), decline in vegetation levels due to deforestation and increasing population density. Increasing an evergreen tree and green space coverage, design and develop city parks and rehabilitate the existing degraded natural environments are among the recommended strategy to reduce the rate of LST.

scholarly journals Estimation of Land Surface Temperature from Landsat-8 OLI Thermal Infrared Satellite Data. A Comparative Analysis of Two Cities in Ghana

2021 ◽  
Vol 10 (04) ◽  
pp. 131-149
Author(s):  
Yaw A. Twumasi ◽  
Edmund C. Merem ◽  
John B. Namwamba ◽  
Olipa S. Mwakimi ◽  
Tomas Ayala-Silva ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Two Cities
Sign in / Sign up

Export Citation Format

Share Document