LAND SURFACE TEMPERATURE INVESTIGATION AROUND IKOGOSI WARM SPRING NIGERIA USING LANDSAT8 DATA

2021 ◽  
Vol 5 (2) ◽  
pp. 264-272
Author(s):  
Y. A. Bello ◽  
K. M. Lawal ◽  
B. B. M. Dewu ◽  
A. E. Ikpokonte
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Hot Spot ◽  
Geophysical Methods ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Geothermal Resource ◽  
Geothermal Resources ◽  
Warm Spring

Ikogosi warm spring (IWS) is among the most visited geothermal resource by tourists in Nigeria. On that basis, it has attracted so much attention from researchers using various geophysical methods, except the retrieval of the land surface temperature (LST) from remote sensing data. This work aimed at computing LST to delineate hot zone around Ikogosi geothermal resources. The split-window approach was used to compute the LST from Landsat 8 data. The interpretation of Landsat8 data revealed that the central region of the study area is of high LST, and the temperature then drops towards the southwest direction. The result also shows that the warm spring is situated around a region with high land surface temperature (about 29 °C) which is an indication of a geothermal reservoir. The supervised classification of the LST yields two zones of the high density of pixels with high temperature, hot spot zones. The hot spot zone west of IWS is believed to be the heat source of IWS as it has high LST, and it is closer to IWS while the hot spot zone NW of IWS shows an indication of a viable geothermal resource, high LST

scholarly journals Retrieval of Land Surface Temperature From Landsat 8 Data of the Dandong-liaoyang Geothermal Area

2020 ◽  
Author(s):  
Yiming Luan
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Fossil Fuels ◽  
Hot Springs ◽  
Atmospheric Correction ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Geothermal Resources ◽  
Thermal Infrared Remote Sensing

Abstract In recent years, with the intensification of problems like the depletion of traditional fossil fuels and environmental degradation, the development of new energy sources has become a key long-term strategy in China. Geothermal energy has attracted much attention due to its advantages of abundance and low environmental impact. Based on infrared data sensed remotely by the Landsat 8 satellite, this paper reports a verification of the atmospheric-correction method for extracting the surface temperature of the Dandong-Liaoyang geothermal region in all months of 2014. The method combines the abnormal points in the inversion results with the local sites of hot springs, structures, local historical air temperatures, and land surface temperature/emissivity data (MOD11_L2). Results showed that these data sources were spatially distributed in similar ways, which indicates that these results can be used to identify promising geothermal resources from publically available thermal-infrared remote-sensing data.

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 A Comparative Analysis of Retrieval Algorithms of Land Surface Temperature from Landsat-8 Data: A Case Study of Shanghai, China

2021 ◽  
Vol 18 (11) ◽  
pp. 5659
Author(s):  
Yue Jiang ◽  
WenPeng Lin
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Single Channel ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Thermal Infrared Remote Sensing ◽  
Retrieval Algorithms ◽  
Split Window Algorithm

In the trend of global warming and urbanization, frequent extreme weather has a severe impact on the lives of citizens. Land Surface Temperature (LST) is an essential climate variable and a vital parameter for land surface processes at local and global scales. Retrieving LST from global, regional, and city-scale thermal infrared remote sensing data has unparalleled advantages and is one of the most common methods used to study urban heat island effects. Different algorithms have been developed for retrieving LST using satellite imagery, such as the Radiative Transfer Equation (RTE), Mono-Window Algorithm (MWA), Split-Window Algorithm (SWA), and Single-Channel Algorithm (SCA). A case study was performed in Shanghai to evaluate these existing algorithms in the retrieval of LST from Landsat-8 images. To evaluate the estimated LST accurately, measured data from meteorological stations and the MOD11A2 product were used for validation. The results showed that the four algorithms could achieve good results in retrieving LST, and the LST retrieval results were generally consistent within a spatial scale. SWA is more suitable for retrieving LST in Shanghai during the summer, a season when the temperature and the humidity are both very high in Shanghai. Highest retrieval accuracy could be seen in cultivated land, vegetation, wetland, and water body. SWA was more sensitive to the error caused by land surface emissivity (LSE). In low temperature and a dry winter, RTE, SWA, and SCA are relatively more reliable. Both RTE and SCA were sensitive to the error caused by atmospheric water vapor content. These results can provide a reasonable reference for the selection of LST retrieval algorithms for different periods in Shanghai.

Spatial Hotspot Analysis of Bucharest’s Urban Heat Island (UHI) Using Modis Data

2018 ◽  
Vol 18 (1) ◽  
pp. 14-22 ◽  
Author(s):  
Georgiana Grigoraș ◽  
Bogdan Urițescu
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Hot Spots ◽  
Land Surface ◽  
Hot Spot ◽  
Monitoring Network ◽  
Residential Areas ◽  
Hotspot Analysis ◽  
The City

Abstract The aim of the study is to find the relationship between the land surface temperature and air temperature and to determine the hot spots in the urban area of Bucharest, the capital of Romania. The analysis was based on images from both moderate-resolution imaging spectroradiometer (MODIS), located on both Terra and Aqua platforms, as well as on data recorded by the four automatic weather stations existing in the endowment of The National Air Quality Monitoring Network, from the summer of 2017. Correlation coefficients between land surface temperature and air temperature were higher at night (0.8-0.87) and slightly lower during the day (0.71-0.77). After the validation of satellite data with in-situ temperature measurements, the hot spots in the metropolitan area of Bucharest were identified using Getis-Ord spatial statistics analysis. It has been achieved that the “very hot” areas are grouped in the center of the city and along the main traffic streets and dense residential areas. During the day the "very hot spots” represent 33.2% of the city's surface, and during the night 31.6%. The area where the mentioned spots persist, falls into the "very hot spot" category both day and night, it represents 27.1% of the city’s surface and it is mainly represented by the city center.

scholarly journals The Challenge of the Urban Compact Form: Three-Dimensional Index Construction and Urban Land Surface Temperature Impacts

2021 ◽  
Vol 13 (6) ◽  
pp. 1067
Author(s):  
Han Yan ◽  
Kai Wang ◽  
Tao Lin ◽  
Guoqin Zhang ◽  
Caige Sun ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Form ◽  
Three Dimensional ◽  
Compact Form ◽  
Landsat 8 ◽  
Driving Mechanism ◽  
Building Density ◽  
Building Height

Cities are growing higher and denser, and understanding and constructing the compact city form is of great importance to optimize sustainable urbanization. The two-dimensional (2D) urban compact form has been widely studied by previous researchers, while the driving mechanism of three-dimensional (3D) compact morphology, which reflects the reality of the urban environment has seldom been developed. In this study, land surface temperature (LST) was retrieved by using the mono-window algorithm method based on Landsat 8 images of Xiamen in South China, which were acquired respectively on 14 April, 15 August, 2 October, and 21 December in 2017, and 11 March in 2018. We then aimed to explore the driving mechanism of the 3D compact form on the urban heat environment (UHE) based on our developed 3D Compactness Index (VCI) and remote sensing, as well as Geo-Detector techniques. The results show that the 3D compact form can positively effect UHE better than individual urban form construction elements, as can the combination of the 2D compact form with building height. Individually, building density had a greater effect on UHE than that of building height. At the same time, an integration of building density and height showed an enhanced inter-effect on UHE. Moreover, we explore the temporal and spatial UHE heterogeneity with regards to 3D compact form across different seasons. We also investigate the UHE impacts discrepancy caused by different 3D compactness categories. This shows that increasing the 3D compactness of an urban community from 0.016 to 0.323 would increase the heat accumulation, which was, in terms of satellite derived LST, by 1.35 °C, suggesting that higher compact forms strengthen UHE. This study highlights the challenge of the urban 3D compact form in respect of its UHE impact. The related evaluation in this study would help shed light on urban form optimization.

Sign in / Sign up

Export Citation Format

Share Document