Spatiotemporal variability of land surface temperature in north-western Ethiopia

Author(s):  
Getachew Bayable ◽  
Getnet Alemu
2021 ◽  
Author(s):  
Getachew Bayable ◽  
Getnet Alemu

Abstract The aggravating deforestation, industrialization and urbanization are increasingly becoming the principal causes for environmental challenges worldwide. As a result, satellite-based remote sensing helps to explore the environmental challenges spatially and temporally. This investigation analyzed the spatiotemporal discrepancies in Land Surface Temperature (LST) and the link with elevation in Amhara region, Ethiopia. The Moderate Resolution Imaging Spectroradiometer (MODIS) LST data (2001–2020) was used. The pixel-based linear regression model was employed to explore the spatiotemporal discrepancies of LST changes pixel-wise. Furthermore, Sen's slope and Mann-Kendall were used for determining the extent of temporal shifts of the areal average LST and evaluating trends in areal average LST values, respectively. Coefficient of Variation (CV) was calculated to examine spatial and temporal discrepancies in seasonal and annual LST for each pixel. The distribution of average seasonal LST spatially ranged from 43.45–16.62℃, 39.89–14.59℃, 50.39-21.102℃ and 43.164–20.39℃ for autumn (September-November), summer (June-August), spring (March-May) and winter (December-February) seasons, respectively. The seasonal LST CV varied from1.096-10.72%, 0.7–11.06%, 1.29–14.76% and 2.19–10.35% for average autumn, summer, spring and winter seasons, respectively. The seasonal spatial LST trend varied from − 0.7 − 0.16, -0.4-0.224, 0.6 − 0.19 and − 0.6 − 0.32 for average autumn, summer, spring and winter seasons, respectively. Besides, the annual spatial LST slope varied from − 0.58 − 0.17. An insignificantly declining trend in LST shown at 0.036℃ yr− 1, 0.041℃ yr− 1, 0.074℃ yr− 1, 0.005℃ yr− 1 in autumn, summer, spring and winter seasons (P < 0.05), respectively. Moreover, the annual variations of mean LST decreased insignificantly at 0.046℃ yr− 1. Generally, the LST is tremendously variable in space and time and negatively correlated with an elevation.


Author(s):  
Mitiku Badasa ◽  
Lachisa Busha

Analysis of the correlation between indices (Normalized Difference Vegetation Index, Normalized Difference Barren Index and Modified Normalized Difference Water Index) and land surface temperature is used to natural resources and environmental studies. This research aimed to analysis of Land Surface Temperature due to dynamics of Different Indices (NDVI, NDBaI and MNDWI) Using Remote Sensing Data in three selected districts (Gida Kiremu, Limu and Amuru), western Ethiopia. From thermal and multispectral bands of landsat imageries (Landsat TM of 1990, landsat ETM+ of 2003 and landsat OLI/TIRS of 2020) Land surface temperature and NDVI, NDBaI and MNDWI were calculated. Correlation analysis was used to indicate relationships between LST with NDVI, NDBaI and MNDWI. The study found that Land Surface Temperature was increased by 50C from 1990 to 2020. Vegetation areas (NDVI) and Water bodies (MNDWI) have strong negative relationship with Land Surface Temperature (R2= 0.99, 0.95) whereas Barren land (NDBaI) has positive relationship with Land Surface Temperature (R2= 0.96). Finally, we recommend the decision makers and environmental analyst to emphasis the importance of vegetation cover and water body to minimize the potential impacts of land surface temperature.


Author(s):  
Jefferson Inayan de Oliveira Souto ◽  
Julia Clarinda Paiva Cohen

Abstract Cities experience the extensive urban heat island effect (UHI), which continue to pose challenges for humanity's increasingly urban population, where tropical cities have experienced a continued and rapid urbanization process in the past few decades. We present the evolution of surface UHI and its controlling factors in the Metropolitan Region of Belém, over the last 16 years (2003-2018), which has experienced unique consolidated economic growth and urban transformation under wet equatorial climate. We incorporate MODIS and Landsat satellite data and evaluate statistical techniques for estimates the variation in the land surface temperature (LST) during two seasons: wet season and dry season. Our result revealed that the regions of fast urbanization resulted in a decrease of normalized difference vegetation index and increase of LST. In addition, annual maps showed the spatial pattern of surface UHI intensities were produced based on daytime and nighttime temperature, and the analysis result indicated that the spatial distribution of high heat capacity was closely related with the densely built-up areas. These findings are helpful for understanding the urbanization process as well as urban ecology, which both have significant implications for urban planning and minimize the potential environmental impacts of urbanization in Metropolitan Region of Belém.


Author(s):  
Georgiana Grigoraș ◽  
Bogdan Urițescu

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.


2021 ◽  
Vol 1825 (1) ◽  
pp. 012021
Author(s):  
Nasrullah Zaini ◽  
Muhammad Yanis ◽  
Marwan ◽  
Muhammad Isa ◽  
Freek van der Meer

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