Land Surface Temperature Variation Due to Changes in Elevation in Northwest Vietnam

Phan, Thanh Noi; Kappas, Martin; Tran, Trong Phuong

doi:10.3390/cli6020028

Cited by 42 publications

(35 citation statements)

References 41 publications

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“…In contrast, the source of heat at night comes from the heat trapped during the day. Therefore, the trend during the day decreased and the trend at night increased in the highlands, with a strong correlation between nighttime and daytime patterns [69]. This information helps to better understand local warming and climate regimes, which are important in shaping agricultural production.…”

Section: Discussionmentioning

confidence: 95%

“…However, at night, the heat released by the surface is absorbed while most heat is radiated back to space by the atmosphere. In the highlands during the warm period, the trend decreased during the day and increased at night, which suggests that the warmest temperature occurred at night [69]. This variation in LST from day to night is indicative of human activities and solar characteristics during the daytime [70].…”

Section: Daytime and Night Time Change Analysismentioning

confidence: 95%

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Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017)

et al. 2020

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It is very important to understand the temporal and spatial variations of land surface temperature (LST) in Africa to determine the effects of temperature on agricultural production. Although thermal infrared remote sensing technology can quickly obtain surface temperature information, it is greatly affected by clouds and rainfall. To obtain a complete and continuous dataset on the spatiotemporal variations in LST in Africa, a reconstruction model based on the moderate resolution imaging spectroradiometer (MODIS) LST time series and ground station data was built to refactor the LST dataset (2003–2017). The first step in the reconstruction model is to filter low-quality LST pixels contaminated by clouds and then fill the pixels using observation data from ground weather stations. Then, the missing pixels are interpolated using the inverse distance weighting (IDW) method. The evaluation shows that the accuracy between reconstructed LST and ground station data is high (root mean square er–ror (RMSE) = 0.84 °C, mean absolute error (MAE) = 0.75 °C and correlation coefficient (R) = 0.91). The spatiotemporal analysis of the LST indicates that the change in the annual average LST from 2003–2017 was weak and the warming trend in Africa was remarkably uneven. Geographically, “the warming is more pronounced in the north and the west than in the south and the east”. The most significant warming occurred near the equatorial region in South Africa (slope > 0.05, R > 0.61, p < 0.05) and the central (slope = 0.08, R = 0.89, p < 0.05) regions, and a nonsignificant decreasing trend occurred in Botswana. Additionally, the mid-north region (north of Chad, north of Niger and south of Algeria) became colder (slope > −0.07, R = 0.9, p < 0.05), with a nonsignificant trend. Seasonally, significant warming was more pronounced in winter, mostly in the west, especially in Mauritania (slope > 0.09, R > 0.9, p < 0.5). The response of the different types of surface to the surface temperature has shown variability at different times, which provides important information to understand the effects of temperature changes on crop yields, which is critical for the planning of agricultural farming systems in Africa.

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Section: Discussionmentioning

confidence: 95%

Section: Daytime and Night Time Change Analysismentioning

confidence: 95%

Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017)

et al. 2020

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“…The annual mean LST in this region is higher than in the eastern part with the similar latitude. Taking into consideration the geographical characteristics of the area, it is observed that the low elevation increases the thermal insulation inside the basin [40]. Regarding the land cover type factor, the largest desert in China is located in this basin, which absorbs solar radiation.…”

Section: ) Correlation Analysismentioning

confidence: 99%

Interannual Spatiotemporal Variations of Land Surface Temperature in China From 2003 to 2018

Duan

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…LST also increases which is directly proportional. Height increases the temperature decreases [ 37 – 39 ]. Built-up land plays a major role in raising the temperature [ 40 ] because of the hard concrete surface which contains almost nil water storage which leads to less humidity.…”

Section: Resultsmentioning

confidence: 99%

Extents of Predictors for Land Surface Temperature Using Multiple Regression Model

2020

The Scientific World Journal

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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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Land Surface Temperature Variation Due to Changes in Elevation in Northwest Vietnam

Cited by 42 publications

References 41 publications

Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017)

Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017)

Interannual Spatiotemporal Variations of Land Surface Temperature in China From 2003 to 2018

Extents of Predictors for Land Surface Temperature Using Multiple Regression Model

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