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Remote Sens. 2018, 10(12), 2034; https://doi.org/10.3390/rs10122034

Global Land Surface Temperature Influenced by Vegetation Cover and PM2.5 from 2001 to 2016

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Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
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Research Base of Karst Eco-environments at Nanchuan in Chongqing, Ministry of Nature Resources, School of Geographical Sciences, Southwest University, Chongqing 400715, China
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Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Karst Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, China
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Chongqing Key Laboratory of Karst Environment, School of Geographical Sciences, Southwest University, Chongqing 400715, China
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High School Affiliated to Southwest University, Chongqing 400700, China
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Department of Geography and Environmental Science, University of Reading, Whiteknights, Reading RG6 6AB, UK
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Authors to whom correspondence should be addressed.
Received: 7 November 2018 / Revised: 10 December 2018 / Accepted: 11 December 2018 / Published: 14 December 2018
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Abstract

Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine particulate matter (PM2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM2.5 increased by 0.17 K, 0.04, and 1.02 μg/m3 in the period of 2001–2016, respectively. During the past 16 years, LST showed an increasing trend in most areas, with two peaks of 1.58 K and 1.85 K at 72°N and 48°S, respectively. Marked warming also appeared in the Arctic. On the contrary, remarkable decrease in LST occurred in Antarctic. In most parts of the world, LST was affected by the variation in vegetation cover and air pollutant, which can be detected by the satellite. In the Northern Hemisphere, positive relations between SINDVI and LST were found; however, in the Southern Hemisphere, negative correlations were detected. The impact of PM2.5 on LST was more complex. On the whole, LST increased with a small increase in PM2.5 concentrations but decreased with a marked increase in PM2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature. View Full-Text
Keywords: land surface temperature; SINDVI; PM2.5; air pollution; time-series analysis; Arctic; Antarctic land surface temperature; SINDVI; PM2.5; air pollution; time-series analysis; Arctic; Antarctic
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Song, Z.; Li, R.; Qiu, R.; Liu, S.; Tan, C.; Li, Q.; Ge, W.; Han, X.; Tang, X.; Shi, W.; Song, L.; Yu, W.; Yang, H.; Ma, M. Global Land Surface Temperature Influenced by Vegetation Cover and PM2.5 from 2001 to 2016. Remote Sens. 2018, 10, 2034.

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