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

Remote Sensing

Xuguang Tang¹  Weiyu Shi¹  Lisheng Song¹  Qiuping Li¹  Xujun Han¹  Wenping Yu¹  Mingguo Ma¹  Wei Ge¹  Chao Tan¹  Zengjing Song¹  Hong Yang¹  Siyao Liu²  Ruihai Li²  Ruiyang Qiu² 

[1] Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China;High School Affiliated to Southwest University, Chongqing 400700, China;

关键词: land surface temperature;    SINDVI;    PM_2.5;    air pollution;    time-series analysis;    Arctic;    Antarctic;   

DOI  :  10.3390/rs10122034

来源: DOAJ

【 摘 要 】

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 (PM_2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM_2.5 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 PM_2.5 on LST was more complex. On the whole, LST increased with a small increase in PM_2.5 concentrations but decreased with a marked increase in PM_2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature.

【 授权许可】

Unknown