Enhanced Statistical Estimation of Air Temperature Incorporating Nighttime Light Data
AbstractNear surface air temperature (Ta) is one of the most critical variables in climatology, hydrology, epidemiology, and environmental health. In situ measurements are not efficient for characterizing spatially heterogeneous Ta, while remote sensing is a powerful tool to break this limitation. This study proposes a mapping framework for daily mean Ta using an enhanced empirical regression method based on remote sensing data. It differs from previous studies in three aspects. First, nighttime light data is introduced as a predictor (besides land surface temperature, normalized difference vegetation index, impervious surface area, black sky albedo, normalized difference water index, elevation, and duration of daylight) considering the urbanization-induced Ta increase over a large area. Second, independent components are extracted using principal component analysis considering the correlations among the above predictors. Third, a composite sinusoidal coefficient regression is developed considering the dynamic Ta-predictor relationship. This method was performed at 333 weather stations in China during 2001–2012. Evaluation shows overall mean error of −0.01 K, root mean square error (RMSE) of 2.53 K, correlation coefficient (R2) of 0.96, and average uncertainty of 0.21 K. Model inter-comparison shows that this method outperforms six additional empirical regressions that have not incorporated nighttime light data or considered predictor independence or coefficient dynamics (by 0.18–2.60 K in RMSE and 0.00–0.15 in R2). View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Chen, Y.; Quan, J.; Zhan, W.; Guo, Z. Enhanced Statistical Estimation of Air Temperature Incorporating Nighttime Light Data. Remote Sens. 2016, 8, 656.
Chen Y, Quan J, Zhan W, Guo Z. Enhanced Statistical Estimation of Air Temperature Incorporating Nighttime Light Data. Remote Sensing. 2016; 8(8):656.Chicago/Turabian Style
Chen, Yunhao; Quan, Jinling; Zhan, Wenfeng; Guo, Zheng. 2016. "Enhanced Statistical Estimation of Air Temperature Incorporating Nighttime Light Data." Remote Sens. 8, no. 8: 656.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.