Estimation of satellite-derived lake water surface temperatures in the western Mediterranean: Integrating multi-source, multi-resolution imagery and a long-term field dataset using a time series approach

被引:17
作者
Virdis, Salvatore G. P. [1 ]
Soodcharoen, Nooch [1 ]
Luglie, Antonella [2 ]
Padedda, Bachisio M. [2 ]
机构
[1] Asian Inst Technol, Sch Engn & Technol, Dept Informat & Commun Technol, POB 4,58 Moo 9,Km 42, Klongluang 12120, Pathum Thani, Thailand
[2] Univ Sassari, Dept Architecture Design & Urban Planning DADU, Via Piandanna 4, I-07100 Sassari, Italy
关键词
LSWT; In situ long-term dataset; Mediterranean Sea; Climate change; Time series; Nash-Sutcliffe efficiency; Mann-Kendall test; Sen's slope; CLIMATE-CHANGE; FRESH-WATER; RETRIEVAL METHODS; VALIDATION; TRENDS; PRECIPITATION; REGRESSION; PATTERNS; PRODUCT;
D O I
10.1016/j.scitotenv.2019.135567
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Lake surface water temperature (LSWT) is a key parameter to help study the environmental and ecological impacts of climate change. In this work, we measured the LSWT of 1 natural and 23 artificial lakes located on the island of Sardinia in the western Mediterranean, which is a region where changes in climate are projected to have significant impacts. By integrating multi-source and multi-resolution datasets of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat and long-term in situ temperature observations, we detected, measured, and analysed the LSWT trends during the period of 2000-2018 across all the investigated lakes. Methodologically, we demonstrated that a simplified approached based on Planck's equation for Landsat thermal infrared (TIR) data could be a valid alternative to radiative transfer equation retrieval methods for the retrieval of LSWT without loss of accuracy. Moreover, we demonstrated that rescaled and independently validated MOD112A-derived LSWT showed good accuracy, efficiently filled the spatial and temporal gaps in long-term in situ LSWT, and could be used for long-term LSWT trend detection and measurement. All 24 lakes showed an annual warming trend of +0.010 degrees C/y, warming winter trend of +0.013 degrees C/y, and cooling summer trend of -0.038 degrees C/y during the period of 2000-2018. This study demonstrated that the measured trend rates could be explained by and were strongly correlated with the climatology of Italy for the 2000-2018 period. Finally, we demonstrated the key role and the importance of the availability of long-term in situ temperature datasets. The approach used in this study is up-scalable to other medium to low-resolution TIR sensors as well as to other long-term monitoring sites, such as LTER-Italy, LTER-Europe, or ILTER sites. (C) 2018 Elsevier B.V. All rights reserved.
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页数:12
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