A Google Earth Engine Application to Retrieve Long-Term Surface Temperature for Small Lakes. Case: San Pedro Lagoons, Chile

Remote Sensing

Óscar Parra¹  María Pedreros-Guarda²  Rodrigo Abarca-del-Río³  Ignacio García³  Karen Escalona⁴ 

[1] EULA-Chile and Faculty of Environmental Sciences, University of Concepción, Concepción 4030000, Chile;Environmental Sciences with Mention in Continental Aquatic Systems, Aquatic Systems Department, Faculty of Environmental Sciences, University of Concepción, Concepción 4030000, Chile;Geophysics Department, Faculty of Physical Sciences and Mathematics, University of Concepción, Concepción 4030000, Chile;Physical Sciences, Faculty of Physical Sciences and Mathematics, University of Concepción, Concepción 4030000, Chile;

关键词: water surface temperature;    Google Earth Engine;    lakes;    remote sensing;    Landsat;   

DOI  :  10.3390/rs13224544

来源: DOAJ

【 摘 要 】

Lake surface water temperature (LSWT) is a crucial water quality parameter that modulates many lake and reservoir processes. Therefore, it is necessary to monitor it from a long-term perspective. Over the last decades, many methods to retrieve LSWT fields from satellite imagery have been developed. This work aims to test, implement and automate six methods. These are performed in the Google Earth Engine (GEE) platform, using 30 m spatial resolution images from Landsat 7 and 8 satellites for 2000–2020. Automated methods deliver long-term time series. Series are then calibrated with in situ data. Two-dimensional (2D) × time data fields are built on the lakes with the calibration, and a subsequent LSWT climatology is derived. Our study area is two urban lagoons with areas smaller than two (2) km${}^2$ of the city of San Pedro de la Paz, South-Central Chile. The six methods describe the seasonal variation of LSWT (Willmott’s index of agreement > 0.91, $R^2$ > 0.67). The main difference between series is their bias. Thus, after a simple calibration, all series adequately describe the LSWT. We utilized the Pedro de la Paz lagoons to demonstrate the method’s utility. Our research demonstrates that these adjacent lagoons exhibit comparable LSWT spatial (15.5–17 ${}^{\circ }$C) and temporal (7–25 ${}^{\circ }$C) trends throughout the year. Differences in geographical pattern might result from the northern island’s heat impact and the existence of the Biobío river to the east. Our work represents an efficient alternative for obtaining LSWT in particular lakes and reservoirs, especially useful in medium and small-sized ones.

【 授权许可】

Unknown