The differences, advantages, and disadvantages of various image compositing methods on the Google Earth Engine platform: an exploration

Google Earth Engine (GEE) is a cloud-based platform that provides powerful capabilities for remote sensing image compositing, processing, and analysis. Among GEE’s diverse applications, temporal aggregation of multiple images is one of its widely used techniques. Nevertheless, a systematic exploration of the advantages and disadvantages of its five primary image compositing methods – minimum (Min), maximum (Max), Median, Mean, and Mode – has not been conducted. It remains unclear whether the commonly used Median method is genuinely universal. Additionally, it is usually unknown which input images and their seasonal origins predominantly contribute to the final composite image. Therefore, this study systematically explores the performance of the five compositing methods across four regions in China and Uganda, with different geographic locations and climatic conditions, by examining their strengths, weaknesses, and applicable scenarios. A novel quantitative metric, contribution percentage (CP), is developed to identify which input images and bands in a time series primarily contribute to the final composite image. The results show that the commonly used Median metric is not always the optimal choice. The Min and Mode methods perform better than the Median method in haze and cloudy regions, particularly in haze removal and vegetation monitoring. The Max method also exhibits superior performance in compositing thermal infrared and near-infrared images compared to the Median. Based on this study, the applicable scenarios for the five compositing methods have been clarified. Furthermore, the proposed CP metric effectively reveals the input images and bands that contribute principally to the final composite. Understanding these insights is crucial for users to choose appropriate GEE compositing methods and study plant phenology and surface thermal environments, thereby providing a foundation for the scientific application of GEE compositing methods.