Evaluating the applicability of landsat 8 data for global time series analysis

Introduction Factors such as (1) the number of satellite images available for a specific study and (2), the applicability of these images in terms of cloud cover, can reduce the overall accuracy of time series studies from earth observation. In this context, the Landsat 8 dataset stands out as one of the most widely used and versatile datasets for time series analysis, building on the strengths of its predecessors with its advanced features. However, despite these enhancements, there is a significant gap in the literature regarding a comprehensive assessment of Landsat 8’s performance. Specifically, there is a need for a detailed evaluation of image availability and cloud cover percentages across various global paths and rows. Methods To address this gap, we utilized the Landsat 8 Collection 2 dataset available through Google Earth Engine (GEE). Our approach involved filtering the dataset to focus on Landsat 8 images captured between 2014 and 2023 across all paths and rows. Using the Earth Engine Python API, we accessed and processed this data, extracting key information such as the number of available images and their associated cloud cover percentages. Results and Discussion Our analysis of Landsat 8 image availability revealed that regions such as Australia, parts of Africa, the Middle East, Western Asia, and Southern North America benefit from a higher frequency of Landsat imagery, while Northern Asia and Northern North America have fewer images available. Latitude-specific trends show that areas between 55 and 82 degrees receive notably fewer images. We also found that regions like central Australia, northern Africa, and the Middle East generally experience lower cloud cover, while central Africa, and northern parts of Asia, Europe, and North America have higher cloudiness. Latitudinal trends show a significant drop in cloud cover from approximately 90% at latitudes -60 to -20 degrees to below 10%, with a rise near the Equator. Cloud cover decreases again from 0 to 20 degrees latitude but increases between 20 and 60 degrees. Europe has the highest average cloud cover at 42.5%, impacting image clarity, whereas Africa has the lowest average at 23.3%, indicating clearer satellite imagery.