TSDP: Automatic preprocessing and downloading of Landsat 1–9, Sentinel-2, and other remote sensing data for multi-resolution time-series image analysis

The Time-Series Data Downloader and Preprocessor (TSDP) is an open-source Python tool designed to streamline the acquisition and preprocessing of multispectral satellite imagery for time-series analysis. Built on Google Earth Engine (GEE), TSDP supports Landsat 1–9—from Landsat MSS to Landsat OLI—as well as Sentinel-2 imagery, GEDI canopy height and biomass products, and the recently released Google Satellite Embedding dataset. TSDP applies a consistent set of preprocessing routines across all optical sensors—including automatic image filtering, cloud, snow, and smoke masking, and topographic correction—generating analysis-ready time series spanning 1972 to the present. The tool integrates recent advances such as the Cloud Score+ algorithm for improved cloud detection in Sentinel-2 imagery and implements the SCS+C method for topographic correction using user-selectable digital elevation models (DEMs). TSDP prioritizes data quality by downloading imagery at its native spatial resolution and, in most cases, avoiding spatial resampling. This approach makes it particularly well suited for developing multi-resolution and multisource methods—an emerging direction in remote sensing for long-term environmental monitoring, land-cover change detection, and vegetation dynamics research. This technical note describes the tool’s functionalities, input parameters, processing workflow, and outputs, providing guidance for users who wish to generate high-quality time series datasets from publicly available satellite archives.