PyGEE-SWToolbox: A Python Jupyter Notebook Toolbox for Interactive Surface Water Mapping and Analysis Using Google Earth Engine

Continuous monitoring of surface water resources is often challenging due to the lack of monitoring systems in remote areas and the high spatial distribution of water bodies. The Google Earth Engine (GEE) platform, which houses a large set of remote sensing datasets and geospatial processing power, has been applied in various aspects of surface water resources monitoring to solve some of the challenges. PyGEE-SWToolbox is a freely available Google Earth Engine-enabled open-source toolbox developed with Python to be run in Jupyter Notebooks that provides an easy-to-use graphical user interface (GUI) that enables the user to obtain time series of Landsat, Sentinel-1, and Sentinel-2 satellite imagery, pre-process them, and extract surface water using water indices, such as the Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Automated Water Extraction Index (AWEI), and Dynamic Surface Water Extent (DSWE). The validation of the toolbox is carried out at four reservoir and lake locations: Elephant Butte Lake, Hubbard Creek Reservoir, Clearwater Lake, and Neversink Reservoir in the United States. A time series of the water surface area generated from PyGEE-SWToolbox compared to the observed surface areas yielded good results, with R 2 ranging between 0.63 and 0.99 for Elephant Butte Lake, Hubbard Creek Reservoir, and Clearwater Lake except the Neversink Reservoir with a maximum R 2 of 0.52. The purpose of PyGEE-SWToolbox is to provide water resource managers, engineers, researchers, and students a user-friendly environment to utilize the GEE platform for water resource monitoring and generation of datasets. The toolbox is accompanied by a step-by-step user manual and Readme documentation for installation and usage.