Abstract
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 R2 ranging between 0.63 and 0.99 for Elephant Butte Lake, Hubbard Creek Reservoir, and Clearwater Lake except the Neversink Reservoir with a maximum R2 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.
Highlights
Introduction published maps and institutional affilInformation on the spatial and temporal dynamics is vital to the management and protection of water resources
The significance of this study is to introduce a new open-source toolbox developed by the authors with a graphical user interface (GUI) called PyGEE-SWToolbox to support users with little to no knowledge of the use of the Google Earth Engine (GEE) platform and its coding requirements as a solution to some of the challenges faced by non-programmers in utilizing the GEE platform
This paper presents PyGEE-SWToolbox, a freely available and open-source GEE-enabled python toolbox that gives the user the ability to obtain time series of satellite imagery and process and extract surface water characteristics at any location around the world
Summary
Information on the spatial and temporal dynamics is vital to the management and protection of water resources. Given the vast spatial distribution of surface water resources, conventional methods of monitoring have become difficult and expensive, in remote areas. Remote sensing methods have been applied in monitoring of various water resources, such as flood monitoring [2], satellite-derived bathymetry [3], wetland inundation dynamics [4], shoreline extraction [5] and gap-filling of time series data [6]. Climate change is expected to have adverse impacts on water resources, which could have enormous environmental and economic implications [7]. To assess the impacts of climate change on water resources, historical baseline data on the dynamics of these iations
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