An Open-Source Tool for Updating ICESat-2 ATL03 Land-Sea Masks with High-Resolution Shoreline Datasets

Title: An Open-Source Tool for Updating ICESat-2 ATL03 Land-Sea Masks with High-Resolution Shoreline Datasets

Abstract: The NASA Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) employs precise lasers to measure Earth's surface elevation through photon data. This data is particularly valuable in remote locations where traditional surveying methods are either expensive or less feasible. For example, it can reveal critical insights into ocean conditions globally. However, despite the availability of some methods for land/sea classification based on photon data, these techniques often require extensive efforts. The absence of a standardized method for transforming photon data into actionable land/sea measurements makes it difficult for both ocean and terrestrial communities, especially new users, to utilize ICESat-2 data. To address this gap, we introduce SeaLandIdentifier, an open-source Python tool designed to simplify the process of labeling land/sea and extracting ICESat-2 data. By linking ICESat-2 photon data with existing updated high-resolution land-sea mask datasets, SeaLandIdentifier enables users to visualize photon returns alongside coincident shoreline data for accurate inspection. Our work aims to eliminate obstacles when scientists prepare high-resolution ICESat-2 data over land or sea. SeaLandIdentifier is expected to be a key tool for the development of future "Ancillary Masks" products for ICESat-2 data, thereby promoting more efficient and user-friendly land/sea classification.