Planet Utilities - A Python Package for Efficient Processing and Analysis of PlanetScope Satellite Data

The increasing availability of high-resolution satellite data, such as PlanetScope, offers immense potential for a wide range of Earth observation applications. However, effectively handling and analyzing such data can be challenging for researchers. To address this issue, we introduce "Planet Utilities," a Python package designed to streamline the processing and analysis of PlanetScope satellite data. The Planet Utilities package offers a comprehensive set of functions and modules to extract metadata, read digital numbers (DN) and reflectance data, plot true color composite images, reproject data, and apply supervised classification for mask generation. This package enables to select the training samples, reflectance and the texture information, for different classses for machine learning training. Additionally, the package includes modules for data validation and feature extraction, further enhancing its utility for scientific research and remote sensing applications.

The Planet Utilities package caters to users at various skill levels, providing a user-friendly interface for novices while offering customization options for advanced users. With an extensive collection of examples and tutorials, users can quickly grasp the package's functionalities and integrate them into their workflows seamlessly. We demonstrate the effectiveness and efficiency of Planet Utilities through a series of use cases, including image processing, data visualization, and supervised classification. The package's modular design and versatile functionalities make it a valuable tool for researchers, students, and practitioners in fields such as environmental monitoring, land cover classification, and ecosystem analysis.

By making the handling and analysis of PlanetScope satellite data simpler, we hope to promote collaboration and support data-driven discoveries using this Python module. Due to the open-source nature of the Planet Utilities package and its availability on GitHub, the community is constantly able to add to, enhance, and expand its capabilities.