Python Library & CLI¶
The Python package
planet is an Apache
Python client library and command-line interface for working with Planet's public API.
To install, run
pip install planet anywhere that Python 2.7 or Python 3.4+ is installed.
The Developer Experience team at Planet has created a collection of Apache 2.0-licensed Jupyter Notebooks, along with a Docker image that makes it easy to run your own geospatially-enabled Jupyter instance.
The interactive guides in this collection are designed to help Python-familiar developers explore Earth observation data, work with Planet's Public API, and learn how to extract information from Planet's archive of high-cadence satellite imagery.
QGIS is the most widely-used free and open-source desktop geographic information system (GIS). Planet's Plugin for QGIS, which makes it easy for QGIS users to discover, stream and download Planet imagery, is also open source on Planet's Github.
Staccado is a Java-based catalog that implements the SpatioTemporal Asset Catalog (STAC) specification that Planet helped author. We have a number of users who maintain copies of Planet’s catalog to meet security, disaster mitigation, or latency reduction requirements, and Staccato provides an ideal, standards-based solution for these use cases.
The Planet Labs Stratus GitHub project code is no longer actively maintained. The GitHub repository has been archived.
Stratus, previously known as Boundless Server Enterprise (BSE), is an open source server for serving geospatial data. Stratus extends the core GeoServer project with cloud-native capabilities, enabling scalability through automatic provisioning of compute nodes. It replaces GeoServer’s disk-based configuration with a shared Redis datastore that is always in sync. This code is no longer actively maintained, and the repository has been archived.
In support of the International Disaster Charter, Planet make imagery of disaster areas around the globe available directly to the public, volunteers, humanitarian organizations, and other coordinating bodies. Disaster data is openly licensed under the Creative Commons: CC-BY-SA for commerical use, and CC-NC-BY for non-commerical use.