Analysis updated 2026-08-15 · repo last pushed 2019-09-16
Build an app that tracks ocean temperatures using NASA satellite data.
Study climate patterns by pulling historical ocean measurements into your analysis.
Feed satellite ocean data into a machine learning model for environmental prediction.
Bulk-download ocean color datasets from NASA's processing system for offline research.
| mrvnmchm/podaacpy | 0xallam/posthog | 0xallam/search-engine | |
|---|---|---|---|
| Stars | 1 | 1 | 1 |
| Language | — | Python | C++ |
| Last pushed | 2019-09-16 | 2026-03-26 | 2023-08-23 |
| Maintenance | Dormant | Maintained | Dormant |
| Setup difficulty | moderate | moderate | hard |
| Complexity | 2/5 | 3/5 | 3/5 |
| Audience | researcher | pm founder | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires creating NASA Earthdata credentials to authenticate with PO.DAAC and OceanColor web services before retrieving data.
Podaacpy is a Python library that lets you search, retrieve, and work with NASA's vast collection of ocean and climate data. Instead of manually clicking through web portals to find satellite measurements of sea surface temperatures or ocean currents, you can write a few lines of code to pull that data directly into your project. NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) holds enormous amounts of satellite data about the oceans. This library wraps all of PO.DAAC's web services into simple Python commands. You can search for specific datasets, grab metadata about individual satellite passes, render data into image files, and download subsets of data in formats like netCDF or HDF. It also taps into NASA's OceanColor web service, so you can locate and bulk-download files from NASA's ocean data processing system. This is built for researchers, data scientists, and developers working on oceanography, climate science, or environmental monitoring. If you're building an app that tracks ocean temperatures, studying climate patterns, or need to feed satellite ocean data into a machine learning model, this library saves you from building custom integrations with NASA's APIs from scratch. The project includes Jupyter notebook examples to help you get started quickly. The library is free to use under the Apache License, though because it's government-funded software, there are export control restrictions to be aware of. It's available through standard Python package managers, making installation straightforward. The project was developed by the California Institute of Technology with NASA sponsorship, so it's an official tool rather than a community side project.
A Python library for searching, retrieving, and working with NASA's satellite ocean and climate data. It wraps NASA's ocean data web services into simple Python commands so you can pull sea surface temperatures, ocean currents, and other measurements directly into your code.
Dormant — no commits in 2+ years (last push 2019-09-16).
Free to use for any purpose, including commercial use, as long as you keep the copyright notice, however, government-funded software means export control restrictions may apply.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.