https://github.com/mxagar/space_exploration
This repository is a collection of mini-projects and tutorials related to space images and geo-spatial data.
https://github.com/mxagar/space_exploration
data-analysis deep-learning geospatial machine-learning
Last synced: 9 months ago
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This repository is a collection of mini-projects and tutorials related to space images and geo-spatial data.
- Host: GitHub
- URL: https://github.com/mxagar/space_exploration
- Owner: mxagar
- License: gpl-3.0
- Created: 2023-03-14T06:13:33.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-05-02T08:12:55.000Z (about 3 years ago)
- Last Synced: 2025-04-09T20:47:45.888Z (about 1 year ago)
- Topics: data-analysis, deep-learning, geospatial, machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 24 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# Space Exploration
This repository is a collection of mini-projects and tutorials related to space images and geo-spatial data. It is a sandbox where I'll try tools and techniques; as such, it will grow organically.
Each mini-project has a dedicated folder with a `README.md`. Datasets should be contained in `data`, however, image data is usually not commited; instead, I provide the necessary download links.
## Contents
- [`space_image_classification`](./space_image_classification/): CNN which classifies space images from [Satellite Image Classification](https://www.kaggle.com/datasets/mahmoudreda55/satellite-image-classification); RBG images are used and the classification is per image.
- [`geospatial_data_guide`](./geospatial_data_guide/): a guide on how to visualize and work with geospatial data, based on two courses from Datacamp:
- [Visualizing Geospatial Data in Python](https://app.datacamp.com/learn/courses/visualizing-geospatial-data-in-python)
- [Working with Geospatial Data in Python](https://app.datacamp.com/learn/courses/working-with-geospatial-data-in-python)
- [`satellite_image_analysis`](./satellite_image_analysis): classification, clustering and dimensionality reduction examples with satellite images; images with several bands (channels) are processed and the ML techniques are applied pixel-wise. The examples come originally from [syamkakarla98/Satellite_Imagery_Analysis](https://github.com/syamkakarla98/Satellite_Imagery_Analysis).
## Requirements
The notebooks can be opened with Google Colab (if link provided in each notebook) or in a dedicated environment. A brief recipe to set one up using [conda](https://docs.conda.io/en/latest/) is the following:
```bash
# Create and activate e
conda create --name ds pip python=3.7
conda activate ds
# Install pip dependencies
pip install -r requirements.txt
```
## Authorship
Mikel Sagardia, 2023.
No guarantees.
If you find this repository useful and use it, please, cite the original source. This work is protected by the GPL-3.0 license; see [`LICENSE.md`](LICENSE.md) for more information.