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57 lines
2.5 KiB
Markdown
57 lines
2.5 KiB
Markdown
# Remote Sensing for Journalism
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This repository contains a series of notebooks describing interaction with the Copernicus Open Acces Hub in order to obtain and manipulate earth observation data.
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The aim is to document common tasks that might make the data from the Copernicus Sentinel missions attractive for usage in data journalism reporting.
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The publication and research uses [Jupyter notebooks](https://jupyter.org) and is published using [jupyter-books](https://jupyter-book.org), an open-source python project that allows generating HTML pages from a collection of Jupyter notebooks.
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## Copernicus Open Access Hub
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Copernicus Open Access Hub is the platform which is openly distributing the Terrabytes of Sentinel-2 data which these notebooks rely on.
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A (free) Scihub account is needed in order to follow this documentation interactively.
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The registration form can be found at https://scihub.copernicus.eu/dhus/.
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## Obtaining and Running the Code
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The source code lives at https://github.com/heyarne/remote-sensing-for-journalism.
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A `Dockerfile` is present at the root of the repository to help with reproducing the computing environment.
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The image can be built by running the following command from the project root:
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``` bash
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docker build . -t eratosthenes:latest
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```
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When running the docker image you need to define your Scihub user credentials as environment variables:
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``` bash
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docker run -it \
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--name eratosthenes \
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--net host \
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--volume "$(pwd)":/home/jovyan \
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-e SCIHUB_USERNAME='<username>' \
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-e SCIHUB_PASSWORD='<password>' \
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eratosthenes:latest
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```
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This starts up a `JupyterLab` environment which allows you to interactively execute all notebooks and modify them to suit your needs.
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The Docker image is based on the [jupyter/scipy-notebook](https://github.com/jupyter/docker-stacks/tree/master/scipy-notebook).
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Follow the link for more information on installed packages or other configuration details.
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## Hardware Requirements
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Note that working with this kind of data is resource intensive.
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These notebooks download or create roughly 50GB of data, most of which is occupied by compressed GeoTIFF files.
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They have been executed and tested on a virtual server with 4 CPU cores at 2.6 GHz each and 32 GB of RAM.
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## Building the Jupyter Book
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The `jupyter-book` dependency is included in the `Dockerfile`.
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You can build a book from a running container by executing the following command on the Docker host:
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```
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docker run -it eratosthenes jupyter-book build .
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```
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The resulting book can be found in the directory `_build/html/`.
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