SeaCharts

Python-based API for Electronic Navigational Charts (ENC)

Features

• Read and process spatial depth data from FileGDB files into shapefiles.
• Read and process spatial depth data from S-57 files into shapefiles.
• Visualize S-57 layers.
• Access and manipulate standard geometric shapes such as points and polygon collections.
• Visualize colorful seacharts features and vessels.

Code style

This module follows the PEP8 convention for Python code.

Prerequisites - For SeaCharts 4.0 see this section

DEPRECATED - Linux (Virtual Environment)

First, ensure that you have the GDAL and GEOS libraries installed, as these are required in order to successfully install GDAL and Cartopy:

sudo apt-get install libgeos-dev libgdal-dev

From the root folder, one may then install an editable version of the package as follows:

pip install -e .

This should preferably be done inside a virtual environment in order to prevent Python packaging conflicts.

DEPRECATED - Anaconda

Install an edition of the Anaconda package manager, and then create a new conda environment with Python 3.11 or higher using e.g. the graphical user interface of PyCharm Professional as detailed here.

The required data processing libraries for spatial calculations and visualization may subsequently be installed simply by running the following commands in the terminal of your chosen environment:

conda install -c conda-forge fiona cartopy matplotlib
conda install matplotlib-scalebar cerberys pyyaml

DEPRECATED - Windows (Pipwin)

First, ensure that Python 3.11 or higher is installed. Next, install all required packages using Pipwin:

python -m pip install --upgrade pip
pip install wheel
pip install pipwin
pipwin install numpy
pipwin install gdal
pipwin install fiona
pipwin install shapely
pip install cartopy
pip install pyyaml
pip install cerberus
pip install matplotlib-scalebar

Simply copy and paste the entire block above (including the empty line) into the terminal of your virtual environment, and go get a cup of coffee while it does its thing.

Installation

After the necessary dependencies have been correctly installed, the SeaCharts package may be installed directly through the Python Package Index (PyPI) by running the following command in the terminal:

pip install seacharts

or locally inside the SeaCharts root folder as an editable package with pip install -e .

Usage

This module supports reading and processing FGDB and 'S-57' files for sea depth data.

Downloading regional datasets - FGDB

The Norwegian coastal data set used for demonstration purposes, found here. To visualize and access coastal data of Norway, follow the above link to download the Depth data (Sjøkart - Dybdedata) dataset from the Norwegian Mapping Authority by adding it to the Download queue and navigating to the separate download page. Choose one or more county areas (e.g. Møre og Romsdal), and select the EUREF89 UTM sone 33, 2d (UTM zone 33N) projection and FGDB 10.0 format. Finally, select your appropriate user group and purpose, and click Download to obtain the ZIP file(s).

Configuration and startup

Unpack the downloaded file(s) and place the extracted .gdb or 'S-57' folder in a suitable location, in which the SeaCharts setup may be configured to search. The current working directory as well as the relative data/ and data/db/ folders are included by default.

The minimal example below imports the ENC class from seacharts.enc with the default configuration found in seacharts/config.yaml, and shows the interactive SeaCharts display. Note that at least one database with spatial data (e.g. Møre og Romsdal from the Norwegian Mapping Authority) is required.

if __name__ == '__main__':

    from seacharts.enc import ENC

    enc = ENC()
    enc.display.show()

The config.yaml file specifies which file paths to open and which area to load. In the configuration file the desired map type can be specified by listring data to display - depths for 'FDGB', and layers for 'S-57'. The corresponding config_schema.yaml specifies how the required setup parameters must be provided, using cerberus.

API usage and accessing geometric shapes

After the spatial data is parsed into shapefiles during setup, geometric shapes based on the Shapely library may be accessed and manipulated through various ENC attributes. The seacharts feature layers are stored in seabed, shore and land.

if __name__ == '__main__':
    from seacharts.enc import ENC

    # Values set in user-defined 'seacharts.yaml'
    # size = 9000, 5062
    # center = 44300, 6956450
    enc = ENC("seacharts.yaml")

    print(enc.seabed[10])
    print(enc.shore)
    print(enc.land)

    enc.display.show()

Note how custom settings may be set in a user-defined .yaml-file, if its path is provided to the ENC during initialization. One may also import and create an instance of the seacharts.Config dataclass, and provide it directly to the ENC.

FGDB demonstration

S-57 demonstration

Environment visualization

The ENC.start_display method is used to show a Matplotlib figure plot of the loaded sea charts features. Zoom and pan the environment view using the mouse scroll button, and holding and dragging the plot with left click, respectively.

Dark mode may be toggled using the d key, and an optional colorbar showing the various depth legends may be toggled using the c key. Images of the currently shown display may be saved in various resolutions by pressing Control + s, Shift + s or s.

SeaCharts 4.0 setup tips

Please be aware that these setup tips require setting up Conda environment.
Possible support for pip installation will be resolved in the future.

This is a short to-do list that might come useful when setting up SeaCharts 4.0 for the first time:

1. Set up conda environment as instructed in conda_requirements.txt file
2. Use setup.ps1 (WINDOWS ONLY) to setup directory structure needed by SeaCharts or manually create directories: data, data/db and data/shapefiles
3. Download US1GC09M map via this link, and put the US1GC09M directory (found in ENC_ROOT directory) inside data/db folder.
4. Run test_seacharts_4_0.py code either by pasting code into some main.py file in root of your project directory or by running it directly (needs fixing the issues with importing seacharts in the test file)
5. After execution you can expect such image to be displayed:

For further experimentation options, look into files: `enc.py`, `config.yaml` and `config-schema.yaml` (for reference)

License

This project uses the MIT license.