Bathymetry Database

The Bathymetry Database module is used to import bathymetric data from the Delft Dashboard OPeNDAP server at Deltares.

Getting started

It is required that you have or create a database folder in which bathymetric tiles can be cached. For Delft Dashboard users, the path is typically something like:

d:\\delftdashboard\\data\\bathymetry

The Bathymetry Database can be initialized like this:

from cht.bathymetry_database import BathymetryDatabase

bdb = BathymetryDatabase("d:\\delftdashboard\\data\\bathymetry")

Importing bathymetry

Bathymetry data can now be downloaded using the get_data method. You’ll need to prescribe the dataset name, the limits (bounding box), and the minimum resolution for of the requested data. For example, if you wish to obtain gridded bathymetry data from GEBCO19 for an area in the Gulf of Mexico with a maximum cell size of 500 metres, you can do:

x, y, z = bdb.get_data('gebco19',
                       xlim=[-85.0, -80.0],
                       ylim=[ 28.0,  34.0],
                       max_cell_size=500.0)

This will return the 1D Numpy arrays x and y containing the horizontal coordinates of the data, and a 2D NumPy array z which contains the vertical elevation data.

THE NEXT BIT HAS NOT YET BEEN IMPLEMENTED !!!

You can also import gridded data in a coordinate reference system (CRS) other than the native CRS of the requested data. In this case, you’ll need to define the grid spacing dx an dy, as well as the name of the requested CRS. The raw bathymetric data will be interpolated onto the grid specified by you.

x, y, z = bdb.get_data('gebco19',
                       xlim=[ 420000.0,  460000.0],
                       ylim=[3320000.0, 3420000.0],
                       dx=200.0,
                       dy=200.0,
                       crs='WGS 84 / UTM zone 17N')

Note

If you do NOT prescribe a CRS, please ensure that xlim and ylim are specified in the native CRS of the requested dataset !

Obtaining a list of available datasets

You can show a list of available datasets with:

for dataset in bdb.dataset:
    print(dataset.name)

Obtaining meta-data for a dataset

Meta data of a dataset are stored as attributes of the class Dataset.

print(bdb.get_metadata('gebco19', variable='crs'))

You can also do this:

ds = bdb.get_dataset('gebco19')
print(ds.crs)

Module

Classes

class cht.bathymetry_database.BathymetryDatabase(pth)

The main Bathymetry Database class

Parameters: pth (string) – Path name where bathymetry tiles will be cached.

get_crs(dataset_name)

Returns coordinate reference system (CRS) of dataset

Parameters: dataset_name (str) – Name of requested bathymetry dataset.
Returns: CRS
Return type: str

get_data(dataset_name, xlim, ylim, max_cell_size)

Returns imported data from database

Parameters

dataset_name (str) – Name of requested bathymetry dataset.
xlim (list) – x-limits.
y_lim (list) – y-limits.
max_cell_size (float, optional) – Maximum cell size (in metres)
dx (float, optional) – dx
dx – dy
crs (str, optional) – name of coordinate reference system

read(): Reads meta-data of all datasets in the database.

class cht.bathymetry_database.BathymetryDataset

Bathymetry dataset class

Variables

name – initial value: ‘’
nr_zoom_levels – initial value: 0

get_data(xlim, ylim, max_cell_size): Reads data from database Returns x, y, z

read_data_from_netcdf_tiles(xl, yl, izoom, max_cell_size): Reads data from database Returns x, y, z