rivertopo

Tools to help combine river profile data and DEMs

Background

These tools are intended to modify a DEM raster to include cross sectional data points of streams, to be able to derive cross sectional data from a DEM to use in hydraulic modelling etc..

The tools take as input a DEM raster as well as two kinds of adjustments objects:

• Stream centerline, a LineString of stream centerline (vandløbsmidte) for one stream

• Profile points, obtained from dataforsyningen.dk (Skikkelsesdata for vandløb).

The profile points are projected unto the stream centerline as reference for the interpolation of z values, which will be used for generated perpendicular lines across the centerline. The perpendicular lines will then be used for creating 3d lines across the stream with z-values using the profile points and a interp function based of the datapoints (see profile.py) as evaluation points. Then a linear/ slope like interpolation is applied over the line geometries, and the 3d lines can then be used to burned into the raster.

Example of adjustment of generated 3d lines in DEM

Installation

A Python 3 environment is required. A suitable Conda environment (here called "rivertopo") can be created with:

conda env create -n rivertopo -f environment.yml

For now, the tools support editable installation using pip. To install the tools this way, use the following command in the root directory:

pip install -e .

Test that everything works by calling pytest from the root directory:

pytest

Usage

The tools can be used for single streams with a linestring for the centerline and profile data points along this centerline, obtained from Dataforsyningen.dk

Preparing line objects for burning using cross_lines_z and cross sectional data

This module is made for creating ready to burn lines from cross sectional data gathered from Dataforsyningen.dk (skikkelsesdata for vandløb).

cross_lines_z input_points_simpel input_points_sammensat input_points_opmaalt input_polyline output_lines 

Parameter	Description
input_points_simpel	Path to gpkg file of regulatory simple profiles
input_points_sammensat	Path to gpkg file of regulatory sammensat profiles
input_points_opmaalt	Path to gpkg file of opmaalt profiles
input_polyline	Path to geoDK vandloebsmidte polyline
output_lines	Path to file to write output elevation-sampled 3D line objects to. Will be written in gpkg format

Burning the prepared vector objects into raster tile

This module is made for burning the cross sectional data created in the 2d lines the above script (cross_lines_z).

burn_line_z input_lines input_raster output_raster 

Parameter	Description
input_lines	Path or connection string to OGR-readable datasource containing the cross_lines_z 2D line objects
input_raster	Path to GDAL-readable raster dataset for input tile
output_raster	Path to write output raster tile to. Will be written in GeoTIFF format

Profile extraction along polyline

This module is made to extract profiles along a polyline e.g. a polyline over a streamlines mid. The output is npz files intended to use for plotting.

profile_extraction input_rasters input_line output_lines 

Parameter	Description
input_rasters	Path to GDAL-readable raster dataset(s) for input tile
input_line	Path to geoDK vandloebsmidte polyline
output_lines	Path to file to write output elevation-sampled 3D line objects to. Will be written in gpkg format

Profile plotting using plotly module

This module is made for 5 specific cross section files created in profile_extraction.py for 4 locations.

profile_plotting.py ex_profiles1 ex_profiles2 ex_profiles3 ex_profiles4_line1 ex_profiles5_line2

Parameter	Description
ex_profiles1	Path to first (karup.csv) npz file containing cross sectional data from profile_extraction.py
ex_profiles2	Path to second (fiskbæk.csv) npz file containing cross sectional data from profile_extraction.py
ex_profiles3	Path to third (skive.csv) npz file containing cross sectional data from profile_extraction.py
ex_profiles4_line1	Path to (indbrændt.csv) npz file containing cross sectional data from profile_extraction.py
ex_profiles5_line2	Path to (indbrændings_eksempel.csv) npz file containing cross sectional data from profile_extraction.py

Example workflow (creating and burning cross sectional data points)

As an example, the steps below illustrate preparing the relevant intermediate data and burning it into a raster tile.

Example filename	Description
test_sammensat.gpkg	Input cross sectional data of type sammensat
test_simpel.gpkg	Input cross sectional data of type simple
test_opmaalt.gpkg	Input cross sectional data of type opmaalt
cropped_vandloebsmidte.gpkg	Input vandloebsmidte polyline
LINES_WITH_Z.gpkg	Intermediate datasource of prepared 3D line objects
ORIGINAL_DTM/1km_NNNN_EEE.tif	Input raster tile for which corresponding output will be produced.
ADJUSTED_DTM/1km_NNNN_EEE.tif	Output raster tile, created from the input raster tile with 3D lines burned in

Prepare lines with cross sectional data points:

cross_lines_z test_simpel.gpkg test_sammensat.gpkg test_opmaalt.gpkg cropped_vandloebsmidte.gpkg LINES_WITH_Z.gpkg 

Create the adjusted DEM tile from the 3d lines and the original DEM tile:

burn_line_z LINES_WITH_Z.gpkg ORIGINAL_DTM/1km_NNNN_EEE.tif ADJUSTED_DTM/1km_NNNN_EEE.tif 

Example workflow (extracting and plotting profiles from DEM tile)

Prepare and extract profiles to a npz file on polyline:

profile_extraction ORIGINAL_DTM/1km_NNNN_EEE.tif cropped_vandloebsmidte.gpkg 

Now the npz file can be used in the plotting module. It is currently set up to plot the 5 example case files:

profile_plotting.py karup.csv skive.csv fiskbæk.csv indbrændt.csv indbrændt_eksempel.csv