Code to automate some useful beach analysis tasks.
First time, open Anaconda Prompt and run the following:
conda env create --file BeachProfileTools.yml
All other times, activate this environment first:
conda activate BeachProfileTools
Currently there are three modules that can be imported (import .... as ....).
import dem_to_shoreline as dts
dts.lidar_dem_to_shoreline(dem_path,
contour_path,
shoreline_path,
no_data_value=-9999,
filter_extra=False):
"""
Uses gdal to take a raster DEM (.tif, .img, Esri grids, etc.)
and generate contours. Then extracts the 0 contour as the shoreline.
If data includes areas that have low spots other than the shore
(ex: ponds inland from dune), then can filter out the longest 0 contour as shoreline.
inputs:
dem_path: path to the dem (str)
contour_path: path to save all of the contours to, end this with .shp (str)
shoreline_path: path to save the 0 contour to, end with .shp (str)
no_data_value (optional, default=-9999): the no data value for the raster
filter_extra (optional, default=False): If set to True, will only save the longest 0 contour to the shoreline file
"""
import generating_transects as gen_tr
gen_tr.make_transects(input_path,
transect_spacing,
transect_length):
"""
Generates normal transects to an input line shapefile
inputs:
input_path: path to shapefile containing the input line
transect_spacing: distance between each transect in meters
transect_length: length of each transect in meters
outputs:
output_path: path to output shapefile containing transects
import profile_raster
profile_raster.main(in_raster, in_line, csv_file, res, NO_DATA, batch=False):
"""
Extracts elevation profile given an input raster dem and an input shapefile line
inputs:
in_raster: path to raster dem
in_line: path to shapefile profile line
csv_file: path to save extracted distance, elevation pairs to
res: resolution to sample at in meters
N0_DATA: raster no data value
batch (optional): this should stay as False if just one profile is taken, use batch_main function for multiple profiles
"""
profile_raster.batch_main(in_raster, in_lines, out_folder, res, NO_DATA):
"""
Repeatedly take elevation profiles from a raster dem with an input shapefile containing all of the lines
inputs:
in_raster: path to raster dem
in_lines: path to shapefile containing profile lines
out_folder: path to folder to save csvs and png figures to
res: resolution to sample at in meters
NO_DATA: no data value for raster
"""
profile_raster.main_raster(in_rasters, in_line, save_folder, res, NO_DATA, batch=False):
"""
Extracts elevation profile given multiple input raster dems and an input shapefile line
inputs:
in_raster_folder: list containing paths to raster dems
in_line: path to shapefile profile line
csv_folder: path to save results to (csvs, png figure)
res: resolution to sample at in meters
N0_DATA: raster no data value
batch (optional): this should stay as False if just one profile is taken, use batch_main_raster function for multiple profiles
"""
profile_raster.batch_main_raster(in_rasters, in_lines, save_folder, res, NO_DATA, batch=True):
"""
Extracts elevation profiles given multiple input raster dems and an input shapefile containing mutliple lines
inputs:
in_raster_folder: list containing paths to raster dems
in_line: path to shapefile containing profile lines
save_folder: path to save results to (csvs, png figure)
res: resolution to sample at in meters
N0_DATA: raster no data value
batch (optional): this should stay as False if just one profile is taken, use batch_main function for multiple profiles
"""
This module generates timeseries data and figures for shoreline change.
You need a shapefile with timestamped shorelines and a shapefile with one or multiple transects (for multiple, use the batch function).
The intersection points between each shoreline and the transect are computed. Then the cross-shore distance for each point is computed.
The earliest time shoreline intersection point is taken as the origin.
Outputs a figure of the timeseries and a csv with the data (time, eastings, northings, cross-shore distance).
Shown below is some fake data for Cape Henlopen, where I made some shorelines that are migrating inward over time:
Batch function will output data and a figure for multiple transects.
import shoreline_timeseries as sts
sts.transect_timeseries(shoreline_shapefile,
transect_shapefile,
sitename,
transect_id,
output_folder,
switch_dir=False,
batch=False):
"""
Generates timeseries of shoreline cross-shore position
given a shapefile containing shorelines and a shapefile containing
a cross-shore transect. Computes interesection points between shorelines
and transect. Uses earliest shoreline intersection point as origin.
inputs:
shoreline_shapefile (str): path to shapefile containing shorelines
(needs a field 'datetime' YYYY-MM-DD-HH-MM)
transect_shapefile (str): path to shapefile containing cross-shore transect
sitename (str): name of site
transect_id (int): integer id for transect
output_folder (str): path to save csv and png figure to
switch_dir (optional): default is False, set to True if transects are in the opposite direction
batch (optional): default is False, this gets set to True when batch function is used
"""
sts.batch_transect_timeseries(shorelines,
transects,
sitename,
output_folder,
switch_dir=False):
"""
Generates timeseries of shoreline cross-shore position
given a shapefile containing shorelines and a shapefile containing
cross-shore transects. Computes interesection points between shorelines
and transects. Uses earliest shoreline intersection point as origin.
inputs:
shoreline_shapefile (str): path to shapefile containing shorelines
(needs a field 'datetime' YYYY-MM-DD-HH-MM)
transect_shapefile (str): path to shapefile containing cross-shore transects
sitename (str): name of site
output_folder (str): path to save csvs and png figures to
switch_dir (optional): default is False, set to True if transects are in the opposite direction
"""