Raster-Basics

Basic geoprocessing tools to handle geotiff and shapefile data

Contains some additional tools for basic glacier calculations and plotting

Installation

Activate the desired python or conda environment, then enter pip install raster_basics

To import the modules, type import raster_basics or import specific functions with from raster_basics.RasterBasics import function

If you've already downloaded the module, enter sudo pip install raster_basics --upgrade while in the conda environment to upgrade to the newest version

All of the functions can be imported with:

• from raster_basics.RasterBasics import rOpen, show_fig, show_fig_subplot, rasterLike, rasterMath
• from raster_basics.RasterBasics import shpReprojection, shpClip, tifReprojectionResample, reproject_velocity, fillHole, mosaic_files
• from raster_basics.RasterBasics import extract_along_line,points_along_lines, end_points

Installing Dependencies

Dependencies are automatically installed when raster_basics is downloaded via PyPI. Dependencies can otherwise be installed via the requirements.txt file. Download the file, navigate to it's directory in the terminal, and install dependencies by typing pip install -r requirements.txt or conda install --file requirements.txt. If creating a new conda environment for raster_basics, you may also need to conda install pip initially. This should install all the dependencies needed to run the raster_basics module.

Using raster_basics

The raster_basics module can be used in Jupyter Notebooks or any IDE. Simply import the desired functions to use them. An example of use can be found in the rasterio_basics-package.ipynb, velocity_reprojection.ipynb, wolverine_index_site_method.ipynb, and gulkana_flux_gate_method.ipynb notebooks.

Functions

• rOpen: open a geotiff file as an array, and/or get the geotiff resolution and coordinate system
• show_fig: show geotiff as a matplotlib figure
• show_fig_subplot: shows multiple geotiff or array-like figures
• rasterLike: save array as a raster
• shpReprojection: reproject shapefile
• shpBuffer: add a buffer to shapefile
• shpClip: clip geotiff by a shapefile
• tifReprojectionResample: reproject, resample, and/or clip geotiff
• reproject_velocity: reproject velocity data
• rasterMath: perform basic arithmetic on two raster files (even if they have difference crs, res, and/or extents)
• fillHole: fill missing data in geotiff
• fillArrayHole: helper function for fillHole, but works directly with arrays
• mosaic_files: mosaic two or more geotiffs together
• extract_along_line: sample for points on a line (this uses geocoordinate points as line)
• points_along_lines: sample for points on a line (this uses a shapefile line)
• end_points: obtain raster values at point locations
• distance_to_shp: gets the distance from every pixel to a shapefile

Testing and Tutorials

After installing raster_basics into a virtual environment, create a Jupyter Notebook kernel to use the example notebooks. In the terminal, enter python -m ipykernel install --user --name raster_basics_kernel (the last entry can be any desired kernel name). Then, launch the Jupyter with jupyter notebook. In the browser tab, navigate to examples and open the desired notebook.

Follow the Jupyter Notebooks in the examples folder to see how functions can be used. Access to the sample data used in the tutorial can be found by following the links in the notebooks. Run the notebook code in the same folder as the data.

Other functions in the package

There are a few more functions to help produce specific plots and glacier calculations. These can be imported with:

• from raster_basics.GlacierFunctions import FUNCTION_NAME
• from raster_basics.BaseFunctions import FUNCTION_NAME
• from raster_basics.DataPlots import FUNCTION_NAME
• from raster_basics.SmoothingFunctions import FUNCTION_NAME
• from raster_basics.NoiseFunctions import FUNCTION_NAME

where FUNCTION_NAME is the name of the desired function.

Example Glacier Functions

• glacierArea: get the area of a glacier
• totalMassBalance: get the total mass change on a glacier (pixel by pixel)
• totalMassBalanceValue: get the total mass change on a glacier (area-sum of pixels)
• divQ: get the flux divergence
• glacierSlope: alternate function to obtain the riserun or degree slope from an array
• demHillshade: create a hillshade from a DEM
• velocityAspect: returns the aspect of velocity based on vx and vy
• velAspectAngle: get the angle between two arrays of velocity aspect
• velFlowlineAspect: return the aspect of every pixel based on a shapely geometry flowline
• velFlowlineOutlineAspect: return the aspect of every pixel based on a shapely geometry flowline and outline
• particle_flow: track the position of a particle based on velocity arrays
• distance_from_line: get an array representing the distance of every pixel from any True value in an array

Example Base Functions

• glacierOutline: uses a shapefile and raster array of ones to create a binary array of glacier terrain (1 is glacier, 0 is off-glacier)
• altitudeAggregation: returns statistics for a desired statistic in an elevation bin, bin boundaries, count, number, standar deviation, min, and max
• binPercentile: returns binned statistics value at a desired percentile of a bin (e.g. 25th percentile MB value per elevation bin)
• latlonTiffIndex: obtain raster array index values from a lat/lon coordinate pair

Example Plotting Functions

Note that all of these plotting functions only save the image if savefig=True (by default, it is set to False).

• plotData: another method to plot an array. Can handle quiver inputs for arrows on velocity plots (quiver input from velPlot function)
• plotData3: same as plotData but places 3 plots side-by-side
• plotMany: an arbitrary number of plots side-by-side in a grid
• elevationBinPlot: plots two sets of data: line plot for MB and horizontal bar graph for elevation bin size
• elevationBinPlot3Subfigs: plots elevationBinPlot along with 3 more subplots from desired input arrays
• plotDataPoints: plots labeled data points on top of an array basemap. This is used to plot stake locations, for example
• plotDataPoints2: identical to plotDataPoints, but plots two maps side-by-side
• velPlot: this does no actually plot anything. Rather, it returns the quiver input needed to plot velocity arrows in other functions such as plotData
• plotClassify: plot array with discrete values
• plotContinuous: plot array with continuous values
• plot_binned_data: returns a data array with values corresponding to alitudinally-aggregated elevation bins

Example Smoothing Functions

• sgolay2d: Savitzky-Golay smoothing filter to eliminate high frequency noise via moving average; a low-pass filter
• gaussianFilter: Gaussian (normal) smoothing filter
• dynamicSmoothing: Gaussian filter, dynamic smoothing with changing pixel window size
• dynamicSmoothingExponential: Exponential filter, dynamic smoothing with changing pixel window size
• add_array_border: Helper function to add a border around an array in dynamicSmoothing and dynamicSmoothingExponential
• smoothingCorrection: Apply a correction to smoothed data products, such that smoothing does not decrease the mean values Correction is based on glacier centerline values
• distance_scaling_correction: corrects a smoothed data products based on a scaling from relative distance from centerline

Example Noise Functions

• add_grf_noise: Introduce spatially-correlated noise via Gaussian random fields
• add_ice_thickness_bias: Add ice thickness bias based on parabolic vs V-shape bed cross-section assumption