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t.rast.line: new addon to draw trend lines based on raster layers fro…
…m a strds (#1053) t.rast.line: new addon to plot trend lines based on raster layers in a space-time raster data set (strds). Optionally, separate trend lines can be plotted per raster category of a zonal layer. Co-authored-by: Veronica Andreo <veroandreo@gmail.com> Co-authored-by: Anna Petrasova <kratochanna@gmail.com>
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| MODULE_TOPDIR = ../.. | ||
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| PGM = t.rast.line | ||
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| include $(MODULE_TOPDIR)/include/Make/Script.make | ||
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| default: script |
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| <h2>DESCRIPTION</h2> | ||
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| <em>t.rast.line</em> draws trend lines of the average values of the | ||
| input raster layers in a space-time raster dataset (strds). The trend | ||
| line represents the average values of the current computational region. | ||
| The user can optionally show an error bar for each trend line | ||
| using the <b>error</b> option. The error bar can be based on the | ||
| standard deviation (SD) or standard error (SE). The user can multiply | ||
| the SD or SE to increase or decrease the width of the error band using | ||
| the <b>n</b> option. | ||
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| <p> | ||
| If a zonal raster map is provided, using the <b>zones</b> option, trend | ||
| lines are plotted for each zone (category) in the zonal raster layer. | ||
| The zonal raster should be a single, static integer raster map. | ||
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| <p> | ||
| <div align="left" style="margin: 10px"> <a href="t_rast_line_07.png"> | ||
| <img src="t_rast_line_07.png" alt="Trend lines for three land cover | ||
| categories of the FCover for the fraction of green vegetation cover for | ||
| the period 2014-2019." border="0"> </a><br><i>Trend lines (average | ||
| ± SD) for three land cover categories of the FCover for the | ||
| fraction of green vegetation cover for the period 2014-2019.</i> </div> | ||
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| <p> | ||
| The function will plot all rasters in the strds. Alternatively, the user | ||
| can select a subset of the raster layers using the WHERE conditions. | ||
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| <p> | ||
| By default, the resulting plot is displayed on a new screen. However, the | ||
| user can also save the plot to a file using the <b>output</b> option. The | ||
| format is determined by the extension given by the user. So, if output | ||
| = outputfile.png, the plot will be saved as a *png* file. The user can | ||
| set the output size (in inches) and resolution (dpi). | ||
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| <p> | ||
| There are a few plot format and layout options, including the option to | ||
| plot grid lines and the legend, rotate the labels, change the font size | ||
| of the labels, and change the date format. | ||
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| <p> | ||
| If a zonal map is provided, the lines will take the colors of the | ||
| categories on that map. If the zonal map does not have a color table, | ||
| the lines will be assigned random colors. | ||
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| <p> | ||
| The default format of the date-time labels on the x-axis depend on the | ||
| temporal granularity of the data. This can be changed by the user using | ||
| the <b>date_format</b> option. For a list of options, see the <a | ||
| href="https://strftime.org/">Python strftime cheatsheet</a>. | ||
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| <p> | ||
| The <b>where</b> options allows allows performing different selections | ||
| of maps registered in the space-time datasets. For example, with | ||
| <i>start_time < '2020-01-01'</i> the time series is limited to all maps | ||
| with a start time before the given date. For more details, see <a | ||
| href="https://grass.osgeo.org/grass83/manuals/temporalintro.html#modules-to-process-space-time-raster-datasets">this | ||
| page</a> for more details. | ||
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| <h2>NOTE</h2> | ||
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| The user can specify the number of threads to be used with the <b>nprocs</b> | ||
| parameter. However, note that parallelization does not work when the | ||
| MASK is set. If speed is an issue, it is recommended to create a new | ||
| zonal layer using, e.g., <em>r.mapcalc</em>, remove the MASK and use | ||
| the newly created zonal layer. | ||
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| <p> | ||
| The t.rast.line module operates on the raster array defined by the | ||
| current region settings, not the original extent and resolution of the | ||
| input map. See <a | ||
| href="https://grass.osgeo.org/grass-stable/manuals/r.univar.html">g.region</a> | ||
| to understand the impact of the region settings on the calculations. | ||
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| <h2>EXAMPLE</h2> | ||
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| The next two examples use the North Carolina full (NC) and North | ||
| Carolina Climate 2000-2012 data sets, which can be downloaded from (<a | ||
| href="https://grass.osgeo.org/download/data/#NorthCarolinaDataset">this | ||
| download page</a>). | ||
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| <p> | ||
| First step is to create temporal datasets <i>tempmean</i> and | ||
| <i>precip_sum</i> for the rainfall and temperature time | ||
| series respectively, as described in <a | ||
| href="http://ncsu-geoforall-lab.github.io/grass-temporal-workshop">this | ||
| tutorial</a>. These will serve as input for the examples below. The | ||
| <i>landclass_96</i> raster layer in the PERMANENT mapset of the NC | ||
| project (location) will be used as zonal map. | ||
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| <h3>Example 1</h3> | ||
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| Plot the tempmean time series. Note that you can speed up the process | ||
| considerably by making use of the cores and threads of your computer. | ||
| You can set the number of threads to be used with the <b>nprocs</b> | ||
| option. | ||
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| <p> | ||
| <div class="code"><pre> | ||
| g.region raster=2000_01_tempmean | ||
| t.rast.line input=tempmean nprocs=10 | ||
| </pre></div> | ||
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| <p> | ||
| <div align="center" style="margin: 10px"> | ||
| <img src="t_rast_line_01.png"> | ||
| </div> | ||
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| <h3>Example 2</h3> | ||
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| Plot the rainfall time series. Set the color of the line to green, and | ||
| choose the option to plot an error band based on the <i>standard | ||
| deviation</i> using the <b>error</b> option. | ||
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| <p> | ||
| <div class="code"><pre> | ||
| t.rast.line input=precip_sum error=sd line_color=0:128:0:255 nprocs=10 | ||
| </pre></div> | ||
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| <p> | ||
| <div align="center" style="margin: 10px"> | ||
| <img src="t_rast_line_02.png"> | ||
| </div> | ||
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| <h3>Example 3</h3> | ||
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| Now, compare the temporal rainfall patterns in the inland Avery County | ||
| and Brunswick County on the coast. Set the flag <b>-l</b> to include a | ||
| legend. | ||
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| <p> | ||
| <div class="code"><pre> | ||
| # Create a zonal map | ||
| echo "11 = 1 Avery | ||
| 19 = 2 Brunswick | ||
| * = NULL" > recl.txt | ||
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| r.reclass input=boundary_county_500m output=comparison_counties rules=recl.txt | ||
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| t.rast.line -l input=tempmean zones=comparison_counties error=sd nprocs=10 | ||
| </pre></div> | ||
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| <p> | ||
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| <p> | ||
| <div align="center" style="margin: 10px"> | ||
| <img src="t_rast_line_03.png"> | ||
| </div> | ||
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| <p> | ||
| Because the zonal map does not have a color table, the lines have a | ||
| random color. | ||
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| <h3>Example 4</h3> | ||
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| If you want the colors of the trend lines to match the color of the | ||
| zonal categories, make sure to define the category colors. | ||
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| <p> | ||
| <div class="code"><pre> | ||
| # Define colors | ||
| echo "1 purple | ||
| 2 green"> color_rules.txt | ||
| r.colors map=comparison_counties rules=color_rules.txt | ||
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| # Create the plot | ||
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| t.rast.line -l -g input=tempmean zones=comparison_counties error=sd nprocs=10 | ||
| </pre></div> | ||
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| <p> | ||
| Whether this was the right color choice is debatable, but, the colors | ||
| of the graph match those of the zones of the map. Note that with the | ||
| <b>-g</b>, vertical grid lines are drawn. | ||
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| <p> | ||
| <div align="center" style="margin: 10px"> | ||
| <img src="t_rast_line_04c.png"> | ||
| </div> | ||
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| <h3>Example 5</h3> | ||
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| You can zoom in on a specific period using the <b>where</b> option. | ||
| For example, to plot the trend line for the time period 01-01-2004 to | ||
| 01-01-2010, you can use the following: | ||
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| <p> | ||
| <div class="code"><pre> | ||
| t.rast.line -l -g input=tempmean zones=comparison_counties error=sd nprocs=10 \ | ||
| where="start_time > '2004-01-01' AND start_time < '2010-01-01'" | ||
| </pre></div> | ||
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| <p> | ||
| <div align="center" style="margin: 10px"> | ||
| <img src="t_rast_line_05.png"> | ||
| </div> | ||
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| <h3>Example 6</h3> | ||
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| If you want to create and compare two plots, it might be useful to | ||
| force both to use a specific scale by using the <b>y_axis_limits</b> | ||
| parameter and the same y-axis label by using the <b>y_label</b> | ||
| parameter. | ||
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| <p> | ||
| <div class="code"><pre> | ||
| t.rast.line -l -g input=tempmean \ | ||
| zones=comparison_counties error=sd nprocs=10 \ | ||
| y_axis_limits=-10,40 y_label="mean temperature" | ||
| </pre></div> | ||
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| <p> | ||
| <div align="center" style="margin: 10px"> | ||
| <img src="t_rast_line_06.png"> | ||
| </div> | ||
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| <h2>Acknowledgements</h2> | ||
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| This work was carried out within the framework of the <a | ||
| href="https://savethetiger.nl/" target="_blank">Save the Tiger, Save | ||
| the Grassland, Save the Water</a> project by the <a | ||
| href="https://www.has.nl/en/has-research/research-groups/innovative-bio-monitoring-research-group" | ||
| target="_blank">Innovative Bio-Monitoring research group</a> of the HAS | ||
| University of Applied Sciences. | ||
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| <h2>SEE ALSO</h2> | ||
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| <em> | ||
| <a href="https://grass.osgeo.org/grass-stable/manuals/addons/t.rast.boxplot.html">r.boxplot.html</a>, | ||
| <a href="https://grass.osgeo.org/grass-stable/manuals/addons/r.boxplot.html">r.boxplot.html</a>, | ||
| <a href="https://grass.osgeo.org/grass-stable/manuals/addons/r.series.boxplot.html">r.series.boxplot.html</a>, | ||
| <a href="https://grass.osgeo.org/grass-stable/manuals/addons/d.vect.colbp.html">d.vect.colbp</a>, | ||
| <a href="https://grass.osgeo.org/grass-stable/manuals/addons/r.scatterplot.html">r.scatterplot</a>, | ||
| <a href="https://grass.osgeo.org/grass-stable/manuals/r.stats.zonal.html">r.stats.zonal</a>, | ||
| </em> | ||
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| <h2>AUTHOR</h2> | ||
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| Paulo van Breugel<br> Applied Geo-information Sciences<br> <a | ||
| href="https://www.has.nl/">HAS green academy, University of Applied | ||
| Sciences</a><br> |
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