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grass-gis-addons/m.analyse.trees/v.trees.cd/v.trees.cd.html

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<h2>DESCRIPTION</h2>
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<em>v.trees.cd</em> calculates the change between two given treecrown vector
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maps (<b>inp_t1</b> and <b>inp_t2</b> for time t1 and t2, respectively).
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maps (<b>input</b> and <b>reference</b> for time t1 and t2, respectively).
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<p>
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It returns three vector maps: <i>&ltbasename&gt_congruent</i> for congruent
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trees, <i>&ltbasename&gt_only_&ltinp_t1&gt</i> for gone trees and
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<i>&ltbasename&gt_only_&ltinp_t2&gt</i> for new trees,
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trees, <i>&ltbasename&gt_only_&ltinput&gt</i> for gone trees and
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<i>&ltbasename&gt_only_&ltreference&gt</i> for new trees,
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with <i>&ltbasename&gt</i> defined by <b>output</b>.
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For the congruent trees the parameter <b>vec_congr_thr</b> can be set,
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For the congruent trees the parameter <b>congr_thresh</b> can be set,
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defining the threshold of overlap (in percentage) above which trees are
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considered to be congruent. Per default it is set to 90%.
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<p>
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For the two other maps (gone and new trees) two parameters can be set,
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to remove small areas: <b>vec_diff_min_size</b> and <b>vec_diff_max_fd</b>.
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to remove small areas: <b>diff_min_size</b> and <b>diff_max_fd</b>.
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They define the minimum size of identified change areas in sqm (default
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0.25 sqm), and the maximum value of fractal dimension of identified change
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areas (default 2.5).
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<h3>Calculate change detection with tile_size of 500</h3>
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<div class="code"><pre>
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v.trees.cd inp_t1=treecrowns_2020 inp_t2=treecrowns_2022 output=cd_2020_2022 tile_size=500
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v.trees.cd input=treecrowns_2020 reference=treecrowns_2022 output=cd_2020_2022 tile_size=500
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</pre></div>
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<h3>Calculate change detection with explicit values for filtering congruent and changed maps</h3>
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<div class="code"><pre>
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v.trees.cd inp_t1=treecrowns_2020 inp_t2=treecrowns_2022 output=cd_2020_2022 vec_congr_thr=80 vec_diff_min_size=1 tile_size=500
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v.trees.cd input=treecrowns_2020 reference=treecrowns_2022 output=cd_2020_2022 congr_thresh=80 diff_min_size=1 tile_size=500
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</pre></div>
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<h2>SEE ALSO</h2>
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<h2>AUTHORS</h2>
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Julia Haas and Lina Krisztian, <a href="https://www.mundialis.de/">mundialis GmbH &amp; Co. KG</a>, Germany
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Julia Haas, <a href="https://www.mundialis.de/">mundialis GmbH &amp; Co. KG</a>, Germany
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Lina Krisztian, <a href="https://www.mundialis.de/">mundialis GmbH &amp; Co. KG</a>, Germany

grass-gis-addons/m.analyse.trees/v.trees.param/v.trees.param.html

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tree height, crown area, crown perimeter, NDVI per single tree, crown volume,
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stem position, distance to nearest building and distance to nearest tree.
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The module takes as input a raster map of the <b>ndom</b> for computation
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The module takes as input a raster map of the <b>ndsm</b> for computation
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of the tree height, a raster map of the <b>ndvi</b> for computation of the
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NDVI per single tree and a vector map of the <b>buildings</b> for computation
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of the distance to the nearest building.
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<p>
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Optionally, the parameters <b>distance_building</b> and <b>distance_tree</b>
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Optionally, the parameters <b>dist_building</b> and <b>dist_tree</b>
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can be given, determining the range within neighbouring buildings or trees
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are searched for. First the region is set to the tree of interest, then the
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region is extended in each direction by <b>distance_building</b> or
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<b>distance_tree</b> (given in meters). By default <b>distance_building</b>
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is unset, and <b>distance_tree</b> is set to 500 m.
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region is extended in each direction by <b>dist_building</b> or
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<b>dist_tree</b> (given in meters). By default <b>dist_building</b>
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is unset, and <b>dist_tree</b> is set to 500 m.
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<p>
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The calculation can be done in parallel, with the number of parallel processes
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given by <b>nprocs</b>.
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<h3>Example 1:</h3>
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<div class="code"><pre>
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v.trees.param ndom=ndom ndvi=ndvi buildings=hausumringe treecrowns=trees
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v.trees.param ndsm=ndsm ndvi=ndvi buildings=hausumringe treecrowns=trees
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</pre></div>
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<h3>Example 2: run with 5 parallel processes</h3>
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<div class="code"><pre>
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v.trees.param ndom=ndom ndvi=ndvi buildings=hausumringe treecrowns=trees nprocs=5
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v.trees.param ndsm=ndsm ndvi=ndvi buildings=hausumringe treecrowns=trees nprocs=5
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</pre></div>
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<h3>Example 3: with optional input of <b>distance_tree</b> and <b>distance_building</b></h3>
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<h3>Example 3: with optional input of <b>dist_tree</b> and <b>dist_building</b></h3>
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<div class="code"><pre>
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v.trees.param ndom=ndom ndvi=ndvi buildings=hausumringe treecrowns=trees distance_tree=500 distance_building=500
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v.trees.param ndsm=ndsm ndvi=ndvi buildings=hausumringe treecrowns=trees dist_tree=500 dist_building=500
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</pre></div>
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<h2>SEE ALSO</h2>

grass-gis-addons/m.analyse.trees/v.trees.species/v.trees.species.html

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@@ -8,7 +8,7 @@ <h3>Classify trees in deciduous and coniferous trees</h3>
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<div class="code"><pre>
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v.trees.species red_raster=top_red_02 green_raster=top_green_02 \
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blue_raster=top_blue_02 nir_raster=top_nir_02 ndvi=top_ndvi_02 \
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blue_raster=top_blue_02 nir_raster=top_nir_02 ndvi_raster=top_ndvi_02 \
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ndsm=ndsm treecrowns=trees memory=10000
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</pre></div>
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grass-gis-addons/m.import.rvr/m.import.rvr.html

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<h2>DESCRIPTION</h2>
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<em>m.import.rvr</em> imports data for the processing of <b>gebaeudedetektion</b>,
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<b>dachbegruenung</b> and/or <b>einzelbaumerkennung</b>.
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<em>m.import.rvr</em> imports data for the processing of <b>buildings analysis</b>,
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<b>green roofs</b> and/or <b>trees analysis</b>.
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The module takes as options the paths to the input directories and files.
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With the flag <b>-c</b> the module checks only if all required input options
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for the selected processing <b>type</b> are set.
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The module imports the following data for the different processing <b>type</b>s:
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<ul>
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<li><b>gebaeudedetektion</b>
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<li><b>buildings analysis</b>
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<ul>
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<li>Flächennutzungskartierung (FNK): imported from given vector file <b>fnk_file</b></li>
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<li>Reference buildings: imported from given vector file <b>reference_buildings_file</b> or from openNRW if <b>-b</b> is set</li>
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<li>Normalized Digital Surface Model (nDSM): calculated on the basis of <b>DSM</b> and <b>DTM</b></li>
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</ul>
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</li>
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<li><b>dachbegruenung</b>
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<li><b>green roofs</b>
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<ul>
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<li>Flächennutzungskartierung (FNK): imported from given vector file <b>fnk_file</b></li>
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<li>Reference Trees: imported from given vector file <b>tree_file</b></li>
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<li>Normalized Digital Surface Model (nDSM): calculated on the basis of <b>DSM</b> and <b>DTM</b></li>
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</ul>
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</li>
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<li><b>einzelbaumerkennung</b>
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<li><b>trees analysis</b>
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<ul>
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<li>True digital orthophotos (TOP): GTIFF files from given directory <b>top_dir</b> imported and resampled to 0.2 m</li>
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<li>Digital surface model (DSM): LAZ files from given directory <b>dsm_dir</b> imported and resampled to 0.2 m</li>
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<h2>EXAMPLES</h2>
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<h3>Import gebaeudedetektion data for Dinslaken 2020</h3>
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<h3>Import data for buildings analysis for Dinslaken 2020</h3>
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In this example the DTM data will be downloaded from
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<a href="https://www.bezreg-koeln.nrw.de/brk_internet/geobasis/">OpenNRW</a>
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and also the reference data for buildings will be downloaded from
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<a href="https://www.bezreg-koeln.nrw.de/brk_internet/geobasis/">OpenNRW</a>.
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<div class="code"><pre>
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DATAFOLDER=/mnt/data/Originaldaten_RVR/Dinslaken
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m.import.rvr memory=6000 type=gebaeudedetektion \
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m.import.rvr memory=6000 type='buildings analysis' \
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area=/mnt/data/Dinslaken/fnk_dinslaken/fnk_dinslaken.shp \
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fnk_file=/mnt/data/Dinslaken/fnk_dinslaken/fnk_dinslaken.shp \
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fnk_column=code_2020 \
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dsm_dir=${DATAFOLDER}/2020_Sommer/Punktwolke_2_5D_RGBI \
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dop_dir=${DATAFOLDER}/2020_Sommer/DOP -b
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</pre></div>
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<h3>Import dachbegruenung data for Dinslaken 2020</h3>
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<h3>Import data for green roofs detection for Dinslaken 2020</h3>
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<div class="code"><pre>
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DATAFOLDER=/mnt/data/Originaldaten_RVR/Dinslaken
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m.import.rvr memory=6000 type=dachbegruenung -b \
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m.import.rvr memory=6000 type='green roofs' -b \
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area=/mnt/data/Dinslaken/fnk_dinslaken/fnk_dinslaken.shp \
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fnk_file=/mnt/data/Dinslaken/fnk_dinslaken/fnk_dinslaken.shp \
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fnk_column=code_2020 \
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dsm_dir=${DATAFOLDER}/2020_Sommer/Punktwolke_2_5D_RGBI \
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dop_dir=${DATAFOLDER}/2020_Sommer/DOP -b
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</pre></div>
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<h3>Import einzelbaumerkennung data for Herne 2020</h3>
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<h3>Import data for trees analysis for Herne 2020</h3>
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<div class="code"><pre>
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DATAFOLDER=/mnt/projects/rv_ruhr_baumstandorte/geodata/rvr_data_Herne_2020/
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m.import.rvr memory=6000 type=einzelbaumerkennung -b \
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m.import.rvr memory=6000 type='trees analysis' -b \
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area=${DATAFOLDER}/test_area.gpkg \
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reference_buildings_file=${DATAFOLDER}/Shapes/herne_hausumringe_100m_puffer.shp \
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top_dir=${DATAFOLDER}/TOP/ \
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<h2>AUTHORS</h2>
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Anika Weinmann and Momen Mawad, <a href="https://www.mundialis.de/">mundialis GmbH &amp; Co. KG</a>
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Anika Weinmann, <a href="https://www.mundialis.de/">mundialis GmbH &amp; Co. KG</a>
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Momen Mawad, <a href="https://www.mundialis.de/">mundialis GmbH &amp; Co. KG</a>

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