import option 'train neural network'

grass-gis-addons/m.import.rvr/m.import.rvr.html

@@ -1,7 +1,7 @@
 <h2>DESCRIPTION</h2>
 
 <em>m.import.rvr</em> imports data for the processing of <b>buildings analysis</b>,
-<b>green roofs</b> and/or <b>trees analysis</b>.
+<b>green roofs</b>, <b>trees analysis</b> and/or ><b>neural network</b>.
 
 The module takes as options the paths to the input directories and files.
 With the flag <b>-c</b> the module checks only if all required input options
@@ -35,12 +35,21 @@ <h2>DESCRIPTION</h2>
   <li><b>trees analysis</b>
   <ul>
     <li>True digital orthophotos (TOP): GTIFF files from given directory <b>top_dir</b> imported and resampled to 0.2 m</li>
+    <li>Reference buildings: imported from given vector file <b>reference_buildings_file</b> or from openNRW if <b>-b</b> is set</li>
     <li>Digital surface model (DSM): LAZ files from given directory <b>dsm_dir</b> imported and resampled to 0.2 m</li>
     <li>Digital terrain model (DTM): from given raster file <b>dtm_file</b>, or tiles from a directory with XYZ files, or if not set from openNRW imported and resampled to 0.2 m </li>
     <li>Normalized Difference Vegetation Index (NDVI): calculated on the basis of <b>TOP</b> and scaled to 0 to 255</li>
     <li>Normalized Digital Surface Model (nDSM): calculated on the basis of <b>DSM</b> and <b>DTM</b></li>
   </ul>
   </li>
+  <li><b>neural network</b>
+    <ul>
+      <li>True digital orthophotos (TOP): GTIFF files from given directory <b>top_dir</b> imported and resampled to 0.2 m</li>
+      <li>Digital surface model (DSM): LAZ files from given directory <b>dsm_dir</b> imported and resampled to 0.2 m</li>
+      <li>Digital terrain model (DTM): from given raster file <b>dtm_file</b>, or tiles from a directory with XYZ files, or if not set from openNRW imported and resampled to 0.2 m </li>
+      <li>Normalized Digital Surface Model (nDSM): calculated on the basis of <b>DSM</b> and <b>DTM</b></li>
+    </ul>
+    </li>
 </ul>
 
 <h2>REQUIREMENTS</h2>
@@ -102,6 +111,21 @@ <h3>Import data for trees analysis for Herne 2020</h3>
   dtm_file=${DATAFOLDER}/DGM/2020_Herne_DGM10_100m_Puffer.tif
 </pre></div>
 
+<h3>Import data for neural network label traindata for Sonsbeck 2020</h3>
+
+<div class="code"><pre>
+CITY=Sonsbeck
+YEAR=2020
+BEFLIEGUNG="08-05"
+DATA_DIR="/media/mundialis_daten/projekte/rvr_grassgis-addon-wartung/Testdaten"
+CITY_DIR="${DATA_DIR}/${CITY}"
+m.import.rvr type="neural network" \
+  area=/media/mundialis_daten/projekte/rvr_grassgis-addon-wartung/Testdaten/Sonsbeck/study_area_4x4km_Sonsbeck.gpkg \
+  dtm_file="${CITY_DIR}/${YEAR}/${BEFLIEGUNG}/DGM1/TIFF_corrected/MOSAIC/DGM1_${CITY}_${YEAR}_corrected.tif" \
+  dsm_dir="${CITY_DIR}/${YEAR}/${BEFLIEGUNG}/2_5D" \
+  top_dir="${CITY_DIR}/${YEAR}/${BEFLIEGUNG}/TOP"
+</pre></div>
+
 
 <h2>SEE ALSO</h2>
 

grass-gis-addons/m.import.rvr/m.import.rvr.py

@@ -18,13 +18,14 @@
 #############################################################################
 
 # %Module
-# % description: Import data for the processing of buildings analysis, green roofs detection and/or trees analysis.
+# % description: Import data for the processing of buildings analysis, green roofs detection, trees analysis and/or neural network.
 # % keyword: raster
 # % keyword: vector
 # % keyword: import
 # % keyword: trees analysis
 # % keyword: buildings analysis
 # % keyword: green roofs
+# % keyword: neural network
 # %end
 
 # %option
@@ -33,7 +34,7 @@
 # % required: yes
 # % multiple: yes
 # % label: Type of processing for which the data should be imported
-# % options: buildings analysis,green roofs,trees analysis
+# % options: buildings analysis,green roofs,trees analysis,neural network
 # % guisection: General input
 # %end
 
@@ -48,7 +49,7 @@
 # % key: dsm_dir
 # % multiple: no
 # % label: Directory where the digital surface model (DSM) is stored as laz files
-# % description: Required for the processing types buildings analysis, green roofs detection and trees analysis
+# % description: Required for the processing types buildings analysis, green roofs detection, trees analysis and neural network
 # % guisection: General input
 # %end
 
@@ -66,7 +67,7 @@
 # % required: no
 # % multiple: no
 # % label: Directory where XYZ files of the digital terrain model (DTM) are stored (leave empty to automatically download DTM from Open.NRW)
-# % description: Required for the processing types buildings analysis, green roofs detection and trees analysis
+# % description: Required for the processing types buildings analysis, green roofs detection, trees analysis and neural network
 # % guisection: General input
 # %end
 
@@ -75,7 +76,7 @@
 # % required: no
 # % multiple: no
 # % label: Raster file (e.g. TIF) of the digital terrain model (DTM) (leave empty to automatically download DTM from Open.NRW)
-# % description: Required for the processing types buildings analysis, green roofs detection and trees analysis
+# % description: Required for the processing types buildings analysis, green roofs detection, trees analysis and neural network
 # % guisection: General input
 # %end
 
@@ -166,7 +167,7 @@
 # % required: no
 # % multiple: no
 # % label: Directory where the true digital orthophots (TOPs) are stored as GeoTiffs
-# % description: Required for the processing of trees analysis
+# % description: Required for the processing of trees analysis and neural network
 # % guisection: Input trees analysis
 # %end
 
@@ -284,6 +285,13 @@
         "dtm": ([0.2], "ndsm", False, "dtm_file", "rasterORxyz"),
         "ndsm": ([0.2], "output", True, "", "ndsm"),
     },
+    "neural network": {
+        # raster
+        "top": ([0.2], "output,ndvi", True, "top_dir", "rasterdir"),
+        "dsm": ([0.2], "ndsm", True, "dsm_dir", "lazdir"),
+        "dtm": ([0.2], "ndsm", False, "dtm_file", "rasterORxyz"),
+        "ndsm": ([0.2], "output", True, "", "ndsm"),
+    },
 }
 
 
@@ -592,8 +600,8 @@ def check_data(ptype, data, val):
     """Checks if all required data are set and the data files or folder
     exists.
     Args:
-        ptype (str): processing type (buildings analysis, green roofs or
-                     trees analysis)
+        ptype (str): processing type (buildings analysis, green roofs,
+                     trees analysis or neural network)
         data (str):  Name or type of the data
         val (tuple): Tuple with values of the data: (resolution, purpose,
                      required, needed input information, import