nearest_pixel_ndvi is created automatically in r.trees.mltrain if not…

… set, so that r.trees.traindata can be skipped if own training data are created

grass-gis-addons/m.analyse.trees/analyse_trees_lib/analyse_trees_lib.py

@@ -378,3 +378,68 @@ def create_grid_cd(tile_size, vec1, vec2):
     grass.message(_(f"Number of tiles is: {number_tiles}"))
 
     return grid_trees, tiles_list, number_tiles, rm_vectors
+
+
+def create_nearest_pixel_ndvi(
+    ndvi, ndvi_threshold, nearest, nprocs, memory, rm_rasters, output
+):
+    """Creates the raster map with nearest tree peaks based on the NDVI
+    threshold
+
+    Args:
+        ndvi (str): The name of the NDVI raster map
+        ndvi_threshold (float): The threshold for the NDVI
+        nearest (str): The name of nearest tree peaks raster map
+        nprocs (int): The number of parallel processes
+        memory (int): The used memory in MB
+        rm_rasters (list): The list of raster which should be removed in the
+                           cleanup
+        output (str): The name for the nearest tree peaks based on NDVI
+                      threshold raster map
+    """
+    # mathematical morphology: opening to remove isolated small patches of high ndvi
+    ndvi_split = ndvi.split("@")[0]
+    grass.run_command(
+        "r.neighbors",
+        input=ndvi,
+        output=f"{ndvi_split}_min1",
+        size=3,
+        method="minimum",
+        nprocs=nprocs,
+        memory=memory,
+    )
+    grass.run_command(
+        "r.neighbors",
+        input=f"{ndvi_split}_min1",
+        output=f"{ndvi_split}_min2",
+        size=3,
+        method="minimum",
+        nprocs=nprocs,
+        memory=memory,
+    )
+    grass.run_command(
+        "r.neighbors",
+        input=f"{ndvi_split}_min2",
+        output=f"{ndvi_split}_max1",
+        size=3,
+        method="maximum",
+        nprocs=nprocs,
+        memory=memory,
+    )
+    grass.run_command(
+        "r.neighbors",
+        input=f"{ndvi_split}_max1",
+        output=f"{ndvi_split}_max2",
+        size=3,
+        method="maximum",
+        nprocs=nprocs,
+        memory=memory,
+    )
+    rm_rasters.append(f"{ndvi_split}_min1")
+    rm_rasters.append(f"{ndvi_split}_min2")
+    rm_rasters.append(f"{ndvi_split}_max1")
+    rm_rasters.append(f"{ndvi_split}_max2")
+
+    grass.mapcalc(
+        f"{output} = if({ndvi_split}_max2 < {ndvi_threshold}, null(), {nearest})"
+    )

grass-gis-addons/m.analyse.trees/r.trees.mltrain/r.trees.mltrain.py

@@ -54,12 +54,30 @@
 # %end
 
 # %option G_OPT_R_INPUT
-# % key: trees_pixel_ndvi
+# % key: nearest_pixel_ndvi
 # % label: raster with trees identified by NDVI value
-# % answer: trees_pixel_ndvi
+# % required: no
+# % answer: nearest_pixel_ndvi
 # % guisection: Input
 # %end
 
+# %option G_OPT_R_INPUT
+# % key: nearest
+# % label: Name of raster with nearest peak IDs
+# % required: no
+# % answer: nearest_tree
+# % guisection: Input
+# %end
+
+# %option
+# % key: ndvi_threshold
+# % type: double
+# % required: no
+# % label: NDVI threshold for potential trees
+# % answer: 130
+# % guisection: Parameters
+# %end
+
 # %option G_OPT_R_INPUT
 # % key: ndvi_raster
 # % label: Name of the NDVI raster
@@ -141,9 +159,16 @@
 # % guisection: Parallel processing
 # %end
 
+# %option G_OPT_MEMORYMB
+# % guisection: Parallel processing
+# %end
+
 # %rules
 # % exclusive: trees_raw_r,trees_raw_v
 # % required: trees_raw_r,trees_raw_v
+# % required: nearest_pixel_ndvi,nearest
+# % excludes: nearest_pixel_ndvi,nearest,ndvi_threshold
+# % requires_all: nearest,ndvi_threshold
 # %end
 
 import atexit
@@ -190,7 +215,11 @@ def main():
         grass.fatal("Unable to find the analyse trees library directory")
     sys.path.append(path)
     try:
-        from analyse_trees_lib import set_nprocs
+        from analyse_trees_lib import (
+            create_nearest_pixel_ndvi,
+            set_nprocs,
+            test_memory,
+        )
     except Exception:
         grass.fatal("m.analyse.trees library is not installed")
 
@@ -213,9 +242,17 @@ def main():
     group_name = options["group"]
     model_file = options["save_model"]
     nprocs = int(options["nprocs"])
-    trees_pixel_ndvi = options["trees_pixel_ndvi"]
+    nearest_pixel_ndvi = options["nearest_pixel_ndvi"]
+    nearest = options["nearest"]
+    ndvi_threshold = options["ndvi_threshold"]
 
     nprocs = set_nprocs(nprocs)
+    memmb = test_memory(options["memory"])
+    # for some modules like r.neighbors and r.slope_aspect, there is
+    # no speed gain by using more than 100 MB RAM
+    memory_max100mb = 100
+    if memmb < 100:
+        memory_max100mb = memmb
 
     grass.use_temp_region()
 
@@ -247,17 +284,28 @@ def main():
         trees_basemap = options["trees_raw_r"]
 
     # non trees
+    if not grass.find_file(name=nearest_pixel_ndvi, element="cell")["file"]:
+        create_nearest_pixel_ndvi(
+            ndvi,
+            ndvi_threshold,
+            nearest,
+            nprocs,
+            memory_max100mb,
+            rm_rasters,
+            nearest_pixel_ndvi,
+        )
+        rm_rasters.append(nearest_pixel_ndvi)
 
     # false trees
     # problem areas with high NDVI like shadows on roofs, solar panels
-    # trees_object_filt_large = NULL and trees_pixel_ndvi != NULL
+    # trees_object_filt_large = NULL and nearest_pixel_ndvi != NULL
     grass.mapcalc(
-        f"false_trees = if(isnull({trees_pixel_ndvi}), null(), if(isnull({trees_basemap}), 1, null()))"
+        f"false_trees = if(isnull({nearest_pixel_ndvi}), null(), if(isnull({trees_basemap}), 1, null()))"
     )
 
     # other areas clearly not trees
     grass.mapcalc(
-        f"notrees = if(isnull({trees_pixel_ndvi}) && isnull({trees_basemap}), 1, null())"
+        f"notrees = if(isnull({nearest_pixel_ndvi}) && isnull({trees_basemap}), 1, null())"
     )
     rm_rasters.append("false_trees")
     rm_rasters.append("notrees")

grass-gis-addons/m.analyse.trees/r.trees.traindata/r.trees.traindata.py

@@ -211,7 +211,11 @@ def main():
         grass.fatal("Unable to find the analyse trees library directory")
     sys.path.append(path)
     try:
-        from analyse_trees_lib import set_nprocs, test_memory
+        from analyse_trees_lib import (
+            create_nearest_pixel_ndvi,
+            set_nprocs,
+            test_memory,
+        )
     except Exception:
         grass.fatal("m.analyse.trees library is not installed")
 
@@ -226,7 +230,6 @@ def main():
     blue = options["blue_raster"]
     nir = options["nir_raster"]
     ndvi = options["ndvi_raster"]
-    ndvi_split = ndvi.split("@")[0]
     ndwi = options["ndwi_raster"]
     ndgb = options["ndgb_raster"]
     ndsm = options["ndsm"]
@@ -273,55 +276,19 @@ def main():
     # - lower such that trees are kept -> shadow areas are kept
 
     # mathematical morphology: opening to remove isolated small patches of high ndvi
-    grass.run_command(
-        "r.neighbors",
-        input=ndvi,
-        output=f"{ndvi_split}_min1",
-        size=3,
-        method="minimum",
-        nprocs=nprocs,
-        memory=memory_max100mb,
-    )
-    grass.run_command(
-        "r.neighbors",
-        input=f"{ndvi_split}_min1",
-        output=f"{ndvi_split}_min2",
-        size=3,
-        method="minimum",
-        nprocs=nprocs,
-        memory=memory_max100mb,
-    )
-    grass.run_command(
-        "r.neighbors",
-        input=f"{ndvi_split}_min2",
-        output=f"{ndvi_split}_max1",
-        size=3,
-        method="maximum",
-        nprocs=nprocs,
-        memory=memory_max100mb,
-    )
-    grass.run_command(
-        "r.neighbors",
-        input=f"{ndvi_split}_max1",
-        output=f"{ndvi_split}_max2",
-        size=3,
-        method="maximum",
-        nprocs=nprocs,
-        memory=memory_max100mb,
-    )
-    rm_rasters.append(f"{ndvi_split}_min1")
-    rm_rasters.append(f"{ndvi_split}_min2")
-    rm_rasters.append(f"{ndvi_split}_max1")
-    rm_rasters.append(f"{ndvi_split}_max2")
-
     if options["nearest_pixel_ndvi"]:
         nearest_pixel_ndvi = options["nearest_pixel_ndvi"]
     else:
         nearest_pixel_ndvi = "nearest_pixel_ndvi"
         rm_rasters.append(nearest_pixel_ndvi)
-
-    grass.mapcalc(
-        f"{nearest_pixel_ndvi} = if({ndvi_split}_max2 < {ndvi_threshold}, null(), {nearest})"
+    create_nearest_pixel_ndvi(
+        ndvi,
+        ndvi_threshold,
+        nearest,
+        nprocs,
+        memory_max100mb,
+        rm_rasters,
+        nearest_pixel_ndvi,
     )
 
     # cut to nir: all pixels below 100 are not vegetation