def raster_to_tin(input_terrain_raster):
# read raster records
raster_dataset = gdal.Open(input_terrain_raster)
band = raster_dataset.GetRasterBand(1)
a = band.ReadAsArray(0, 0, raster_dataset.RasterXSize,
raster_dataset.RasterYSize)
# if the raster file is below sea level, the entire case study is lifted to the lowest point is at altitude 0
if (a * (a > -1e3)).min() < 0:
a -= (a * (a > -1e3)).min()
(y_index, x_index) = np.nonzero(a >= 0)
(upper_left_x, x_size, x_rotation, upper_left_y, y_rotation,
y_size) = raster_dataset.GetGeoTransform()
x_coords = x_index * x_size + upper_left_x + (x_size / 2
) # add half the cell size
y_coords = y_index * y_size + upper_left_y + (y_size / 2
) # to centre the point
elevation_mean = int(a[y_index, x_index].mean())
raster_points = [(x, y, z)
for x, y, z in zip(x_coords, y_coords, a[y_index,
x_index])]
tin_occface_list = construct.delaunay3d(raster_points)
return elevation_mean, tin_occface_list
def generate_tin(self):
(y_index, x_index) = np.nonzero(self.elevation_map >= 0)
_x_coords = self.x_coords[x_index]
_y_coords = self.y_coords[y_index]
raster_points = [(x, y, z) for x, y, z in zip(
_x_coords, _y_coords, self.elevation_map[y_index, x_index])]
tin_occface_list = construct.delaunay3d(raster_points)
return tin_occface_list
def terrain_2d_to_3d(citygml_writer, input_terrain_raster):
# read x, y, z coordinates of raster
raster_points = raster_reader(input_terrain_raster)
#create tin and triangulate
tin_occface_list = construct.delaunay3d(raster_points)
geometry_list = gml3dmodel.write_gml_triangle(tin_occface_list)
citygml_writer.add_tin_relief("lod1", "terrain1", geometry_list)
return tin_occface_list
def raster2tin(input_terrain_raster):
# read raster records
raster_dataset = gdal.Open(input_terrain_raster)
band = raster_dataset.GetRasterBand(1)
a = band.ReadAsArray(0, 0, raster_dataset.RasterXSize, raster_dataset.RasterYSize)
(y_index, x_index) = np.nonzero(a >= 0)
(upper_left_x, x_size, x_rotation, upper_left_y, y_rotation, y_size) = raster_dataset.GetGeoTransform()
x_coords = x_index * x_size + upper_left_x + (x_size / 2) # add half the cell size
y_coords = y_index * y_size + upper_left_y + (y_size / 2) # to centre the point
elevation_mean = int(a[y_index, x_index].mean())
raster_points = [(x, y, z) for x, y, z in zip(x_coords, y_coords, a[y_index, x_index])]
tin_occface_list = construct.delaunay3d(raster_points)
return elevation_mean, tin_occface_list