🌳 VoxCity View Index Analysis

Analyze Green View Index (GVI) and Sky View Index (SVI) using 3D ray-casting through your voxel city model.

What are View Indices?

Index	Description	Use Case
GVI	Percentage of view occupied by vegetation	Urban greenery assessment
SVI	Percentage of visible sky	Urban canyon analysis, thermal comfort

Key Features

• Ray-casting from observer viewpoint through 3D voxel model

• Configurable azimuth and elevation sampling

• Tree transmissivity modeling (light passes through tree canopy)

• Export results as colored OBJ meshes

Prerequisites

pip install voxcity

# %pip install voxcity

from voxcity.generator import get_voxcity
from voxcity.geoprocessor.draw import draw_rectangle_map_cityname
from voxcity.simulator.view import get_view_index

cityname = "Tokyo, Japan"
meshsize = 5

# m, rectangle_vertices = draw_rectangle_map_cityname(cityname, zoom=15)
# m

rectangle_vertices = [
    (139.760, 35.680),  # SW
    (139.760, 35.690),  # NW
    (139.770, 35.690),  # NE
    (139.770, 35.680)   # SE
]

city = get_voxcity(
    rectangle_vertices,
    meshsize=meshsize,
    building_source='OpenStreetMap',
    land_cover_source='OpenStreetMap',
    canopy_height_source='High Resolution 1m Global Canopy Height Maps',
    dem_source='DeltaDTM',
    output_dir='output/view_demo'
)

city.voxels.classes.shape

---

🌳 Green View Index (GVI)

Calculate the percentage of visible vegetation from each grid cell.

Advanced Parameters

Parameter	Description	Default
N_azimuth	Number of azimuth angles	72
N_elevation	Number of elevation angles	12
elevation_min_degrees	Minimum elevation angle	-15°
elevation_max_degrees	Maximum elevation angle	30°
ray_sampling	Sampling method: ‘grid’ or ‘fibonacci’	‘fibonacci’
tree_k	Extinction coefficient for tree canopy	0.5
tree_lad	Leaf Area Density (LAD)	1.0

gvi_kwargs = {
    "view_point_height": 1.5,
    "colormap": "Greens",
    "obj_export": True,
    "output_directory": "output/view_demo",
    "output_file_name": "gvi",
    "alpha": 1.0,
    # Ray sampling controls
    "N_azimuth": 72,
    "N_elevation": 12,
    "elevation_min_degrees": -15,
    "elevation_max_degrees": 30,
    "ray_sampling": "fibonacci",  # 'grid' or 'fibonacci'
    # Tree transmittance controls
    "tree_k": 0.5,
    "tree_lad": 1.0,
}

gvi_grid = get_view_index(city, mode='green', **gvi_kwargs)

gvi_grid.shape

---

🌤️ Sky View Index (SVI)

Calculate the percentage of visible sky from each grid cell.

For SVI, the elevation range is typically from horizon (0°) to zenith (90°).

svi_kwargs = gvi_kwargs.copy()
svi_kwargs["colormap"] = "BuPu_r"
svi_kwargs["output_file_name"] = "svi"
svi_kwargs["elevation_min_degrees"] = 0
svi_kwargs["elevation_max_degrees"] = 90

svi_grid = get_view_index(city, mode='sky', **svi_kwargs)

svi_grid.shape

---

📊 Interpreting Results

• GVI values range from 0 to 1 (0% to 100% vegetation visibility)

• SVI values range from 0 to 1 (0% to 100% sky visibility)

• Results are exported as colored OBJ files for visualization in Blender/Rhino

• Higher N_azimuth and N_elevation values give more accurate but slower results

Next Steps

• demo_solar.ipynb - Solar irradiance simulation

• demo_landmark.ipynb - Landmark visibility analysis

• demo_3d_visualization.ipynb - Advanced 3D visualization