Light Pollution Sampler

Overview

The light_pollution_sampler module samples DVNL (Day/Night Visible Lights) raster data during horizon profile generation to estimate local sky brightness and Bortle class.

LightPollutionSampler

Samples aggregated DVNL radiance at geographic coordinates.

class LightPollutionSampler:
    def __init__(self, dvnl_agg_path: str)

Parameters

dvnl_agg_path

str

required

Path to the aggregated (convolved) DVNL GeoTIFF file

Methods

sample_at

Sample DVNL radiance at a specific location.

def sample_at(self, lat: float, lon: float) -> Optional[float]

lat

float

required

Latitude in decimal degrees (WGS84)

lon

float

required

Longitude in decimal degrees (WGS84)

Returns: Aggregated DVNL radiance value (nW/cm²/sr), or None if outside coverage or NoData

estimate_sqm

Estimate Sky Quality Meter reading at a location.

def estimate_sqm(self, lat: float, lon: float) -> Optional[float]

lat

float

required

Latitude in decimal degrees

lon

float

required

Longitude in decimal degrees

Returns: Estimated SQM value in mag/arcsec², or None if no data Formula: Uses the empirical calibration model:

\text{SQM} = 22.0 - 2.4 \cdot \log_{10}(R_{\text{agg}} + 0.001)

estimate_bortle

Estimate Bortle dark-sky class at a location.

def estimate_bortle(self, lat: float, lon: float) -> Optional[int]

lat

float

required

Latitude in decimal degrees

lon

float

required

Longitude in decimal degrees

Returns: Bortle class (1-9), or None if no data

Example

from TerraLab.terrain.light_pollution_sampler import LightPollutionSampler

# Initialize with convolved DVNL data
sampler = LightPollutionSampler("dvnl_convolved_30km.tif")

# Sample at a dark sky site
lat, lon = 42.1234, 1.5678

# Get raw radiance
radiance = sampler.sample_at(lat, lon)
print(f"DVNL radiance: {radiance:.2f} nW/cm²/sr")

# Estimate sky quality
sqm = sampler.estimate_sqm(lat, lon)
print(f"Estimated SQM: {sqm:.2f} mag/arcsec²")

# Get Bortle class
bortle = sampler.estimate_bortle(lat, lon)
print(f"Bortle class: {bortle}")

Integration with Horizon Engine

The sampler is used during horizon profile generation to:

Sample at observer location: Determine zenith sky brightness
Sample along rays: Build directional light pollution maps
Create light domes: Visualize light sources on the horizon

Usage in HorizonBaker

from TerraLab.terrain.engine import HorizonBaker
from TerraLab.terrain.light_pollution_sampler import LightPollutionSampler

baker = HorizonBaker(
    dem_provider=provider,
    lp_sampler=LightPollutionSampler("dvnl_convolved.tif")
)

profile = baker.bake(
    lat=42.0,
    lon=2.0,
    n_bands=20,
    max_dist_m=150000
)

print(f"Observer Bortle class: {profile.bortle_class}")
print(f"Observer SQM: {profile.sqm_estimate:.2f} mag/arcsec²")

Thread Safety

The sampler uses RASTERIO_LOCK for thread-safe concurrent access to the GeoTIFF file.

Performance Considerations

Coordinate transformation: Uses pyproj for accurate WGS84 → raster CRS conversion
Bilinear interpolation: Sub-pixel sampling for smooth gradients
Caching: Rasterio’s internal caching reduces repeated I/O

Terrain Module

Light Pollution

Astronomical

Widgets

Light Pollution Sampler

Overview