Geoskill: Building Footprint Height

Extract building footprints and estimate height, floor count proxy, and volume from DSM/DTM/LiDAR data. Produces 2.5D urban models for 3D city modeling, population downscaling, and risk exposure analysis.

Building Footprint Height

Extract building heights from elevation data (DSM, DTM, LiDAR point cloud) and building footprints. Estimates height, floor count proxy, volume, and quality codes for each building.

Trigger

Use when the user wants to:

• Estimate building heights from DSM/DTM raster data
• Compute building volumes and floor count proxies
• Generate 2.5D urban models for 3D city visualization
• Assess building data quality and flag anomalies
• Prepare building data for population downscaling or risk exposure

CLI Usage

bash

# Synthetic demo mode (no input files needed)
python scripts/building_footprint_height.py --output-dir ./bfh-output

# With custom floor height assumption
python scripts/building_footprint_height.py --floor-height 3.6 --output-dir ./bfh-output

# With point cloud method
python scripts/building_footprint_height.py --height-method point_cloud_quantile --output-dir ./bfh-output

# With custom standards
python scripts/building_footprint_height.py --standard-config ./my-standards.json --output-dir ./bfh-output

Parameters

Parameter	Default	Description
--dsm	None	Path to DSM GeoTIFF
--dtm	None	Path to DTM GeoTIFF
--footprints	None	Path to building footprints GeoJSON/Shapefile
--point-cloud	None	Path to LiDAR point cloud (LAS/CSV)
--height-method	dsm_minus_dtm	Height estimation method
--floor-height	3.0	Assumed floor height in meters
--output-dir	./bfh-output	Output directory
--standard-config	None	Path to building height standards JSON
--bbox	None	W,S,E,N in WGS-84 (auto-downloads Copernicus GLO-30 DEM)
--date-range	None	START,END ISO-8601 (optional for time-invariant DEM)
--aoi-file	None	GeoJSON polygon; its bbox is used for the query
--cache-dir	None	Override the data-fetcher cache directory

数据下载 (Data Download)

This skill can auto-download the elevation input from the Microsoft Planetary Computer STAC catalog. No API key is required.

bash

# Download one Copernicus GLO-30 DEM tile over central Beijing and run the
# pipeline using it as a stand-in DSM (the script falls back to a
# percentile-DTM approximation when no DTM is supplied).
python scripts/building_footprint_height.py \
  --bbox 116.0,39.5,116.8,40.0 \
  --output-dir ./bfh-output

The downloaded asset is cached under ~/.geoskill_cache/ so a second run with the same --bbox reuses the file. The download route also accepts --aoi-file my_polygon.geojson instead of --bbox.

Height Methods

Method	Priority	Requirements	Quality
dsm_minus_dtm	1 (recommended)	DSM + DTM rasters	Code 1 (best)
point_cloud_quantile	2	LiDAR point cloud	Code 2
shadow_based	3	Shadow length + solar angle	Code 3

Output

File	Description
buildings_3d.geojson	Building footprints with height/volume/floors
height.tif (.npy + meta)	Building height raster
building_stats.csv	Per-building statistics
quality_flags.geojson	Buildings with quality issues
report.html	Human-readable HTML report
request.json	Analysis request metadata
dataset-manifest.json	Dataset inventory
output-manifest.json	Output file inventory
qa.json	Quality assurance checks

Quality Codes

Code	Label	Meaning
1	高度可靠	DSM-DTM, coverage >80%
2	高度较可靠	Point cloud quantile, >50 points
3	高度估算	Shadow-based or coarse DEM
4	高度可疑	Coverage <50% or anomaly detected
5	高度缺失	No valid data

Key Algorithms

DSM-DTM Height

Height = quantile(DSM_footprint, 0.95) - median(DTM_footprint)

Uses robust quantile to exclude outliers (antennas, trees). Edge buffer (default 0.5m) excludes mixed-boundary pixels.

Point Cloud Quantile

Height = quantile(points_z, 0.95) - quantile(points_z, 0.05)

Requires ≥10 points per building. Ground reference is 5th percentile.

Floor Count Proxy

floors = round(height / floor_height)

Floor height is an assumption (default 3.0m residential). Min/max range accounts for ±0.5m uncertainty.

Volume

V = footprint_area × height × roof_factor

Roof factors: flat=1.0, pitched=0.85, complex=0.9

Exit Codes

Code	Meaning
0	Success
2	Argument error
3	Dependency missing
6	Data validation failure
7	Processing failure

Limitations

• Synthetic demo mode only; file-based mode requires GeoTIFF/GeoJSON input
• Floor count is a proxy — actual floors may differ
• Shadow method requires manual shadow length measurement
• Does not produce true 3D mesh models (2.5D only)
• Coarse DEM (e.g., SRTM) should NOT be used for individual building heights
• Tree mixing may inflate height estimates in vegetated areas

References

• OSM Building Heights dataset
• Microsoft Building Footprints
• AHN (Actueel Hoogtebestand Nederland) DSM/DTM
• USGS 3DEP LiDAR point clouds