Block-Level Analysis | 1 Generating blocks | Dual carriageway simplification | Controlling block size | 2 Aggregating metrics to block level | Custom aggregation functions | Block-level population | Block-level residential proportion | 3 Visualizing block-level metrics | Comparing several block metrics in one figure | 4 A complete block analysis pipeline

Analyze Building Footprints | Example data | 1 Morphological Metrics | 2 Neighbor Metrics | 3 Distance to Nearest Greenspace | Measuring Along Real Streets | 4 Building Green View Index | 5 A Complete Metric Pipeline

Analyze Building Shadows and Radiation | 1 Workflow Summary | 2 Solar Position | 3 Shadow Footprints | 4 Shadow Height as a Terra Surface | 5 Tree Canopy and Terrain | 6 Building Surface Radiation | 6.1 Building surface visualization | 6.2 Tree canopy and terrain | 6.3 Canopy impact: radiation difference | 6.4 2D map view | 6.5 Cumulative daily radiation | 7 Ground-Level Radiation | 7.1 Ground shadow map | 7.2 Ground radiation with tree canopy | 7.3 Ground vs. roof comparison

1 Retrieve Building Footprints with Heights Using a Bounding Box | 2 Build a Fused Digital Surface Model from Building Height Data | 3 Exporting 3D City Models | 3.1 Quick start | 3.2 Satellite texture | 3.3 Voxel mode

Urban Noise Mapping | 1 Prepare Inputs | Fetch Canopy, Greenspace, and DEM Internally | 2 Run NoiseModelling | Advanced NoiseModelling Controls

1 Quick start | 2 Inputs | 2.1 Spatial layers | 2.2 Terrain and canopy geometry | 2.3 Ground roughness z0 from land-cover data | 2.4 ERA5 weather conditions | 3 Wind simulation | 3.1 Write the case | Any wind direction works | 3.2 Run via Docker | 3.3 Visualise

Donwload multi-band data from Greenspace Seasonality Data Cube with specified area/point of inerest | By bounding box | By place name | By coordinates (point) | By UID and time range | Download ESA WorldCover 10m Annual Dataset | Get NDVI data by place name | Get land cover data from ESA WorldCover 10m dataset | Download Sentinel-2 10m Land Use/Land Cover Time Series | Get LULC data by place name | Get LULC data by bounding box | Compare land cover change across years | Retrieve Sentinel-2-l2a images and compute NDVI | Get the greenspace segmentation from map tiles | Extract values from Greenspace Seasonality Data Cube with samples | Visualize Seasonal Greenspace Dynamics as an Animated GIF

Viewscape | 1. Compute viewshed | 1.1 Compute single viewshed | 1.2 Subset viewshed using by specifying the field of view | 1.3 Compute visual magnitude | 1.4 Compute the viewshed for multiple viewpoints | 1.5 Compute an intervisibility network | Adjacency matrix | Network as spatial lines | Per-viewpoint observer heights | 2. Calculate viewscape metrics | 2.1 Calculate the metrics of viewshed | 2.2 Calculate land use/cover diversity | 2.3 calculate a single feature | 3. Panoramic view | 3.1 Colour panorama (equirectangular, default) | 3.2 Land-cover / land-use panorama (equirectangular + semantic) | 3.3 Multi-layer semantic panorama | 4. Under-canopy visibility | 4.1 Preparing the layers | 4.2 Finding a viewpoint on the road and under the canopy | 4.3 The observer fix on its own | 4.4 The crown band: compute_viewshed_understory() | 4.5 The hemispherical view: pano_view_understory() | 4.6 Road corridors, and the cbh trap | 4.7 Foliage transmittance | 4.8 Which choices matter for which metric | 4.9 Known limitations

1 Get metadata of street view image from Mapillary | 1.1 search data using a bounding box | 1.2 search data using a proximity given coordinates in degree | 1.3 search data with filters | 1.4 search the nearest data given coordinates in degree (within a 10m buffer) | 1.5 batch search data using OSM road line | 2 Calculate the Green View Index | 3 Extract semantic segmentation | 4 Visualize the data in maps | 5 Download data | 6 Generate Qualtrics survey text file

1. construct pairwise comparison | Compute Elo rating

1. Get DSM raster data | 2. Get LiDAR data | 2.1 Get LiDAR data information via API | 2.2 Download LiDAR data with a given point and searching distance