Visualisation

The BEAM-DT interface brings together sensor streams, spatial models, and machine learning outputs into an interactive campus map — enabling real-time and historical exploration of the NUS microclimate.

Visualisation 01

Weather station popup

Clicking any of the 40 weather station markers opens a popup showing the station name, a site photo, and a set of tabbed time-series charts. Each tab corresponds to a measured parameter.

Live · updated hourly Air temperature Solar irradiance Wind speed & direction Relative humidity OTCI comfort index Rainfall Urban morphology

WS popup with charts open
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Current view: past 30 days of hourly readings. · Historical archive: monthly compiled files since late 2023. · The Urban Morphology tab displays a 360° fisheye image from each station's location, capturing sky view factor and surrounding obstruction context.

Ref: Desai et al. CISBAT 2025 §2.2 · BEAM Phase 1 Report §4.5.1

Visualisation 02

Met tower — vertical profile

The meteorological tower popup displays a time × height heatmap — each cell representing a measured value at a specific height (3, 6, 9, or 12 m) and hour. Clicking any cell updates the chart below to show the full vertical profile at that timestamp.

Met tower popup · heatmap
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How it works

Click → vertical profile

The heatmap gives an overview of how conditions vary across time and height. Selecting a cell isolates that hour and redraws the profile chart below — showing how temperature, humidity, or wind changes from 3 m up to 12 m above ground.

This reveals near-surface thermal gradients that single-height stations cannot capture — critical for understanding pedestrian-level heat exposure versus conditions higher in the urban canopy.

Ref: BEAM Phase 1 Report §4.5.2

Visualisation 03

Thermal camera viewer

Each of the 6 IR camera markers opens a dual-panel viewer — a thermal infrared image alongside a visible reference image — allowing direct comparison of surface temperature patterns with physical context.

IR camera popup · thermal + visible
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Thermal image: 464 × 348 px, captured every 30 minutes — surface temperature map across the camera's field of view. · Visible reference: captured every 60 minutes for environmental context. · Nearby weather data from the closest weather station is displayed alongside each image.

Ref: Desai et al. CISBAT 2025 §2.3 · BEAM Phase 1 Report §4.5.3

Visualisation 04

Microclimate heatmap overlay

A campus-wide predictive layer rendered as a 50 m grid over the interactive map — three toggleable overlays, each with its own colour scale and time scrubber for hour-by-hour navigation.

ML-predicted · hourly Air temperature (°C) OTCI comfort index LCZ classification zones

Campus-wide microclimate heatmap overlay

Campus heatmap overlay
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Air temperature predictions are generated by a machine learning model trained on the sensor network, producing spatially continuous estimates across the campus at 50 m resolution. The OTCI (Outdoor Thermal Comfort Index) layer integrates temperature, humidity, wind, and radiation into a single comfort metric. LCZ zones classify the campus by urban morphology type — informing how local climate varies between dense built-up areas, open spaces, and vegetated zones.

Ref: Desai et al. CISBAT 2025 §2.4 · BEAM Phase 1 Report §4.5.1

Visualisation 05

Greenery zone panel

Clicking an administrative zone on the DT map opens a panel with aggregated greenery metrics for that zone — directly sourced from the GIS–Rhino synchronised vegetation database.

Greenery zone panel
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Per-zone metrics

Green Plot Ratio

Each zone panel displays Green Plot Ratio (GnPR) — the ratio of total leaf area to site area — alongside total tree count and canopy coverage area. These metrics are calculated directly from the 3D vegetation model synchronised with ArcGIS Pro.

The five administrative zones (1, 2, 3, 4, 7) correspond to NUS's campus management divisions — enabling zone-by-zone comparison of green cover density and informing targeted planting strategies.

Ref: BEAM Phase 1 Report §4.5.3 · Lu et al. (2025) Journal of Digital Landscape Architecture