GIG · Greenery Insights & Guidelines · NUS Kent Ridge
Campus
greenery,
quantified
The BEAM Greenery programme builds a comprehensive inventory of campus vegetation — mapping every tree, shrub, and turf area — and pairs it with localised temperature monitoring to understand how greenery composition drives cooling. Findings guide tree planting decisions and thermal comfort improvements across NUS.
01 — Data sources
Building the database
Four complementary data streams are fused into a single GIS and 3D model — capturing trees, shrubs, turf, and forested areas at campus scale. The integrated database underpins both the Digital Twin platform and ENVI-Met microclimate simulations.
Source 01
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GIS tree point shapefiles
Tree point data provided by University Campus Infrastructure (UCI), containing species, geospatial coordinates, height, canopy spread, and trunk girth for each tree on campus.
→ Tree locations & species library
Source 02
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LiDAR point cloud data
3D scanning point cloud used to derive accurate geometric information for vegetation beneath tree canopies — shrubs, groundcover, and turf — which cannot be reliably captured from aerial imagery alone.
→ Shrub & turf polygons
Source 03
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Digital elevation model
Satellite-derived DEM data used to model the dense forested areas of Kent Ridge — terrain-following greenery cover that cannot be represented as individual tree objects at scale.
→ Forest cover model
Source 04
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On-site survey
Ongoing collaboration with the NUS horticulture team enables manual labelling and verification of tree positions, improving GIS accuracy beyond what shapefile data alone can provide.
→ Verified tree positions
Step 1
GIS shapefile → 3D tree models
Step 2
Point cloud → shrub & turf geometry
Step 3
DEM → forested area terrain model
Output
Rhino 3D model · GIS layers · ENVI-Met
02 — Inventory indicators
Per-zone greenery metrics
Detailed greenery information is compiled for each administrative zone of the campus. These indicators are displayed in the Digital Twin platform and provide campus planners with a quantitative basis for evaluating vegetation coverage and cooling potential.
Indicator
GnPR
Green Plot Ratio — density of vegetation coverage
Indicator
Species
Tree species list per zone
Indicator
Height
Average tree height per species (m)
Indicator
Girth
Average trunk girth per species (m)
Indicator
Canopy
Average canopy spread per species (m)
Key metric — Green Plot Ratio (GnPR)
GnPR quantifies vegetation density by integrating the leaf area of each vegetation layer — big trees, small trees, shrubs, groundcover, and turf — weighted by Leaf Area Index (LAI), divided by site area. Higher values indicate denser, lusher vegetation with greater cooling potential. LAI values follow NParks recommended standards: trees 3–4, shrubs 3.5–4.5, turf 2.
GnPR = Σ(Aᵢ × LAIᵢ) / A_site
03 — Temperature monitoring
Greenery & microclimate
Air temperature sensors are deployed at locations with varied greenery composition across the campus — quantifying how different vegetation structures affect the thermal environment at pedestrian height.
12
Phase 1 locations Phase 1
Initial 12 greenery monitoring stations established during Phase 1 (March 2024 – May 2025), representing three common vegetation typologies across NUS Kent Ridge. Foundational dataset for understanding canopy cooling effects.
25
Phase 2 locations Phase 2
Expanded to 25 locations in Phase 2, adding sites at PGPR residence, UHC, S14, Science Carpark, Frontier, and MD9 — broadening coverage to residential zones and areas targeted for tree planting.
14+
Months of continuous data
Temperature recorded at 10-minute intervals using HOBO MX2202 Pendant Temperature/Light Data Loggers, averaged to hourly values. Sensors at 1.5 m height — the level at which pedestrians typically perceive ambient temperature.
Sensor specifications — ONSET HOBO MX2202
Instrument
ONSET HOBO MX2202 Pendant MX
Measurement range
−20°C to 70°C
Setup
1.5 m tripod · louvred radiation shield · 10-min interval
Vegetation typologies studied
Type A
Turf with trees
Sites with mature tree canopy over open lawn. Ranges from dense overlapping canopy to scattered large trees. Generally the coolest typology due to shading and evapotranspiration from tree mass.
Examples: Opp. EA (WS1), Opp. CLB (WS7), Opp. CELC (WS9)
Type B
Turf with small trees or shrubs
Sites with recently planted or immature trees providing limited shade, or shrub-dominant ground cover with minimal canopy. Higher diurnal temperature variability due to greater solar exposure.
Examples: Opp. YIH (WS4), Under SDE4 (WS10), Opp. LT15 (WS6)
Type C
Turf with mixed shrubs & trees
Sites combining large canopy trees with a dense understorey of native shrubs and groundcover. Dense multi-layered vegetation provides sustained cooling and stable microclimatic conditions.
Examples: Nasi Ulam Garden (WS8), Beside AS5 (WS12), LKCNHM (WS2)
Site characterisation indices
Three complementary indices are measured at each monitoring location through site surveys and panoramic fisheye photography — capturing both 2D greenery area and 3D canopy structure.
GnPR
Green Plot Ratio
Quantifies vegetation density using leaf area index across all vegetation layers within a 20 m buffer. The primary indicator of cooling potential — driven mainly by large tree canopy mass.
SVF
Sky View Factor
Proportion of sky visible from the point of measurement (0 = fully enclosed, 1 = fully open). Derived from fisheye photography processed with Tree Shade Mapper. Higher SVF correlates with greater solar exposure and temperature variability.
TVF
Tree View Factor
Proportion of the fisheye field of view occupied by tree canopy. Sites with higher TVF tend to show smaller diurnal temperature ranges — indicating tree canopy as a stabilising influence on the local thermal environment.
Monitoring locations
Campus deployment map
All 25 greenery monitoring locations across NUS Kent Ridge — Phase 1 (sites 1–12) and Phase 2 additions (sites 13–25, including PGPR and residential zones).
Map data © Google · Phase 1 locations as of March 2024 · Phase 2 locations ongoing · Open full map ↗
04 — Findings
What the data shows
Preliminary analysis across the 12 Phase 1 stations reveals a clear link between vegetation structure and thermal performance — with large canopy trees emerging as the dominant driver of localised cooling.
Key finding
GnPR closely tracks the pattern of large tree canopy — not shrubs or ground cover alone. Tree shadows provide consistently stronger cooling effects on air temperature than other vegetation types. Stations with higher TVF and GnPR show smaller diurnal temperature ranges, indicating that dense canopy moderates the thermal environment throughout the day and night.
Stations with high SVF (open, sky-exposed) show the largest interquartile temperature ranges — confirming that canopy closure is the critical variable for pedestrian-level thermal comfort in tropical campus settings.
Large trees → greatest cooling
High SVF → more variability
High GnPR → stable temperatures
Annual temperature range across Phase 1 sites
WS8 · Nasi Ulam
IQR ~2.2°C
Smaller IQR = more thermally stable site. WS12 (dense mature canopy, high GnPR) vs. WS10 (sparse young shrubs, SVF 0.69) shows a nearly 2°C difference in temperature variability. Annual mean temperatures across all 12 sites range from 23.5°C to 34.6°C. BEAM Ph.1 §5
05 — Research
Related publications
Peer-reviewed work underpinning the BEAM greenery database, monitoring methodology, and thermal comfort findings.
Journal of Digital Landscape Architecture · 2025
Lu, Y., et al. (2025) Integrating Multisource Data for Comprehensive Greenery Modeling in a Digital Twin — A Case Study of a Singapore Campus
Read ↗
CISBAT 2025
Gottkehaskamp, B., et al. (2025) Walking the Heat: Why Thermal Walks Matter for High Resolution Microclimate Mapping
Read ↗
ASim 2024
Ignatius, M., et al. (2024) Digital Twin and Wearables Unveiling Pedestrian Comfort Dynamics and Walkability in Cities
Read ↗
Landscape and Urban Planning · 2008
Wong, N.H. and Jusuf, S.K. (2008) GIS-based greenery evaluation on campus master plan
Read ↗
BEAM GIG — Greenery Insights & Guidelines is one of five Phase 2 work packages. The greenery database and monitoring network support the broader goal of guiding the planting of ~50,000 additional trees across NUS as part of the 120,000 Tree Planting Campaign, and informing evidence-based campus greening guidelines. Data collected under this programme are also integrated into the ClimaTwin Digital Twin for real-time visualisation and scenario testing.
