Calgary’s Summer Heat: A 2025 Satellite Perspective

This study is part of the development of the Multi-Dimensional Environmental Matrix (MDEM) for Calgary—a system of geospatial data processing algorithms designed for the in-depth analysis of urban environments and ecological sustainability.

Why Does It Matter?

The Urban Heat Island (UHI) effect is more than just a matter of personal comfort, escalating cooling costs, or declining solar photovoltaic (PV) efficiency. From an environmental geochemistry perspective, the overheating of urban surfaces triggers a cascade of invisible yet destructive processes:

• Photochemical Smog: High temperatures catalyze reactions between vehicle exhaust and volatile organic compounds (VOCs), leading to the formation of ground-level ozone (O₃) and formaldehyde (CH₂O)—toxic oxidants that impact respiratory health and vegetation.
• Alteration of the Nitrogen Cycle: On overheated lawns, the decomposition of fertilizers accelerates, leading to reduced nutrient efficiency and excessive ammonia (NH₃) emissions into the urban atmosphere.
• Material Outgassing: According to the laws of thermodynamics, the heating of asphalt, polymers, and coatings increases vapor pressure, “forcing out” volatile compounds even from aging construction materials.
• Impact on Aquatic Ecosystems: Scouring storm runoff from scalding road surfaces causes thermal shock and oxygen depletion in local ponds and rivers, which is critical for fish. Furthermore, rising water temperatures alter the chemical speciation and mobility of various elements.

Methodology and Data

The research is based on data from the Landsat 8/9 (USGS) and Sentinel-2 (ESA) missions collected between June and August 2025. The primary dataset comprises over 242 million individual measurements which, through geometric clipping, quality validation, and temporal averaging, were refined into two synchronized datasets (LST and NDVI) consisting of 950,802 pixels each.

To classify thermal zones, Tukey’s Fences method was applied. This approach allows for a statistically sound separation of typical “background” values from extreme thermal anomalies (outliers), eliminating subjective “by-eye” classification.

Calgary’s Thermal Load Scale:

1. Urban Cool Island: ≤23.06°C (pronounced cold zones).
2. Cool Background: 23.06°C−30.78°C (comfortable background).
3. Typical Core: 30.78°C−35.93°C (urban norm, representing 50% of the city area).
4. Warm Background: 35.93°C−43.66°C (heated background).
5. Moderate Surface Urban Heat Anomaly (SUHA): 43.66°C−51.38°C (moderate anomaly).
6. Extreme Surface Urban Heat Anomaly : 51.38°C (extreme overheating).

Thermal Anomaly Map

The analysis reveals a clear differentiation: the western part of the city is predictably cooler than the east. Extreme overheating zones are localized within industrial and business districts, while river valleys and large forested areas (such as Fish Creek Park or Nose Hill) form the “cool island” framework.

For local residents, a ranking of established residential communities by average summer surface temperature has been prepared.

Community	LST 2025
MARLBOROUGH	37.81
RUNDLE	37.6
PENBROOKE MEADOWS	37.55
MANCHESTER	37.45
FOREST LAWN	37.37
MARTINDALE	37.29
CASTLERIDGE	37.22
TEMPLE	37.19
PINERIDGE	37.14
MARLBOROUGH PARK	37.13
WHITEHORN	37.01
GREENVIEW	36.84
FALCONRIDGE	36.73
NORTH HAVEN	36.64
MEADOWLARK PARK	36.6
TUXEDO PARK	36.57
FOREST HEIGHTS	36.51
NORTH HAVEN UPPER	36.47
SETON	36.43
TARADALE	36.43
BRENTWOOD	36.35
ERIN WOODS	36.35
APPLEWOOD PARK	36.29
MILLRISE	36.26
NEW BRIGHTON	36.25
KILLARNEY/GLENGARRY	36.2
HUNTINGTON HILLS	36.19
BEDDINGTON HEIGHTS	36.15
WALDEN	36.12
GARRISON WOODS	36.1
ROSSCARROCK	36.1
REDSTONE	36.09
SHAWNESSY	36.03
MAHOGANY	35.98
HARVEST HILLS	35.95
AUBURN BAY	35.89
BANFF TRAIL	35.87
ABBEYDALE	35.79
COVENTRY HILLS	35.78
COUNTRY HILLS VILLAGE	35.77
THORNCLIFFE	35.73
MCKENZIE TOWNE	35.72
MOUNT PLEASANT	35.72
HOUNSFIELD HEIGHTS/BRIAR HILL	35.7
CAPITOL HILL	35.68
GLENBROOK	35.66
EVERGREEN	35.6
LOWER MOUNT ROYAL	35.59
SKYVIEW RANCH	35.58
MAYLAND HEIGHTS	35.56
HIGHWOOD	35.55
MONTEREY PARK	35.55
RED CARPET	35.54
ST. ANDREWS HEIGHTS	35.53
QUEENSLAND	35.47
SOUTHWOOD	35.46
SOUTH CALGARY	35.43
BELTLINE	35.39
SADDLE RIDGE	35.36
UNIVERSITY OF CALGARY	35.34
HILLHURST	35.31
SOMERSET	35.3
BONAVISTA DOWNS	35.27
CAMBRIAN HEIGHTS	35.23
WEST HILLHURST	35.23
DEER RIDGE	35.21
CRESCENT HEIGHTS	35.15
HIGHLAND PARK	35.14
RUTLAND PARK	35.13
ALBERT PARK/RADISSON HEIGHTS	35.1
KINGSLAND	35.1
SUNALTA	35.1
UNIVERSITY DISTRICT	35
CORAL SPRINGS	34.98
ACADIA	34.94
RICHMOND	34.94
SIGNAL HILL	34.94
EVANSTON	34.92
SUNDANCE	34.91
PANORAMA HILLS	34.87
CANYON MEADOWS	34.85
BRIDLEWOOD	34.84
FAIRVIEW	34.84
MIDNAPORE	34.84
LAKE BONAVISTA	34.82
CITADEL	34.81
SANDSTONE VALLEY	34.8
UNIVERSITY HEIGHTS	34.78
LINCOLN PARK	34.76
CHRISTIE PARK	34.68
ARBOUR LAKE	34.61
ALTADORE	34.6
RANCHLANDS	34.6
ROSEDALE	34.59
CHARLESWOOD	34.54
GLAMORGAN	34.54
BANKVIEW	34.48
RENFREW	34.46
PARKLAND	34.45
MACEWAN GLEN	34.4
VISTA HEIGHTS	34.39
MISSION	34.37
WESTGATE	34.37
CHAPARRAL	34.36
SHAWNEE SLOPES	34.33
CLIFF BUNGALOW	34.29
WILLOW PARK	34.29
NOLAN HILL	34.26
ROSEMONT	34.25
NORTH GLENMORE PARK	34.24
RAMSAY	34.2
HAYSBORO	34.17
DOVER	34.15
BRAESIDE	34.14
DEER RUN	34.14
DOWNTOWN WEST END	34.14
CEDARBRAE	34.13
PARKDALE	34.08
KELVIN GROVE	34.03
SCARBORO	33.97
SHERWOOD	33.95
COACH HILL	33.94
RIVERBEND	33.91
STRATHCONA PARK	33.89
DALHOUSIE	33.86
GLENDALE	33.85
PALLISER	33.84
OGDEN	33.77
WOODBINE	33.77
RANGEVIEW	33.75
KINCORA	33.73
SCARBORO/SUNALTA WEST	33.7
COLLINGWOOD	33.66
CHINOOK PARK	33.64
HAWKWOOD	33.6
ELBOYA	33.53
HIDDEN VALLEY	33.5
VARSITY	33.46
TUSCANY	33.42
COUNTRY HILLS	33.38
DOWNTOWN EAST VILLAGE	33.32
DOWNTOWN COMMERCIAL CORE	33.31
ROYAL OAK	33.25
DOUGLASDALE/GLEN	33.2
PARKHILL	33.18
ROCKY RIDGE	33.18
WOODLANDS	33.18
LAKEVIEW	33.17
MONTGOMERY	33.14
SCENIC ACRES	33.13
MCKENZIE LAKE	33.1
EDGEMONT	33.09
SILVER SPRINGS	33.06
MAPLE RIDGE	32.99
BOWNESS	32.97
SOUTHVIEW	32.88
GREENWOOD/GREENBRIAR	32.82
DIAMOND COVE	32.77
MAYFAIR	32.73
BRITANNIA	32.66
OAKRIDGE	32.64
EAGLE RIDGE	32.56
PATTERSON	32.49
WINDSOR PARK	32.47
SPRUCE CLIFF	32.45
COUGAR RIDGE	32.37
WINSTON HEIGHTS/MOUNTVIEW	32.32
SUNNYSIDE	32.31
HUXLEY	32.1
CORNERSTONE	32.07
BEL-AIRE	32.04
ERLTON	31.95
HAMPTONS	31.94
PUMP HILL	31.9
BRIDGELAND/RIVERSIDE	31.86
QUEENS PARK VILLAGE	31.79
BAYVIEW	31.66
SYMONS VALLEY RANCH	31.56
UPPER MOUNT ROYAL	31.56
SHAGANAPPI	31.45
ELBOW PARK	31.26
INGLEWOOD	31.25
CHINATOWN	31.22
POINT MCKAY	30.78
WILDWOOD	30.66
VALLEY RIDGE	30.44
CRESTMONT	30.36
MEDICINE HILL	29.82
EAU CLAIRE	29.74
RIDEAU PARK	29.73
DISCOVERY RIDGE	29.56
ROXBORO	29.51
OSPREY HILL	28.85

Spatial Synthesis: Where Heat Meets Green

To provide a comprehensive visualization of the interplay between urban heat and biomass, a bivariate choropleth map was developed. Unlike standard maps displaying a single metric, this method utilizes a two-dimensional color scale to simultaneously analyze LST (Y-axis) and NDVI (X-axis).

Map Interpretation:

• Bright Magenta Zones (Top Left): Thermal Stress Zones. These are areas with high temperature and low vegetation density. The map clearly localizes them within the NE and SE industrial hubs, along major transportation corridors, and in treeless residential developments. These zones correspond to the functional “thermal inertia regime” identified in the regression analysis.
• Bright Green Zones (Bottom Right): Thermal Stability Zones. Areas with low temperature and high vegetation density. These are Calgary’s “green lungs”: the Bow and Elbow river valleys, Fish Creek Park, Nose Hill. They serve as benchmarks for climatic comfort.
• Dull/Muddy Zones (Center Left): Areas where both temperature and vegetation are at moderate levels.

This cartogram serves as a key diagnostic tool within the MDEM Framework. It does more than just show the problem of overheating; it instantly identifies territories where vegetation deficit is a direct driver of extreme temperatures. This ensures that the selection of sites for targeted greening (the ROI strategy) is maximally accurate and evidence-based.

Vegetation Efficiency: The Mathematical Threshold

While the link between vegetation (NDVI) and land surface temperature (LST) is well-known, this study mathematically identifies the “trigger point” for natural cooling.

Using segmented regression (structural break analysis), I observed that the relationship is non-linear. Several “break-points” are evident in the data, the most significant being NDVI = 0.34.

• Below the 0.34 Threshold: Vegetation is too sparse to significantly impact the thermal balance; surfaces continue to heat up similarly to bare concrete.
• Above the 0.34 Threshold: A sharp regime shift occurs. Cooling efficiency (the slope of the curve) increases by a factor of 4.5. This shift is attributed to reaching a critical biomass mass required for active evapotranspiration and effective shading.
• At NDVI 0.49: The effect intensifies further (by an additional 1.25 times). Overall, areas with an NDVI of 0.49 or higher cool 5.6 times more effectively than sparsely vegetated sites.
• Beyond the 0.76 Threshold: The final detected breakpoint marks the transition of the “vegetative cooling engine” into a steady-state regime. Past this point, the cooling rate significantly levels off, indicating diminishing returns. This represents a thermal saturation point where additional biomass (e.g., transitioning from a dense park to a thick forest) yields minimal further reduction in surface temperature.

These findings allow for the identification of “reference” areas in Calgary that can serve as natural benchmarks for planning future developments. Moreover, leveraging the non-linear nature of the LST-NDVI relationship enables high-precision site selection for urban greening. Since the “vegetative cooling engine” exhibits a threshold-dependent activation (identified at 0.34 for 2025 conditions), strategic intervention in areas currently near this tipping point offers the maximum Return on Investment (ROI). Targeting these “high-leverage” zones ensures the greatest thermal mitigation benefit for every unit of added green infrastructure.

Technical Appendix

• LST Data: Based on the USGS Surface Temperature (Level 2) product. Only pixels with N > 4 valid measurements per season were included in the calculations. Areas with zero valid pixels were identified at the Rocky Ridge YMCA roof (likely flagged as “snow” by the USGS cloud mask) and a specific commercial zone in NE Calgary (Sunridge Blvd/27 St NE).

• NDVI Data: Calculated using COPERNICUS/S2_SR_HARMONIZED (Sentinel-2) with Bottom of Atmosphere (BOA) atmospheric correction. Similar to LST, a threshold of > 4 valid observations was applied to calculate the median summer NDVI.
• Statistics: The non-linear relationship was modeled using Segmented Linear Regression with automatic iterative breakpoint detection (R package ‘segmented’). To maintain computational efficiency while ensuring representativeness, a pseudo-random sample of 40,000 pixel pairs was drawn from the full Calgary dataset.
  The optimal number of breakpoints was determined by minimizing the Bayesian Information Criterion (BIC), ensuring a rigorous balance between model complexity and statistical goodness-of-fit.
  The final model achieved an Adjusted R² of 0.39, with highly significant structural breaks identified. The narrow standard errors for the primary breakpoint (0.34±0.008) confirm the stability of the identified ecological threshold.

Disclaimer: This independent study is conducted for scientific and educational purposes (CC-BY 4.0). The maps and conclusions are based on remote sensing methods and do not constitute an official engineering opinion. Consult with a practicing Professional Member of APEGA before making design, construction, or public health decisions.