#greennessofcalgary — Public Fediverse posts

Honored to share that my spatial analytics research has been featured as an official Success Story on The City of Calgary’s Open Data Portal.

The feature highlights how open municipal datasets can be combined with remote sensing data to evaluate urban heat islands, land cover composition, and microclimate dynamics across Calgary neighbourhoods.

Key aspects of the project:
🔹 Processing multi-spectral satellite imagery to model surface temperature (LST) and vegetation dynamics.
🔹 Translating complex spatial data into accessible, decision-ready insights for climate resilience and urban planning.
🔹 Demonstrating the practical impact of open data in civic-focused research.

A sincere thank you to The City of Calgary Open Data team for recognizing this work and highlighting the value of turning raw open data into actionable insights.

Read the full story here: https://www.calgary.ca/research/open-data/articles/where-data-meets-sustainability.html

#GIS #SpatialData #RemoteSensing #OpenData #Calgary #ClimateResilience #DataScience #UrbanPlanning #GreennessOfCalgary

📈 Imperviousness vs. Temperature: Calgary's Primary Thermodynamic Trend

Mapping 313 Calgary communities reveals a linear relationship between % impervious surface area (Random Forest model on Summer 2025 Sentinel-1/2 & Landsat 8/9) and Land Surface Temperature (LST).

📊 Key Data Points:
• Cool Pole (<28°C, 0–15% impervious): Glenmore Park, Fish Creek (water & mature canopy).
• Hot Pole (37–40°C, 85–95% impervious): Industrial (Franklin, Foothills) & residential (Marlborough, Rundle).
• Thermal Slope: Every +10% impervious cover adds +1.2°C to +1.5°C to LST.

🔬 Variance Drivers:
Material albedo, building geometry (shading), topography, and canopy vs. lawn structure.

💡 Takeaway:
Impervious cover is the dominant microclimate driver. Urban planning—road width, building footprint, and canopy retention—is direct thermodynamic engineering.

#Calgary #YYC #GIS #RemoteSensing #RStats #DataScience #UrbanHeat #CityPlanning #Microclimate #GreennessOfCalgary

📉 Comparing the Solid-to-Tree Ratio with the Land Surface Temperature (LST) data obtained in the previous phase of the study allows for a visual assessment of the relationship between surface sealing and summer surface heating across Calgary’s residential communities.
🔥 The plot reveals a strong pattern for the vast majority of communities: a sharp increase in temperature occurs within the ratio range of 0 to 5. The Downtown Commercial Core stands out as a distinct outlier, where low LST values are driven by deep geometric shading from high-rise buildings. Additionally, neighborhoods such as Manchester, Seton, Redstone, Beltline, and Rangeview, among a few others, slightly diverge from the main trend.
📊 Full methodology and additional charts via the link:👇
https://www.datastory.org.ua/calgarys-microclimatic-anatomy-what-lies-beneath-the-citys-green-appearance/

#Calgary #OpenData #UrbanHeat #DataScience #ClimateResilience #YYC #Geoscience #CityPlanning #RemoteSensing #RStats #MachineLearning #GreennessOfCalgary

Which Calgary neighborhoods are best built to withstand summer heatwaves? 🌳☀️

To measure structural climate resilience across the city, I conducted a spatial analysis of 193 established residential communities, calculating the Solid-to-Tree Ratio—comparing bare artificial surfaces (asphalt, concrete, rooftops) directly against total tree canopy area.

Here are the Top 10 most shade-rich and climate-resilient communities in Calgary:
🟢 Queens Park Village — 0.3 (Just 0.3 ha of hard surface for every 1 ha of canopy!)
🟢 Discovery Ridge — 0.5
🟢 Roxboro — 0.5
🟢 Wildwood — 0.6
🟢 Rideau Park — 0.7
🟢 Medicine Hill — 0.8
🟢 Upper Mount Royal — 0.8
🟢 Crestmont — 0.9
🟢 Elbow Park — 0.9
🟢 Shaganappi — 0.9

👇 The full interactive dataset and study are here:
https://www.datastory.org.ua/calgarys-microclimatic-anatomy-what-lies-beneath-the-citys-green-appearance/

#UrbanAnalytics #GeospatialData #RemoteSensing #GIS #UrbanForestry #CityPlanning #Calgary #DataScience #Microclimate #MachineLearning #GreennessOfCalgary #RStats #FOSSGIS

🔥 Top 10 Calgary Communities with the Highest "Shade Deficit"

To measure structural heat risks, I calculated the Solid-to-Tree Ratio—the ratio of bare artificial surfaces (asphalt, concrete, roofs) to total tree canopy area. A higher ratio means more heat-retaining concrete and less natural cooling.

Here are the 10 most shade-deficient residential communities in Calgary:
🔹 Downtown Commercial Core — 56.2 (56.2 ha of hard surfaces for every 1 ha of trees)
🔹 Beltline — 24.6
🔹 Redstone — 23.8
🔹 Seton — 20.8
🔹 Manchester — 17.7
🔹 Rangeview — 16.8
🔹 Symons Valley Ranch — 16.0
🔹 Lower Mount Royal — 13.9
🔹 Country Hills Village — 13.2
🔹 Martindale — 12.4

An interactive lookup table featuring area metrics and ratios for all 193 established Calgary residential communities is available via the link:
https://www.datastory.org.ua/calgarys-microclimatic-anatomy-what-lies-beneath-the-citys-green-appearance/

#YYC #Calgary #CalgaryRealEstate #UrbanForestry #CityPlanning #RemoteSensing #YycLiving #GreennessOfCalgary #MachineLearning #RStats #Alberta #Canada

🔥 It looks like it's time to lock in the current version of the machine learning model (LULC v.6.0). Validation results on an independent test dataset (Confusion Matrix) demonstrate the excellent predictive power of the algorithm:
🔹 Overall Accuracy: 98.29% (95% CI: 98.16% – 98.41%) with a No Information Rate = 60.28% (p-value < 2.2e-16).
🔹 Cohen’s Kappa: 0.9691, confirming high classification reliability even with severe class imbalance.
The model shows a very low error rate for non-vegetated areas (Solid, Balanced Accuracy 99.72%) and water bodies (Water, 99.75%), but expectedly faces challenges at the boundaries between the Lawn (open grass) and Park (sparse trees) classes.
Currently, I am moving on to an advanced analysis of the drivers shaping Urban Heat Islands (UHI) in Calgary and preparing a publication for my website. Stay tuned for updates!
#Calgary #OpenData #UrbanHeat #DataScience #ClimateResilience #YYC #Geoscience #CityPlanning #RemoteSensing #RStats #MachineLearning #GreennessOfCalgary

One more quick byproduct of my MDEM development: a bivariate map integrating volumetric structural data (SAR) with surface temperature (LST). This approach identifies the exceptionally intensive dissipative role of volumetric vegetation structure (trees and tall shrubs). By accounting for these high-performance cooling elements, we can better understand how they supplement traditional landscaping to enhance the city's overall thermal resilience.

#UrbanHeatIsland #EnvironmentalScience #DataScience #Calgary #YYC #Sustainability #RemoteSensing #GIS #MDEM #GreennessOfCalgary #CalgaryMDEM #RStats #UrbanPlanning #EarthObservation #OpenScience #SpatialDataScience #SpatialData