#greennessofcalgary — Public Fediverse posts

🛰️ On September 28, I will be presenting at Data for Good (Calgary) on “Satellite Remote Sensing & Open Data: From Earth Observation to Measurable Public Impact in Calgary”.
💻 The talk will focus on the technical workflow: ingesting and processing multi-sensor Sentinel and Landsat imagery using Google Earth Engine and R, machine learning for land cover classification, and modeling neighborhood-scale land surface temperature (LST) patterns across the city.

🌳 We will also discuss the role of spatial data science and data visualization in informing local urban climate resilience and municipal open data initiatives. Looking forward to the technical discussion, Q&A, and connecting with Calgary’s data and geospatial community.

🔗 Registration link is here:
https://meetu.ps/e/QgbbR/ZtysN/i

#DataForGoodYYC #Geospatial #RemoteSensing #RStats #GoogleEarthEngine #OpenData #Calgary #EnvironmentalData #GreennessOfCalgary

🛰️ On September 28, I will be presenting at Data for Good (Calgary) on “Satellite Remote Sensing & Open Data: From Earth Observation to Measurable Public Impact in Calgary”.
💻 The talk will focus on the technical workflow: ingesting and processing multi-sensor Sentinel and Landsat imagery using Google Earth Engine and R, machine learning for land cover classification, and modeling neighborhood-scale land surface temperature (LST) patterns across the city.

🌳 We will also discuss the role of spatial data science and data visualization in informing local urban climate resilience and municipal open data initiatives. Looking forward to the technical discussion, Q&A, and connecting with Calgary’s data and geospatial community.

🔗 Registration link is here:
https://meetu.ps/e/QgbbR/ZtysN/i

#DataForGoodYYC #Geospatial #RemoteSensing #RStats #GoogleEarthEngine #OpenData #Calgary #EnvironmentalData #GreennessOfCalgary

🛰️ On September 28, I will be presenting at Data for Good (Calgary) on “Satellite Remote Sensing & Open Data: From Earth Observation to Measurable Public Impact in Calgary”.
💻 The talk will focus on the technical workflow: ingesting and processing multi-sensor Sentinel and Landsat imagery using Google Earth Engine and R, machine learning for land cover classification, and modeling neighborhood-scale land surface temperature (LST) patterns across the city.

🌳 We will also discuss the role of spatial data science and data visualization in informing local urban climate resilience and municipal open data initiatives. Looking forward to the technical discussion, Q&A, and connecting with Calgary’s data and geospatial community.

🔗 Registration link is here:
https://meetu.ps/e/QgbbR/ZtysN/i

#DataForGoodYYC #Geospatial #RemoteSensing #RStats #GoogleEarthEngine #OpenData #Calgary #EnvironmentalData #GreennessOfCalgary

🛰️ On September 28, I will be presenting at Data for Good (Calgary) on “Satellite Remote Sensing & Open Data: From Earth Observation to Measurable Public Impact in Calgary”.
💻 The talk will focus on the technical workflow: ingesting and processing multi-sensor Sentinel and Landsat imagery using Google Earth Engine and R, machine learning for land cover classification, and modeling neighborhood-scale land surface temperature (LST) patterns across the city.

🌳 We will also discuss the role of spatial data science and data visualization in informing local urban climate resilience and municipal open data initiatives. Looking forward to the technical discussion, Q&A, and connecting with Calgary’s data and geospatial community.

🔗 Registration link is here:
https://meetu.ps/e/QgbbR/ZtysN/i

#DataForGoodYYC #Geospatial #RemoteSensing #RStats #GoogleEarthEngine #OpenData #Calgary #EnvironmentalData #GreennessOfCalgary

🛰️ On September 28, I will be presenting at Data for Good (Calgary) on “Satellite Remote Sensing & Open Data: From Earth Observation to Measurable Public Impact in Calgary”.
💻 The talk will focus on the technical workflow: ingesting and processing multi-sensor Sentinel and Landsat imagery using Google Earth Engine and R, machine learning for land cover classification, and modeling neighborhood-scale land surface temperature (LST) patterns across the city.

🌳 We will also discuss the role of spatial data science and data visualization in informing local urban climate resilience and municipal open data initiatives. Looking forward to the technical discussion, Q&A, and connecting with Calgary’s data and geospatial community.

🔗 Registration link is here:
https://meetu.ps/e/QgbbR/ZtysN/i

#DataForGoodYYC #Geospatial #RemoteSensing #RStats #GoogleEarthEngine #OpenData #Calgary #EnvironmentalData #GreennessOfCalgary

🌳 Quantifying Calgary’s Microclimatic Imbalance: The Solid-to-Tree Ratio

To evaluate the structural heat load across Calgary's communities, I calculated the ratio of high-thermal artificial surfaces to cooling tree canopy: Solid / (Park + Forest), based on my 2025 satellite land cover model (LULC v6.0).

Why this ratio matters:
🔹 Thermal Stress Indicator: It measures how many square meters of heat-absorbing surfaces (asphalt, concrete, roofs, bare soil) exist for every square meter of tree canopy.
🔹 Spatial Inequality: While mature western neighborhoods maintain ratios between 1.5 and 4, eastern and peripheral zones reach values from 10 to over 50.
🔹 Evidence-Based Planning: It moves the discussion from generic averages to identifying exact spatial boundaries where microclimatic mitigation is most needed.

Note: The map uses a logarithmic scale.

#Calgary #YYC #DataScience #GIS #RStats #RemoteSensing #UrbanHeat #DataViz #SpatialAnalysis #MachineLearning #GreennessOfCalgary #FOSSGIS #Sentinel1 #Sentinel2

My experiment with land-cover classification for Calgary using satellite imagery and with a machine-learning model trained on data from another continent.

The results turned out surprisingly good — most classes transferred almost perfectly.
The only noticeable shift was the Forest class: tree and shrub vegetation in the source region differs from Calgary’s, so the model mapped it conservatively here.

Still, the general structure of the landscape was captured very well, and community-level land-cover profiles look consistent.

#Rstats #RemoteSensing #GIS #MachineLearning #LandCover #Calgary #EarthObservation #LULC #GreennessOfCalgary #QGIS #UrbanHealth #Alberta #Canada #Sentinel #Copernicus #CopernicusSentinel #Sentinel1 #Sentinel2 #ESA #DataScience #FOSS #UrbanEcology #UrbanNature