#remotesensing

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📉 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
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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
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🔥 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
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🌳 Is Calgary actually as green as it looks? While open lawns (28.6% citywide) give Calgary a visual "green appearance", dry summer conditions quickly strip unirrigated grass of its cooling capacity. Meanwhile, true cooling infrastructure — dense and sparse tree canopy — accounts for only ~17%. To quantify structural heat risks, I introduced the Solid-to-Tree Ratio index across 193 residential communities: 🔹 Critical Deficit: Downtown Core (56.2) and Beltline (24.6), where hard surfaces outnumber tree canopy by tens of times. 🔹 Suburban Pressure: New communities like Redstone (23.8) and Seton (20.8) feature high-density lots with minimal mature shade. 🔹 Ecological Buffers: River valley communities like Discovery Ridge (0.5) and Wildwood (0.6), where canopy exceeds concrete. 👇 Link to the full study and interactive dataset: https://www.datastory.org.ua/calgarys-microclimatic-anatomy-what-lies-beneath-the-citys-green-appearance/ #Calgary #YYC #DataScience #GIS #RStats #RemoteSensing #UrbanHeat #DataViz #SpatialAnalysis #MachineLearning #GreennessOfCalgary #FOSSGIS #Alberta #Canada
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🌳 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
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📊 Beyond Averages: Spatial Heterogeneity in Calgary (LULC v6.0) Averages mask reality. To capture ecological stratification across Calgary's residential communities (excl. major parks/building-out and industrial zones), I combined Violin + Box Plots: 🔹 Solid (Impervious): Median ~67% (IQR 55–74%). High-thermal non-vegetated surfaces are a systemic structural feature across nearly all neighborhoods. 🔹 Park vs. Lawn (Canopy vs. Turf): Park median (~20%) doubles Lawn (~10%). A long upper tail (>50%) highlights spatial inequality in tree cover. 🔹 Forest & Water: Near 0% for 95% of communities, but sharp needles (up to 25% forest, 16% water) mark outliers with lakes or remnant woods. 💡 Takeaway: Calgary isn't homogenous—microclimatic comfort heavily depends on geographic boundaries. Full analysis coming soon: https://www.datastory.org.ua/ #Calgary #YYC #DataScience #GIS #RStats #RemoteSensing #UrbanHeat #DataViz #SpatialAnalysis #MachineLearning #GreennessOfCalgary #FOSSGIS #OpenData #OpenSource #TreeEquity
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#Introduction — I'm a geospatial scientist (PhD, Earth System & Geoinformation Science) and I teach GIS and remote sensing at the University of North Dakota. I build Earth-observation pipelines and GeoAI models for drought, vegetation, water quality, and land-governance problems — much of it focused on Cameroon. Posting about #RemoteSensing #GIS #EarthObservation #DataScience and reproducible science. Portfolio: https://github.com/mbongowo/Data-science-Portfolio
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Hello Mastodon, an #introduction. I'm a geospatial scientist with a PhD in Earth System and Geoinformation Science. I work in remote sensing and #GeoAI, mostly on drought, vegetation, and land — in Africa and the US Great Plains. I'll mostly post maps, model results, and #GoogleEarthEngine and Python tutorials (#geopandas, #rasterio). I'm also building a national GIS data portal for #Cameroon. #RemoteSensing #GIS #EarthObservation #Python
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It is a common belief that higher elevations are naturally cooler. In pristine landscapes, this rule holds firm. But what about urban environments? Humanity moves vast amounts of matter and energy, sometimes fundamentally altering the thermodynamic parameters of our habitat. 🛰️ I correlated summer Land Surface Temperature (LST) data across Calgary’s neighborhoods with the Canadian Medium-Resolution Digital Elevation Model (MRDEM). The chart below illustrates the relationship between "Average Elevation" and "Average Surface Temperature" specifically for established residential communities. As observed, this relationship is notably weak, even though a slight cooling trend persists. Based on my data analysis, elevation above sea level is not a key factor in cooling the city. #Calgary #OpenData #UrbanHeat #DataScience #ClimateAction #YYC #GreennesOfCalgary #ClimateEquity #EnvironmentalEquity #CityPlanning #RemoteSensing #RStats #Landsat #fossgis #DigitalElevationModel
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To distinguish between "normal" and anomalous surface temperatures in Calgary in 2025, I applied Tukey’s method. The statistical distribution shows a negative skewness (coefficient ≈−0.59). This highlights a critical phenomenon: the vast majority of the urban area is densely clustered in the warmer temperature range. In contrast, cool refuges (the rivers, reservoir, and dense parks) are statistically scarce, forming a long "tail" on the left side of the plot. In essence, Calgary’s baseline is shifted toward higher temperatures, making Urban Cool Islands a rare and vital resource. I would like to remind my readers and followers that I am currently preparing a comprehensive article based on these research results. In it, I will explore the ecological and geochemical implications of this thermal distribution. Stay tuned for further updates! #YYC #Calgary #ClimateResilience #UrbanHeatIsland #DataAnalytics #RemoteSensing #Landsat #OpenData #CitizenScience #LST #ClimateOfCalgary #Landsat #Rstats
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