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#ndvi — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #ndvi, aggregated by home.social.

  1. Remote Sensing And GIS-Supported Framework Of Pre-Monsoon Drought Assessment In Bangladesh (2000–2022) Using CHIRPS-Based SPI-3 And MODIS-Derived Vegetation And Temperature Indices
    --
    doi.org/10.1007/s12665-026-128 <-- shared paper
    --
    H/T MD. ABDULLAH AL MAMUNM | Studying PhD in Rural and Environmental Sciences
    “১ বছর ২০ দিন লেগে গেল! প্রথম ৪ জন রিভিউয়ারের প্রায় ৫০+ কমেন্টের পর মনে হয়েছিল আর এগোব না। তবে আমার সুপারভাইজার বলেছিলেন, “রিজেকশনের চেয়ে কমেন্ট ফেস করা ভালো।”
    --
    #GIS #spatial #mapping #remotesensing #Bangladesh #earthobservation #water #hydrology #premoonsoon #moonsoon #drought #CHIRPS #MODIS #SPI #vegetation #temperature #indices #parameters #SPI #NDVI #VCI #TCI #VHI #monitoring #droughts #agriculture #farming #crop #cultivation #yield #foodsecurity #weather #rainfall #precipitation #Pearsoncorrelation #geostatistics #irrigation #watersecurity #foodsecurity #policy #planning

  2. Remote Sensing And GIS-Supported Framework Of Pre-Monsoon Drought Assessment In Bangladesh (2000–2022) Using CHIRPS-Based SPI-3 And MODIS-Derived Vegetation And Temperature Indices
    --
    doi.org/10.1007/s12665-026-128 <-- shared paper
    --
    H/T MD. ABDULLAH AL MAMUNM | Studying PhD in Rural and Environmental Sciences
    “১ বছর ২০ দিন লেগে গেল! প্রথম ৪ জন রিভিউয়ারের প্রায় ৫০+ কমেন্টের পর মনে হয়েছিল আর এগোব না। তবে আমার সুপারভাইজার বলেছিলেন, “রিজেকশনের চেয়ে কমেন্ট ফেস করা ভালো।”
    --
    #GIS #spatial #mapping #remotesensing #Bangladesh #earthobservation #water #hydrology #premoonsoon #moonsoon #drought #CHIRPS #MODIS #SPI #vegetation #temperature #indices #parameters #SPI #NDVI #VCI #TCI #VHI #monitoring #droughts #agriculture #farming #crop #cultivation #yield #foodsecurity #weather #rainfall #precipitation #Pearsoncorrelation #geostatistics #irrigation #watersecurity #foodsecurity #policy #planning

  3. Remote Sensing And GIS-Supported Framework Of Pre-Monsoon Drought Assessment In Bangladesh (2000–2022) Using CHIRPS-Based SPI-3 And MODIS-Derived Vegetation And Temperature Indices
    --
    doi.org/10.1007/s12665-026-128 <-- shared paper
    --
    H/T MD. ABDULLAH AL MAMUNM | Studying PhD in Rural and Environmental Sciences
    “১ বছর ২০ দিন লেগে গেল! প্রথম ৪ জন রিভিউয়ারের প্রায় ৫০+ কমেন্টের পর মনে হয়েছিল আর এগোব না। তবে আমার সুপারভাইজার বলেছিলেন, “রিজেকশনের চেয়ে কমেন্ট ফেস করা ভালো।”
    --
    #GIS #spatial #mapping #remotesensing #Bangladesh #earthobservation #water #hydrology #premoonsoon #moonsoon #drought #CHIRPS #MODIS #SPI #vegetation #temperature #indices #parameters #SPI #NDVI #VCI #TCI #VHI #monitoring #droughts #agriculture #farming #crop #cultivation #yield #foodsecurity #weather #rainfall #precipitation #Pearsoncorrelation #geostatistics #irrigation #watersecurity #foodsecurity #policy #planning

  4. Remote Sensing And GIS-Supported Framework Of Pre-Monsoon Drought Assessment In Bangladesh (2000–2022) Using CHIRPS-Based SPI-3 And MODIS-Derived Vegetation And Temperature Indices
    --
    doi.org/10.1007/s12665-026-128 <-- shared paper
    --
    H/T MD. ABDULLAH AL MAMUNM | Studying PhD in Rural and Environmental Sciences
    “১ বছর ২০ দিন লেগে গেল! প্রথম ৪ জন রিভিউয়ারের প্রায় ৫০+ কমেন্টের পর মনে হয়েছিল আর এগোব না। তবে আমার সুপারভাইজার বলেছিলেন, “রিজেকশনের চেয়ে কমেন্ট ফেস করা ভালো।”
    --
    #GIS #spatial #mapping #remotesensing #Bangladesh #earthobservation #water #hydrology #premoonsoon #moonsoon #drought #CHIRPS #MODIS #SPI #vegetation #temperature #indices #parameters #SPI #NDVI #VCI #TCI #VHI #monitoring #droughts #agriculture #farming #crop #cultivation #yield #foodsecurity #weather #rainfall #precipitation #Pearsoncorrelation #geostatistics #irrigation #watersecurity #foodsecurity #policy #planning

  5. Remote Sensing And GIS-Supported Framework Of Pre-Monsoon Drought Assessment In Bangladesh (2000–2022) Using CHIRPS-Based SPI-3 And MODIS-Derived Vegetation And Temperature Indices
    --
    doi.org/10.1007/s12665-026-128 <-- shared paper
    --
    H/T MD. ABDULLAH AL MAMUNM | Studying PhD in Rural and Environmental Sciences
    “১ বছর ২০ দিন লেগে গেল! প্রথম ৪ জন রিভিউয়ারের প্রায় ৫০+ কমেন্টের পর মনে হয়েছিল আর এগোব না। তবে আমার সুপারভাইজার বলেছিলেন, “রিজেকশনের চেয়ে কমেন্ট ফেস করা ভালো।”
    --

  6. 🏡 Here is the data analysis for Calgary, Summer 2025. This chart shows the relationship between vegetation density (NDVI) and Land Surface Temperature (LST).

    🔥 The data reveals a critical "tipping point": vegetation only starts effectively cooling the environment once it reaches a specific density threshold. Below this threshold (the left side of the curve), green spaces stay just as hot as the surrounding concrete.
    Sparse or isolated trees don't act as air conditioners—they "burn" in the urban furnace right along with us.

    ❗ What does this mean for Calgary? Simply planting a few scattered trees isn't enough. To actually move the needle on temperature, we need dense, healthy green belts. Otherwise, it’s just a waste of water and resources.

    🔗 Link to the research: datastory.org.ua/calgarys-summ

    #Calgary #UrbanHeatIsland #NDVI #ClimateChange #UrbanPlanning #DataScience #Environment #YYC #BigData #ScienceMatters #GreennessOfCalgary #ClimateOfCalgary #rstats #RemoteSensing #OpenScience

  7. How hot was Calgary's neighborhood in 2025? 🛰️🌡️

    I processed satellite data from last summer to see how Calgary’s communities handle the heat. It turns out that not all greenery is equal. My research shows a clear "breakpoint" where the density of vegetation actually starts to drop the surface temperature.

    I’ve mapped the "Hottest" and "Coolest" communities — see where yours stands and why some "green" areas are still overheating.

    Full article and maps here:
    datastory.org.ua/calgarys-summ

    #RemoteSensing #Rstats #GreennesOfCalgary #ClimateOfCalgary #OpenData #FOSSGIS #ClimateResilence #Landsat #Sentinel2 #Calgary #Alberta #Canada #YYC #LST #NDVI

  8. How hot was Calgary's neighborhood in 2025? 🛰️🌡️

    I processed satellite data from last summer to see how Calgary’s communities handle the heat. It turns out that not all greenery is equal. My research shows a clear "breakpoint" where the density of vegetation actually starts to drop the surface temperature.

    I’ve mapped the "Hottest" and "Coolest" communities — see where yours stands and why some "green" areas are still overheating.

    Full article and maps here:
    datastory.org.ua/calgarys-summ

    #RemoteSensing #Rstats #GreennesOfCalgary #ClimateOfCalgary #OpenData #FOSSGIS #ClimateResilence #Landsat #Sentinel2 #Calgary #Alberta #Canada #YYC #LST #NDVI

  9. How hot was Calgary's neighborhood in 2025? 🛰️🌡️

    I processed satellite data from last summer to see how Calgary’s communities handle the heat. It turns out that not all greenery is equal. My research shows a clear "breakpoint" where the density of vegetation actually starts to drop the surface temperature.

    I’ve mapped the "Hottest" and "Coolest" communities — see where yours stands and why some "green" areas are still overheating.

    Full article and maps here:
    datastory.org.ua/calgarys-summ

    #RemoteSensing #Rstats #GreennesOfCalgary #ClimateOfCalgary #OpenData #FOSSGIS #ClimateResilence #Landsat #Sentinel2 #Calgary #Alberta #Canada #YYC #LST #NDVI

  10. How hot was Calgary's neighborhood in 2025? 🛰️🌡️

    I processed satellite data from last summer to see how Calgary’s communities handle the heat. It turns out that not all greenery is equal. My research shows a clear "breakpoint" where the density of vegetation actually starts to drop the surface temperature.

    I’ve mapped the "Hottest" and "Coolest" communities — see where yours stands and why some "green" areas are still overheating.

    Full article and maps here:
    datastory.org.ua/calgarys-summ

    #RemoteSensing #Rstats #GreennesOfCalgary #ClimateOfCalgary #OpenData #FOSSGIS #ClimateResilence #Landsat #Sentinel2 #Calgary #Alberta #Canada #YYC #LST #NDVI

  11. How hot was Calgary's neighborhood in 2025? 🛰️🌡️

    I processed satellite data from last summer to see how Calgary’s communities handle the heat. It turns out that not all greenery is equal. My research shows a clear "breakpoint" where the density of vegetation actually starts to drop the surface temperature.

    I’ve mapped the "Hottest" and "Coolest" communities — see where yours stands and why some "green" areas are still overheating.

    Full article and maps here:
    datastory.org.ua/calgarys-summ

    #RemoteSensing #Rstats #GreennesOfCalgary #ClimateOfCalgary #OpenData #FOSSGIS #ClimateResilence #Landsat #Sentinel2 #Calgary #Alberta #Canada #YYC #LST #NDVI

  12. Calgary experienced a very wet and rainy summer in 2025. Naturally, the city’s vegetation responded vigorously to the high moisture levels, showing lush growth compared to the scorching summer of 2024. 🌿
    Among residential areas, tiny Roxboro showed the most significant "greening"! Meanwhile, the lowest "recovery" rates were observed in the city's newest communities.

    Read more about my research and explore the full data here:
    datastory.org.ua/how-much-gree

    #Calgary #NDVI #RemoteSensing #DataScience #Climate #YYC #OpenData #RStats #GreennessOfCalgary

  13. How did Calgary respond to the wet summer of 2025?
    Here’s the median summer NDVI map derived from Sentinel-2 imagery.
    You can clearly see the Bow River corridor, Nose Hill Park, and the contrast between established tree-rich communities and newer developments.

    Full analysis here:
    datastory.org.ua/how-much-gree

    #Geospatial #NDVI #UrbanClimate #Calgary #RStats #GreennessOfCalgary #yyc #Apberta #QGIS #foss4g #EnvironmentalMonitoring #UrbanHealth

  14. New analysis published:
    “How Much Greener Is Calgary in 2025?”

    Using Sentinel-2 data (~8.5M pixels), I calculated NDVI change (ΔNDVI) between the 2024 drought and the rainy 2025 season across all Calgary communities.

    Clear spatial pattern:
    • Strong rebound in mature tree neighborhoods
    • Limited change in developing, impervious-heavy zones

    Method: R (terra, tidyverse) + QGIS
    Community boundaries: Open Calgary

    Article + interactive table: datastory.org.ua/how-much-gree

    #RemoteSensing #NDVI #OpenData #UrbanEcology #RStats #QGIS #GreennessOfCalgary

  15. How much does landform position matter for vegetation dynamics across Calgary?

    I explored how ΔNDVI (2025-2024) varies across geomorphon classes (summit, ridge, slope, hollow, valley, etc.) using a large spatial dataset (~194k observations).

    A few key points from the analysis:
    • Non-parametric Kruskal–Wallis test shows statistically significant differences between geomorphons
    • However, the effect size is moderate (ε² ≈ 0.04)
    • Distributions strongly overlap — landform position matters, but it is not a deterministic driver
    • Median ΔNDVI tends to be higher in lower landscape positions (hollows, footslopes, valleys), consistent with moisture and accumulation controls

    #EnvironmentalData #RemoteSensing #NDVI #LandscapeEcology #Geomorphology #DataAnalysis #RStats
    #ReproducibleResearch #Calgary #GreennessOfCalgary #Sentinel2

  16. How successive #meteotsunami and storm activity disrupts #saltmarsh vegetation

    Clare Lewis, Jonathan Dale, Jessica Neumann, Tim Smyth, Hannah Cloke, October 2025

    Abstract
    "Meteotsunami (#MeteorologicalTsunami) are globally occurring progressive shallow water waves with a period of between 2 and 120 min which result from sudden pressure changes and wind stress due to moving atmospheric systems. These waves are known to cause destruction to and loss of assets. Currently, there is no research into the impact of meteotsunami on #CoastalEcosystems such as saltmarshes, despite the significant role saltmarsh play in providing vital habitats for resident and migrating birds, natural flood defences and climate mitigation. As such the restoration of saltmarshes has emerged as a pivotal focus within the UK Government's environmental policy framework.

    "This paper examines the impact of two meteotsunami events (2016 and 2021) on saltmarsh vegetation in the southwestern #UK. An assessment of the vegetation pre and post event was undertaken using high resolution satellite imagery and the Normalised Difference Vegetation Index (#NDVI). Results revealed that the 2016 meteotsunami exacted minimal vegetation change with a decrease in NDVI from 0.26 to 0.23 and a temporary reduction in coverage of 40%, suggesting a potential resilience to single episodic disturbances. In contrast, the 2021 event, compounded by multiple significant storms and additional meteotsunami, led to a decline in NDVI values from 0.44 to 0.22 and a temporary reduction in vegetation coverage of 66%.

    "Both events indicated a short-term disruption with a relatively rapid rebound (within one to three months). However, the longer-term effects of such a disruption on the saltmarsh ecosystem need to be investigated further.
    This comparative analysis underscores the complex interactions between meteotsunami, climatic phenomena, and coastal vegetation dynamics, highlighting the necessity for ongoing monitoring and research to understand the resilience mechanisms of such ecosystems in the face of increasing #ClimaticVariability and #ExtremeWeather events."

    Full paper:
    sciencedirect.com/science/arti

    #ClimateChange #AtmosphericDisturbances #AtmosphericDisturbance #CoastalAreas #RogueWave

  17. 💡 We’re excited to share that our new satellite-based NDVI monitoring feature is now in early testing at selected locations. Using Sentinel-2 imagery processed through OpenEO, the system generates up to 36 months of historical NDVI data and true-color maps, enabling vegetation health monitoring, ecosystem restoration tracking 🌍✨

    📍 Testing locations:

    agroecologymap.org/locations/t

    agroecologymap.org/locations/f

    #GIS #Agroecology #NDVI #Permaculture #OpenData

  18. 🌍✨ Something big is coming! We're working on a new feature: free and open NDVI satellite monitoring using Copernicus Sentinel-2 and OpenEO. 🛰️

    This future tool will help farmers, researchers, and communities track vegetation health, ecosystem recovery, and agroecological impact using open data, free software, and citizen science principles. 🌱📡

    Not released yet — but coming soon. 💚🌾

    #NDVI #Copernicus #OpenData #OpenScience #Agroecology #Permaculture #CitizenScience #SatelliteImagery

  19. #GreennessOfCalgary
    I’ve almost finished it!
    I’ve uploaded all eight parts of “The Greenness of Calgary: A Community-Level Atlas (2025). Contrast Color Edition” to #Gumroad

    Each part is a separate PDF using the “classic” high-contrast NDVI palette, optimized for visual interpretation of vegetation patterns. (The soft green palette will come later.)

    I’ve created a dedicated landing page with descriptions of all releases and download links.
    📎 Landing page is here: datastory.gumroad.com/l/qemrgul

    💲 The materials are available under a “pay what you want” model — free or with optional support.

    This is my first attempt at publishing geospatial analytical materials in this format. I apologise for some template-like descriptions. I hope this atlas series will be useful for researchers, enthusiasts, and anyone interested in Calgary’s urban ecology.

    #Calgary #YYC #UrbanEcology #NDVI #RemoteSensing #GIS #OpenData #Geospatial #DataVisualization #Cartography #QGIS #FOSS #Canada #Alberta #RStats #Sentinel2

  20. I like to verify my remote-sensing results directly in the field. Besides basic self-validation, field walks often generate new ideas and hypotheses.

    For mobile field GIS, I use QField, loading both final map layers and custom templates for data collection.
    Here’s an example from Nose Hill Park, where I checked several locations that showed a consistent NDVI increase in 2025 compared to 2024.
    Field observations help confirm whether the spectral trends match real vegetation changes on the ground.

    #RemoteSensing #EarthObservation #GIS #QGIS #QField #NDVI #VegetationMonitoring #Sentinel2 #FieldWork #GeoSpatial #OpenData #GeoDataScience #UrbanEcology #Calgary #NoseHillPark #Alberta #Canada #Copernicus #CopernicusSentinel #GreennessOfCalgary

  21. I like to verify my remote-sensing results directly in the field. Besides basic self-validation, field walks often generate new ideas and hypotheses.

    For mobile field GIS, I use QField, loading both final map layers and custom templates for data collection.
    Here’s an example from Nose Hill Park, where I checked several locations that showed a consistent NDVI increase in 2025 compared to 2024.
    Field observations help confirm whether the spectral trends match real vegetation changes on the ground.

    #RemoteSensing #EarthObservation #GIS #QGIS #QField #NDVI #VegetationMonitoring #Sentinel2 #FieldWork #GeoSpatial #OpenData #GeoDataScience #UrbanEcology #Calgary #NoseHillPark #Alberta #Canada #Copernicus #CopernicusSentinel #GreennessOfCalgary

  22. I like to verify my remote-sensing results directly in the field. Besides basic self-validation, field walks often generate new ideas and hypotheses.

    For mobile field GIS, I use QField, loading both final map layers and custom templates for data collection.
    Here’s an example from Nose Hill Park, where I checked several locations that showed a consistent NDVI increase in 2025 compared to 2024.
    Field observations help confirm whether the spectral trends match real vegetation changes on the ground.

    #RemoteSensing #EarthObservation #GIS #QGIS #QField #NDVI #VegetationMonitoring #Sentinel2 #FieldWork #GeoSpatial #OpenData #GeoDataScience #UrbanEcology #Calgary #NoseHillPark #Alberta #Canada #Copernicus #CopernicusSentinel #GreennessOfCalgary

  23. I like to verify my remote-sensing results directly in the field. Besides basic self-validation, field walks often generate new ideas and hypotheses.

    For mobile field GIS, I use QField, loading both final map layers and custom templates for data collection.
    Here’s an example from Nose Hill Park, where I checked several locations that showed a consistent NDVI increase in 2025 compared to 2024.
    Field observations help confirm whether the spectral trends match real vegetation changes on the ground.

    #RemoteSensing #EarthObservation #GIS #QGIS #QField #NDVI #VegetationMonitoring #Sentinel2 #FieldWork #GeoSpatial #OpenData #GeoDataScience #UrbanEcology #Calgary #NoseHillPark #Alberta #Canada #Copernicus #CopernicusSentinel #GreennessOfCalgary

  24. I like to verify my remote-sensing results directly in the field. Besides basic self-validation, field walks often generate new ideas and hypotheses.

    For mobile field GIS, I use QField, loading both final map layers and custom templates for data collection.
    Here’s an example from Nose Hill Park, where I checked several locations that showed a consistent NDVI increase in 2025 compared to 2024.
    Field observations help confirm whether the spectral trends match real vegetation changes on the ground.

    #RemoteSensing #EarthObservation #GIS #QGIS #QField #NDVI #VegetationMonitoring #Sentinel2 #FieldWork #GeoSpatial #OpenData #GeoDataScience #UrbanEcology #Calgary #NoseHillPark #Alberta #Canada #Copernicus #CopernicusSentinel #GreennessOfCalgary

  25. Comparison of the median-seasoned NDVI for central Calgary: 2024 vs 2025

    Here is a side-by-side look at how the vegetation conditions in central Calgary changed between two years, using median-seasoned NDVI maps derived from Sentinel-2 imagery.

    You can clearly see the interannual differences in greenness — especially in parks, riparian zones, and residential areas with large tree cover.
    The spatial patterns remain stable, but 2025 shows noticeably higher NDVI in many neighbourhoods due to more favourable moisture conditions.

    This is part of my ongoing project on analyzing the vegetation dynamics of Calgary communities: #GreennessOfCalgary

    #RemoteSensing #EarthObservation #NDVI #Sentinel2 #Calgary #UrbanEcology #GIS #RStats #DataAnalysis #EnvironmentalMonitoring #Copernicus #Alberta #Canada #YYC #UrbanHealth #QGIS #FOSS

  26. 🌿 Greenness of Calgary Communities (Summer 2024)
    📎 datastory.org.ua/greenness-of-

    Last year I published my first attempt to analyze the actual vegetation condition across Calgary and to build a data-driven ranking of its communities based on median summer NDVI. It was my very first experiment in assessing urban greenness at the neighbourhood scale — but the results turned out surprisingly insightful.
    Some patterns were expected, while others revealed unexpectedly low vegetation density in places that looked green from the ground.

    This exploration later grew into a much larger line of research on Calgary’s greenness, climate resilience, and spatial variability in vegetation health. You can find some results here with thematic hashtag #GreennessOfCalgary

    If you're working on urban ecology, remote sensing, or land-cover analysis of Canadian cities — I’d be happy to exchange ideas.

    #NDVI #RemoteSensing #Calgary #UrbanEcology #Sentinel2 #QGIS #RStats #Alberta #Canada #EnvironmentalMonitoring #GeospatialAnalysis

  27. Continuing my exploration of #GreennessOfCalgary

    I’m working with two large geospatial datasets for the city:
    • median summer NDVI for 2024 and 2025 (Sentinel-2)
    • MRDEM-2024 digital elevation model

    From the NDVI maps I calculated ΔNDVI, and from MRDEM I derived aspect, slope, and TPI, all resampled into the ΔNDVI raster grid.

    I then asked a simple question:
    👉 Does terrain aspect influence ΔNDVI between 2024 and 2025?

    To check this, I:
    – converted aspect values into 8 cardinal directions
    – excluded flat areas (slope ≤ 2°)
    – randomly sampled ~60,000 rows from the original 8.5-million-row dataset

    The result:
    Although the Kruskal–Wallis test detects statistically significant differences (inevitable with such a large sample size), the distributions show that aspect has almost no meaningful influence on ΔNDVI.

    In other words, the observed increase in greenness in some parts of Calgary is likely driven by other environmental or anthropogenic factors, not by terrain orientation.

    #NDVI #Calgary #RemoteSensing

  28. Here is the city-wide map of ΔNDVI for Calgary — the difference between the median summer NDVI (mid-May to mid-September) in 2024 vs 2025.

    As in the previous post, the signal is quite clear:
    2025 shows a systematic increase in vegetation index across almost the entire city, but some areas showing a decrease.

    This pattern is consistent with what I see in the frequency distributions of median NDVI:
    2025 has a broader, greener distribution — likely reflecting better moisture conditions and a more favourable growing season.

    Working with ΔNDVI on a pixel-by-pixel scale (10 × 10 m) offers a much more detailed picture of how vegetation responds spatially, compared with community-level averages or city-wide summaries.

    #NDVI #Sentinel2 #RemoteSensing #Calgary #GreennessOfCalgary #GIS #Rstats #DataAnalysis #ESA #UrbanEcology #Copernicus #CopernicusSentinel #SustainableDevelopment #SustainableUrbanDevelopment #Alberta #Canada #EnvironmentalMonitoring #GIS #Geospatial

  29. 🌿 A noticeable shift in the statistical distribution of median NDVI values for Calgary between 2024 and 2025.

    🛰️ Both histograms are based on Sentinel-2 data with 10×10 m resolution, and each NDVI value represents the median for mid-May to mid-September.

    The contrast is striking:

    🔥 2024 shows a distribution shifted toward lower NDVI values → drier summer, weaker vegetation growth, more heat-stress periods.
    🏡 2025 is clearly shifted to the right → stronger greenness, more moisture, and more stable summer conditions.

    This kind of interannual comparison reveals how much the city’s ecosystems can vary from year to year — using nothing more than open satellite data and clean statistics.

    #NDVI #Sentinel2 #RemoteSensing #Calgary #GreennessOfCalgary #GIS #Rstats #DataAnalysis #ESA #UrbanEcology #Copernicus #CopernicusSentinel #SustainableDevelopment #SustainableUrbanDevelopment #Alberta #Canada

  30. 🌿 NDVI change in Calgary’s Weaselhead Flats (2024 → 2025)

    This map shows how vegetation in one of Calgary’s most diverse natural areas responded to the city’s unusually wet summer of 2025.
    Greener shades mark zones where NDVI increased most strongly compared to 2024 — the same floodplain and forest patches that locals know for dense canopy recovery.

    Even modest year-to-year shifts in temperature and rainfall leave clear spatial traces in NDVI — a reminder of how sensitive urban ecosystems are to climate variability, and how well open-data satellite products can capture it.

    🛰 Data and processing: Sentinel-2 + R + QGIS

    #NDVI #RemoteSensing #Calgary #UrbanEcology #ClimateImpact #EnvironmentalMonitoring #GIS #QGIS #RStats #DataVisualization #GeospatialAnalysis #Sentinel2 #CopernicusSentinel2 #CopernicusProgram #Copernicus #GreennessOfCalgary #Alberta #Canada

  31. 🌿 Calgary’s vegetation — satellite comparison (2024 → 2025)

    Median NDVI maps from mid-May to mid-September show a clear difference between the two seasons.

    In 2025, NDVI values are noticeably higher — vegetation stayed greener and denser for longer.
    The wetter summer had a strong effect on canopy productivity across most Calgary communities, especially in parkland and tree-covered zones.

    🛰️ Based on Sentinel-2 imagery and R + QGIS processing.

    #RemoteSensing #NDVI #UrbanEcology #Calgary #GeospatialAnalysis #GIS #Sentinel2 #EnvironmentalData #DataVisualization #OpenScience #EarthObservation #ClimateImpact #RStats #QGIS

  32. 🌿 Calgary Greenness Dynamics (2024–2025)

    Mapping ΔNDVI between the summers of 2024 and 2025 shows how Calgary’s communities changed in their vegetation cover.

    🟢 Some areas became noticeably greener this year — likely due to the wetter and milder summer.
    🔴 Others show slight declines, possibly linked to construction, soil dryness, or limited tree canopy recovery.

    These patterns reveal how different parts of the city respond to seasonal variability — and where future urban greening might have the most impact.

    🛰️ Based on Sentinel-2 data and NDVI analysis in R.

    #Calgary #NDVI #RemoteSensing #UrbanEcology #DataVisualization #GreennessOfCalgary #EnvironmentalData #GIS #RStats #GeospatialAnalysis #yyc #Alberta #Canada

  33. 🌿 Where Calgary Got Greener — and Where It Didn’t?

    A quick look at how Calgary’s residential communities changed in greenness (NDVI) between 2024 and 2025.

    🟢 Some neighbourhoods show a clear recovery of vegetation — probably thanks to a wetter, milder summer, better soil moisture, or local greening efforts.
    🔴 Others stayed stagnant or even lost NDVI — maybe new construction, dry soils, or sparse vegetation played a role.

    The bar chart shows Top-5 and Bottom-5 communities by NDVI change. It’s fascinating how uneven the “greening pulse” can be within one city.

    📊 Based on Sentinel-2 data, mid-May – mid-September, processed in R.

    #Calgary #NDVI #RemoteSensing #UrbanEcology #EnvironmentalData #GIS #Sentinel2 #ClimateImpact #GeospatialAnalysis #DataScience #RStats #OpenData #GreennessOfCalgary #Alberta #Canada

  34. 🌳 The Greenness of Calgary — Community-Level Atlas Project

    Over the past year, I’ve been working on a long-term project that maps and analyzes vegetation greenness across all Calgary communities using Sentinel-2 satellite data (10 m resolution).

    Each atlas page shows detailed NDVI-based land-cover statistics and community-level summaries.
    The results highlight both environmental gradients and the impact of local watering restrictions, weather patterns, and land-use intensity.

    Two visual editions are available:
    🌿 Green Edition – calm, analytical colors for research and reports:
    🔗 datastory.gumroad.com/l/meqquj
    🎨 Contrast Edition – high-contrast design for presentations and outreach:
    🔗 datastory.gumroad.com/l/kqfmvnc

    All maps and data were produced with R + QGIS + open satellite sources.

    #RemoteSensing #GIS #NDVI #UrbanEcology #Calgary #DataVisualization #OpenSourceGIS #Cartography #yyc #GreennessOfCalgary #Alberta #Canada

  35. New guide: Zonal Statistics in Python with Earth Engine and Colab

    Inside:
    • Template for processing multiple rasters at once
    • Unified reducer (mean/median/std/min/max in one pass)
    • Convert to GeoDataFrame
    • Export to GPKG/CSV + upload to Google Drive
    • Visual maps (relief, NDVI, soil temperature)

    🎁 Bonus: ready-to-use Colab notebook at the end.

    Read more: medium.com/@anton.biatov/zonal

    #Geospatial #GIS #EarthEngine #Python #Geemap #ZonalStatistics #NDVI #DataScience