Today was a masterclass on the difference between models, inference from spaceborne imagers, and field observations.
Today was a masterclass on the difference between models, inference from spaceborne imagers, and field observations.
I wrote a detailed post on LinkedIn about the technical data analysis pipeline I use at my solar energy startup. And I took ChatGPT's advice about a provocative headline at the beginning of the post. Now I think that was a mistake. Because, judging by the statistics, my readers are mostly engineers, not marketers.
#SolarStartup #solarenergy #Geospatial #TechStartup #RemoteSensing #EarthObservation #DataScience #ClimateTech #BuildInPublic
โ Why "Copy-Paste" Fails in Science: Calibrating the Model for Calgary
๐ฐ๏ธ Iโve recently updated the land cover data for Calgary using my Proprietary MDEM Framework (Multi-dimensional Environmental Matrix).
Hereโs an interesting technical challenge: the methodology that worked flawlessly on data from Kryvyi Rih, Ukraine, required significant recalibration for Alberta. Spectral signatures of Canadian spruce and local soil compositions are worlds apart from Eastern European environments.
๐ป I am currently refining the local training set to ensure precise differentiation between vegetation types. This level of accuracy is vital for effective urban monitoring and improving the quality of life in our communities.
๐ฒ The preliminary classification results already offer a fresh, data-driven perspective on the cityโs structure. The work continues!
#DataScience #Geospatial #CalgaryClimate #EnvironmentalAudit #APEGA #RemoteSensing #Calgary #GreennesOfCalgary #YYC
Giving back to Calgary: an article was published today about my satellite research of the city!
It is important to me to use my knowledge as a geoscientist and environmental data scientist to help make our new home better and greener. Thanks to LiveWire Calgary for the interest in this topic!
https://livewirecalgary.com/2026/03/17/new-satellite-study-shows-calgarys-uneven-urban-greenery/
#DataScience #EnvironmentalScience #RemoteSensing #Calgary #PublicEngagement #GIS #Sustainability #RStats #MDEM #yycPlanning #UrbanPlanning #ClimateResilience #NatureBasedSolutions #UrbanEcology #GreenInfrastructure #SmartCities #CalgaryUrbanism #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
ps
I did do one piece of work for free. A real brainworm going back to PhD times and using localised variance in elevation models to classify deformed ice / smooth ice.
...so I just got it done since I have the [openly licensed] data lying around:
Identifying deformed ice features / ridge segmentation using something other than elevation (which has many limitations). It's a novel approach in sea ice research:
https://www.spatialised.net/identifying-deformed-sea-ice-using-geomorphons/
...the 2008 IDL version was trashed, and we invested in commercial software (eCognition) for the 2012 iteration. A different approach entirely - mosaick up images, split the mosaic by blocks, analyse blocks, merge results.
Also in 2012, there were some folks aboard SIPEX-II with a fancy radiometer - so I asked if they could very kindly measure the reflectance in RGB bands over open water, and deep ridge shadows. I'd had a hunch that there's a tiny difference...
3/5