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connorcrowe/README.md

🌎 Data Background, Product Focus, Geospatial Passion

Hi, I'm Connor--- a data-driven product manager with a background in computer engineering & data science and a passion for geospatial problems. I've built products in deep tech, health-tech and education-tech.

I am on a journey in the geospatial industry to leverage my skills towards the problems that I'm most personally passionate about - climate change, urban developmnet, & transportation.

Featured Projects

🚧 Current Project: A Product Managed Approach to Bicycle Network Prioritization

Using geospatial analysis to help prioritize bike lanes, but documenting the entire product development lifecycle from problem definition to launch measurement. Come follow along with how a PM gets things done.

🔗 GitHub Repo

🗺️ High-Resolution Automated LULC Classification at Scale in Toronto

Using trained LULC U-net classifier to autoamtically predict land use land cover of the entire City of Toronto aerial at 2 px per meter. Technologies: gdal, leaflet, Vite, Tensorflow/Keras, Python

🗺️ Live Demo | 🔗 GitHub Repo

🛩️ Land Use Land Cover Neural Network Classification from Aerial Data

Trained a Convolutional Neural Network (CNN) with U-net architecture on aerial imagery to classify land use in downtown Toronto. Technologies: CNN, U-net, Tensorflow/Keras, Map Digitization

🔗 GitHub Repo

🌆 Urban Heat Island & Vulnerability Analysis of Toronto from Satellite Imagery

Mapped urban heat islands in Toronto using remote imagery and overlaid demographic data to highlight vulnerable communities. Technologies: QGIS, GDAL, Raster Analysis, Remote Sensing, Landsat

🗺️ Full Story on StoryMaps! | 🔗 GitHub Repo

🚲 Geospatial Analysis of Toronto Bike Share Data

Analyzed Toronto's bike share data (2016-2024) using spatial SQL and geospatial visualization to assess impact of changes in infrastructure. Technologies: PostGIS, QGIS, Python, PyQGIS

🗺️ Full Story on StoryMaps! | 🔗 GitHub Repo

Skills, Tools, Learning

  • Product Management
    • Prioritization, organisation, storytelling & communication
    • Agile, Jira, Git, etc.
  • Data & Programming
    • Python, Data, Machine Learning (Pandas, Geopandas, PyQGIS, Tensorflow/Keras, scikit-learn)
    • SQL (MySQL, PostGIS, BigQuery)
  • Courses
    • Fundamentals of Remote Sensing and Geospatial Analysis, Udemy, Matt Thompson
    • Machine Learning in GIS: Theory and Practice, Udemy, Kate Alison

Let's Connect

I'm always open to discussions about geospatial data, urban analytics, and climate tech.
💼 LinkedIn

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  1. to-bike-network-prioritization to-bike-network-prioritization Public

    A full product lifecycle solving network-wide bike lane prioritization access for city planners. Documented how a Product Manager would solve this - from problem definition to launch management.

  2. to-lulc-scale to-lulc-scale Public

    This project uses a U-Net CNN to classify land use for the entire City ot Toronto at high-resolution in an automated pipeline.

    Jupyter Notebook 8

  3. to-lulc-aiml to-lulc-aiml Public

    Land use land cover (lulc) classification of aerial imagery using machine learning techniques including U-Net architecture Convolutional Neural Networks (CNNs).

    Jupyter Notebook 1 1

  4. to-urban-heat-island to-urban-heat-island Public

    Geospatial analysis of remote imagery to identify where the urban heat island effect is worst in Toronto, Canada, and which areas have the population most vulnerable to them.

    1

  5. to-bike-analysis to-bike-analysis Public

    Statistical and geospatial analysis of Toronto Bike Share data and what it can tell us about the impact of changes to Toronto's bicycle infrastructure

    Jupyter Notebook 1

  6. dcp-sort dcp-sort Public

    A sorting algorithm designed for improved time complexity on a massively parallel system

    JavaScript 1