Michael Markieta

Michael Markieta

Self-Employed GIS Consultant

Location
Toronto, Canada Area
Industry
Higher Education

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Michael Markieta's Overview

Current
  • GIS Consultant at Michael Markieta (Sole Proprietorship)
Past
  • Transportation Planner (Intern) at Arup
  • Research Assistant, Department of Geography at Ryerson University
  • GIS Analyst at Wildland Research Institute
Education
Connections

260 connections

Websites

Michael Markieta's Summary

Michael is a Geographic Information Systems (GIS) specialist who builds geospatial solutions of the future. He is a wise coder, an artist and life long learner who creates web mapping solutions that are in lockstep with todays bleeding edge technologies. In 2012, Michael started consulting on regional transportation planning projects, where he applied his GIS skills to solve complex growth modeling problems. Shortly thereafter, Michael started his own business as an independent consultant so that he could craft the future of spatial problem solving with beautiful and functional web maps. As a creative thinker and passionate developer, Michael embraces the union of art and code. Specializing in GIS enables Michael to manage and visualize complex spatial data sets.

Michael Markieta's Experience

GIS Consultant

Michael Markieta (Sole Proprietorship)

September 2012Present (2 years 1 month) Toronto, Canada Area

Transportation Planner (Intern)

Arup

Privately Held; 10,001+ employees; Design industry

May 2012August 2012 (4 months) Toronto, Canada

Research Assistant, Department of Geography

Ryerson University

Educational Institution; 1001-5000 employees; Higher Education industry

July 2011May 2012 (11 months) Toronto, Ontario

GIS Analyst

Wildland Research Institute

May 2011July 2011 (3 months) University of Leeds, Leeds, United Kingdom

Michael Markieta's Projects

  • Markham Centre Mobility Hub, City of Markham @ Arup

    • July 2014 to Present
    Team Members: Michael Markieta

    Michael plays a supporting role as a subconsonsultant for Arup by georectifying satellite imagery, sketches and CAD data from disparate data sources. The amalgamation of these datasets allows maps to be produced that provide a clear picture of the planning scenario for the City of Markham. Michael's specialization in GIS allows him to construct a system that acts as a central repository for the disparate data sources, as well as allowing for new digitized spatial data to be added. His thematic and asset management maps were used in a four-day design workshop, where consultants and city planners drew conceptual design for Markham Mobility Hub that could co-exist and compliment existing and planned transit, transportation, amenities, and pedestrian and cycling networks.

  • Confidential Campus Major Capacity Expansion, Confidential @ Arup

    • June 2014 to August 2014
    Team Members: Michael Markieta

    Michael played a supporting role as a subconsonsultant for Arup by developing a drive time catchment analysis for multiple proposed university campus locations. Using Python, Michael programmed a tool that retrieved drive time data from the Inrix Driving Intelligence API. The data was transformed to GeoJSON for use in ArcMap to create elegant maps that display catchment areas for various proposed campus locations. Michael also extracted demographic statistics for each catchment area to support narratives for the various proposed campus locations.

  • Regional Structure Action Strategy, Wood Buffalo @ Arup

    • May 2013 to August 2013
    Team Members: Michael Markieta

    Michael played a supporting role as a subconsonsultant for Arup by providing a clear picture of the land and infrastructure needed to support growth in Wood Buffalo, Alberta. Michael conducted GIS-based land suitability analyses for urban development. In addition, he created a GIS transportation network for modeling accessibility, travel time and vehicle routing in the region. Michael’s work enabled transport planners to better understand the current environment and network connectivity, allowing them to identify areas with potential for future growth with minimal constraints.

  • The Big Move, Metrolinx @ Arup

    • September 2012 to May 2013
    Team Members: Michael Markieta

    Michael played a supporting role as a subconsonsultant for Arup for the The Big Move, a $50 billion Metrolinx project. Utilizing GIS-based analysis of transportation infrastructure, his research aids the client in understanding the evolving breadth and socio-demographic compo- sition of transit catchment areas and rapid transit infrastructure in the Greater Toronto and Hamilton Area over a 25 year period. Michael also produced cartographic representation of transit catchment areas and transit routes, depicting their growth between 1986 and 2011.

  • Buttonville Airport Redevelopment, Cadillac Fairview @ Arup

    • August 2012 to November 2012
    Team Members: Michael Markieta

    Michael played a supporting role as a subconsonsultant for Arup and composed cartographic representations of transit infrastructure oppor- tunities in Buttonville for intensive redevelopment of the current airport lands slated for an urban typology. These maps enabled other consul- tants to compose transit scenario models and simulations, which would be proposed to the client.

  • Global Flights @ Arup

    • March 2013 to Present
    Team Members: Michael Markieta

    Michael designed and published what would become the most read story of the day on the BBC, followed by an in-depth feature in BBC Magazine and broadcast coverage on BBC World News and BBC Global News Bulletin. Recognizing its impact, Arup hosted the visualization on its home page. The Toronto Star and international outlets including Daily Mail, North Korea Times, Fox News and Metro International also picked up the story, not to mention numerous online and print publica- tions across the aerospace, design and branding industries. The story went viral with 35000 shares on the BBC story, 3000 ‘likes’ on its Facebook post and more than 5500 Twitter mentions in the first three days.

  • Integrated Mode Share Estimation Platform @ Arup

    • May 2012 to December 2012
    Team Members: Michael Markieta

    Michael was the lead developer of the Integrated Mode Share Estimation Platform (IMSEP), a tool that would provide a niche consulting service for Arup in the area of mobility hub development. IMSEP is an ArcGIS plug-in developed using Python. The tool is based on leading multiple regression research which identifies measurable attributes of an area that contribute to transit ridership. IMSEP reads spatial data from the GIS and calculates estimated transit station ridership. The tool was designed to be used to explore many development scenarios quickly, the results of which could be used to generate system demands, revenue estimates and mode splits.

  • Neptis Geoweb @ Neptis Foundation

    • January 2013 to Present
    Team Members: Michael Markieta

    Michael developed the interactive web map used by the Neptis Foundation to demonstrate and communicate regional planning issues. Development included the implementation of query functionality such that map popups were populated with data retrieved from a spatial database. Performance of the map ecosystem was improved by moving from MapServer to a tile cache based system. The web map stack includes: OpenLayers, TileStache, PostGIS and Apache server, and Michael manages the Ubuntu server that is it hosted on.

  • The Big Move, Metrolinx @ Arup

    • May 2012 to August 2012
    Team Members: Michael Markieta

    Michael was tasked during his internship to provide GIS support as a member of an interdisciplinary transportation consulting team. He contributed to a Progress Report for the $50bn Metrolinx Regional Transportation Plan, The Big Move. Priority tasks included producing GIS-based demographic summary reports that described the historical growth of the Greater Toronto and Hamilton Area.

  • Skills Development @ Arup

    • May 2012 to August 2012
    Team Members: Michael Markieta

    · Developing a valuable tool for planners interested in quickly estimating transit mode share.
    · Programming aforementioned tool to extract, validate and re-purpose geospatial data.
    · Aforesaid tool's value: test more scenarios faster; higher margin on lump sum projects.
    · Building aforementioned tool in Eclipse with PyDev, as a Python Add-In for ArcGIS 10.1.
    · Utilizing a Mercurial distributed revision control system for ArcGIS Add-In development.
    · Designing extensible ArcGIS File Geodatabase schema for growth beyond case studies.
    · Geoprocessing OpenStreetMap and GTFS data into topologically correct geospatial layers.
    · Exceptional working knowledge of the Transportation Tomorrow Survey for GIS analyses.

  • Census-Driven Maps

    • January 2012 to April 2012
    Team Members: Michael Markieta

    This web map­ping appli­ca­tion was cre­ated by Michael Marki­eta and pre­sented to Ryer­son Uni­ver­sity in par­tial ful­fill­ment for the require­ments of Pro­fes­sional Geo­g­ra­pher (GEO871), a cap­stone course of the Geo­graphic Analy­sis pro­gram. It is an inter­ac­tive web-based map­ping tool that pro­vides users with access to a geo­vi­sual rep­re­sen­ta­tion of the Cana­dian 2011 Cen­sus of the Population.

  • Map Overlay and Opacity Tool 2.0 (moot2) @ Ryerson University

    • September 2011 to May 2012
    Team Members: Michael Markieta

    A visual multi-criteria analysis tool, developed using OpenLayers and jQuery.

  • Using Web Map Overlay for Visual Multi-Criteria Analysis: The Example of the Ontario Human Influence Index @ Ryerson University

    • September 2011 to May 2012
    Team Members: Michael Markieta

    Michael explored web-based visual multiple criteria decision analysis through the development of a web mapping application. This poster was presented at the 14th Annual Global Geospatial Conference 2012. In addition, this poster earned Michael the GEOIDE Student Network Best Poster award. In this poster, Michael introduce the Map Overlay and Opacity Tool, version 2 (“moot2”), a Web-based MCDA tool that combines elements of visual and computational overlay. Research position funded by Ontario Work Study Program and GEOIDE Project PIV-41.

  • Wind Farm Site Location-Allocation @ Wildland Research Institute

    • May 2011 to July 2011
    Team Members: Michael Markieta

    · Assessed visual impact of wind farms in Scotland using novel rapid view­shed tools.
    · Re-engineered viewshed analysis to capture locations of low-impact development areas.
    · Devel­oped guid­ance for policy-making in regards to wind farm development.
    · Col­lab­o­rated with stake­holders, including John Muir Trust and the Scottish Government.
    · Presented research at the 20th Annual GISRUK Conference; published in proceedings.
    · Research position funded by Ryerson International Work Experience Fund and WRi.

Michael Markieta's Education

Ryerson University

Master of Spatial Analysis, Geography

20132014

One year intensive program.
Four month work placement.
Major research paper.

Ryerson University

Bachelor of Arts, Geographic Analysis

20082013

Activities and Societies: GIScience Research Group Member - Directed by Dr. Claus Rinner, Student Researcher - GEOIDE PIV-41 (Participatory Geoweb for Engaging the Public on Global Environmental Change)

Michael Markieta's Publications

  • Using distributed map overlay and layer opacity for visual multi-criteria analysis

    • Geomatica, 68(2), pp. 253-257.
    • June 2014
    Authors: Michael Markieta

    Strategic decision-making is often based on multiple decision criteria and on the decision-makers’ preferences regarding relative criterion importance. We present version 2 of a map overlay and opacity tool (moot2), which supports the visual exploration of decision-making scenarios. The tool uses a basic function of geographic infor- mation systems (GIS): visual map overlay. In this approach, visual overlay serves as a representation of weighted linear combination in multi-criteria decision analysis (MCDA). Using the tool, we model a global human influence index for the extent of the province of Ontario, Canada. The index is a weighted overlay of six indicators that rep- resent human influence on the land. The semi-transparent overlay of the six indicator layers occurs online in a web browser, making it accessible to distant collaborators in low-technology settings. The software architecture of moot2 includes the OpenLayers JavaScript library to display thematic Web Map Service (WMS) layers, such as the human influence indicators, on top of popular base map services, such as OpenStreetMap or Google Maps. The tool also uses jQuery, a JavaScript library that enables interactions between the user and the map environment. Layer opacity is manipulated by the jQuery Slider, permitting the user to generate on-the-fly weighting schemes for the combination of the human influence indicators. By removing the analytical engine (i.e., GIS), decision-makers can perform rapid MCDA without recalculating composite evaluation scores. The case study demonstrates how visual-spatial MCDA supports the refinement of decision-making parameters such as criterion weights.

  • Integrated Mode Share Estimation Platform (IMSEP): Using ArcGIS and Multiple Regression to Predict Transit Ridership

    • Proceedings of the 2013 Esri International User Conference.
    • July 8, 2013
    Authors: Michael Markieta

    The Integrated Mode Share Estimation Platform (IMSEP) assumes the role as an embedded tool in the planning workflow for expedited transportation ridership prediction and mode share analysis. The tool was created as an extension for ArcGIS 10.1 using Python Add-Ins. We take advantage of core GIS functions in our analysis and utilize geospatial databases for data storage; while the central analytical engine was built based on leading research on connections between observed travel behavior, land use and urban design. The tool takes into account the direct and derivative attribute or indicator values for any given catchment area around a transportation hub. Through parameter and model adjustments, the IMSEP allows for the modifications to underlying attribute and indicator values, which subsequently produce alternative transit ridership and mode share estimations. The audience will learn about transportation, neighbourhood design attribute indicators and the use of Python to create add-ins for ArcGIS.

  • A Map Overlay and Opacity Tool for Visual Multi-Criteria Analysis

    • Proceedings of the Joint 2013 Canadian Institute of Geomatics Annual Conference and the 2013 International Conference on Earth Observation for Global Changes
    • June 5, 2013

    Strategic decision-making is often based on multiple decision criteria and on the decision-makers’ preferences regarding relative criterion importances. We present version 2 of a map overlay and opacity tool (moot2), which supports the visual exploration of decision-making scenarios. moot2 relies on a basic function of geographic information systems (GIS): visual map overlay. In this context, visual overlay serves as a representation of weighted linear combination in multi-criteria decision analysis (MCDA). Using the tool, we model a global human influence index for the extent of the Province of Ontario, Canada. The index is a weighted overlay of six indicators that represent human influence on the land. The semi-transparent overlay of the six indicator layers occurs online in a Web browser, making it accessible to distant collaborators in low-technology settings. The development of moot2 utilizes the OpenLayers JavaScript library to display thematic Web Map Service (WMS) layers such as the human influence indicators on top of a popular base map service, such as OpenStreetMap or Google Maps. The tool also uses jQuery, a JavaScript library that enables interactions between user and map environment. The layer opacity is manipulated by the jQuery Slider, permitting the user to generate on-the-fly weighting schemes for the combination of the human influence indicators. By removing the analytical engine (i.e., GIS), decision-makers can perform rapid MCDA without recalculating composite evaluation scores. The case study demonstrates how visual-spatial MCDA supports the refinement of decision-making parameters such as criterion weights.

  • Using OpenStreetMap Data with Open-Source GIS

    • Cartographic Perspectives, 71(1), pp. 91-104.
    • October 2012
    Authors: Michael Markieta

    For many, free and open-source data and software represents accessibility to otherwise inaccessible geospatial workflows in terms of cost and availability. Commercial data used in geographic information systems (GIS) is available through a relatively small number of merchants or vendors, which produce highly accurate, precise, and detailed information. This is produced, however, at a cost that many small and large businesses, private consultants, and startups cannot afford. Open-source data, such as the volunteer geographic information on OpenStreetMap (OSM), represents a community effort to build one of the best web maps, and subsequently the best GIS database, available for free to the public. OpenStreetMap is a web-based map to which any registered user can submit data. These updates, over time, populate the now extensive web map that is the OpenStreetMap. At the same time, the data that lives on the OpenStreetMap can be downloaded and used inside of a GIS for geospatial analysis, cartographic rendering, and other geo-related tasks.

    ISSN: 10489085

  • No High Ground: visu­al­is­ing Scotland’s renew­able energy land­scapes using rapid view­shed assess­ment tools

    • Pro­ceed­ings of the GIS Research UK 20th Annual Con­fer­ence (pp 115–123). Lan­caster, UK: The Uni­ver­sity of Lan­caster.
    • April 13, 2012

    Rapid viewshed modelling techniques are used to address the conflicts between landscape protection and renewable energy goals in Scotland. The area of the country currently without a view of a wind turbine is calculated and used to identify areas that could be developed as wind farms without further impacting on the non-visible areas. The analysis is repeated for protected landscapes and core wild land areas and lowest impact zones identified. The method used relies on the use of voxel-based real-time viewshed modelling techniques to make these analyses practical.

    ISBN: 9781862202948

Michael Markieta's Honors and Awards

  • ESRI Canada GIS Scholarship

    ESRI Canada
    • February 2012

    Michael was selected to receive a comprehensive package of a fully executed lifetime ArcGIS Advanced license, workbooks and access to ESRI training courses and conferences for his exceptional applied research with ESRI software at Ryerson University.

  • Best Student Poster - Global Geospatial Conference 2012

    GEOIDE Student Network
    • May 2012

    Michael was awarded the 2012 GSN Best Student Poster award at the 14 Annual Global Geospatial Conference. The GEOIDE Student Network (GSN) awards prizes to students who display the most original, best-explained and most visually appealing posters. The objective is to reward the creativity and communication skills of students as they present their posters.

  • Award of Merit for Out­stand­ing Progress in the Pro­gram

    Department of Geography, Ryerson University
    • October 2011

    Michael earned this award for demonstrating the most outstanding progress among his peers in the Geographic Analysis Program at Ryerson University.

  • Gold Medal - GIS Com­pe­ti­tion

    Skills Canada - Ontario Technological Skills Competition
    • May 2006

    Michael was part of a team of two that were awarded the gold medal in the Geographic Information Systems competition as part of the Ontario Technological Skills Competition. Secondary school student participate in this competition which aims to evaluate each team's preparation for employment in the field of Geographic Information Systems and to recognize outstanding students for excellence and professionalism in their field.

Michael Markieta's Organizations

  • NACIS - North American Cartographic Information Society

    Member
    • October 2012 to Present

    An organization of specialists in the field of geographic information. Founded in 1980, NACIS has grown into a vibrant society with membership throughout North America and the world. NACIS welcomes new members from the traditional as well as emerging professions that define geographic information science today.

Michael Markieta's Skills & Expertise

  1. ArcGIS
  2. GIS
  3. Web Mapping
  4. Spatial Databases
  5. Python
  6. Programming
  7. Quantum GIS
  8. HTML 5
  9. ArcGIS Extensions
  10. MapInfo Professional
  11. Geodatabase Design
  12. OpenLayers
  13. Leaflet
  14. Statistical Modeling
  15. SPSS
  16. Oracle Spatial
  17. Access
  18. Eclipse
  19. PyDev
  20. IDLE
  21. JavaScript
  22. CSS3
  23. XML
  24. Distributed Revision Control System
  25. Tortoise HG
  26. Transportation Planning
  27. Cartography
  28. Statistics
  29. Geodatabase

View All (29) Skills View Fewer Skills

Michael Markieta's Additional Information

Websites:
Interests:

GIS, web mapping, programming, multivariate statistics, transportation planning, spatial databases, web development, writing, reading and cycling.

Groups and Associations:

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