Applied Environmental & Sustainability Science | Digital Mapping | GIS Analysis
My name is Mark Marji. I earned a Master's degree in Applied Environmental and Sustainability Science from the University of Kentucky and completed a graduate certificate in Digital Mapping.
Experience with QGIS, coordinate systems, projections, cartography, and spatial analysis.
ArcGIS Pro, ArcGIS Online, spatial modeling, visualization, and data-driven mapping.
JavaScript, GitHub Pages, Mapbox, Leaflet, HTML, CSS, and interactive GIS applications.
Volcano lava flow hazard mapping with road impact analysis.
Museums and cultural sites in Washington DC with spatial context.
Monochrome basemap of Kenya created using Mapbox styles.
Museums in NYC with subway routing context.
Interactive map using JavaScript arrays, loops, and popups.
Solar energy production mapping in Oahu, Hawaii.
SVG-based attraction mapping of the Outer Banks region.
Python + Jupyter Notebook workflow for spatial energy analysis.
Deploying coordinate-based geospatial mapping models to plot foundational informant interview points within the LAMSAS project framework.
An attribute-enhanced mapping interface integrating spatial demographic distributions alongside complex professional and occupational data engines.
Developing interactive checkbox query matrices to filter dense linguistic atlas datasets dynamically based on user-selected geographic parameters.
Visualizing geographic variation boundaries and spatial densities across discrete regional terminology datasets.
Utilizing clean vector layers and thematic classification styles to generate crisp choropleth maps detailing changing regional weather variations.
This cartographic interface implements a series of choropleth models to isolate and analyze regional linguistic datasets regarding domestic spaces.
An interactive, checkbox-driven spatial filtering application designed to plot, isolate, and cross-reference geographic linguistic variations for diverse regional terminology datasets.
A series of thematic web maps utilizing custom data classification models to analyze and compare the localized geographic densities of domestic spatial terms.
A multi-layered thematic mapping dashboard leveraging detailed choropleth classifications to visualize the density, geographic distribution, and regional variation of structural domestic design elements.