Project Summary: Offshore Wind Farm Design & Analysis

Domain: Renewable Energy Skill: Modelling / Research

Over a three-week period, I utilized the Youwind platform to design and analyze offshore wind farm layouts off the coast of Nova Scotia. Leveraging my GIS background, I transitioned from using predefined areas to creating custom polygon boundaries for layout optimization.

Key Technical Workflows:

• Layout Optimization: Generated turbine layouts using wake-optimized positioning and maximum spacing configurations.
• Spatial Analysis: Utilized the split function to divide areas of interest into equal sections, analyzing the correlation between turbine density and wake losses.
• Electrical Design: Engineered a mock transmission system by siting onshore and offshore substations and routing array cables using intuitive generation tools.
• Performance Metrics: Focused on the Turbine Layout, Wakes, and Electrical Transmissions modules to interpret how specific coordinates and exclusion zones impact energy yield.

Outcomes & Future Objectives: Through technical support and one-on-one tutorials, I became familiar with the platform’s core workflows to achieve tangible design outcomes. Moving forward, I aim to integrate financial modelling to compare the CAPEX of different sites, specifically analyzing the trade-offs between cabling costs, wake efficiency, and exclusion zone restrictions.

Project Summary: Multispectral Satellite Enhancement

Domain: Hazard / Land Analysis Skill: Remote Sensing / Research

This presentation poster was developed to demonstrate advanced image enhancement techniques applied to remotely sensed imagery. The project focuses on the Mauna Loa volcanic eruption in Hawaii, captured on November 27th, 2022.

Key Technical Objectives:

• Visual Optimization: Applied various contrast stretching and filtering techniques to make volcanic plumes and thermal activity more distinct from the surrounding terrain.
• Feature Extraction: Enhanced spectral signatures to allow for easier identification of active lava flows and ash dispersion.
• Research Readiness: Prepared high-fidelity imagery suitable for further geospatial research and temporal analysis.

Note: Please click on the poster image above to enter Zoom Mode. This will allow you to read the fine technical details, methodology, and results documented in the draft.

Project Summary: Places of the World (Python for QGIS)

Domain: Population Tracking Skill: GIS

Places of the World is a custom PyQGIS tool designed to automate spatial demographic analysis. The program allows users to interactively select global locations within QGIS and generate a structured geospatial report based on Esri shapefile attributes.

Key Technical Features:

• Spatial Data Integration: Developed a workflow to ingest point features and overlay them with OpenStreetMap (OSM) basemaps via the QuickMapServices plugin.
• Interactive Selection: Built the script to recognize user-defined spatial selections (Polygon Tool). It features a "Default Selection" logic that processes the entire global dataset if no specific area is isolated.
• Quadrant Analysis Logic: Programmed a spatial categorization engine that sorts points into the four global hemispheres (NE, NW, SE, SW) based on coordinate geometry.
• Dynamic Reporting: Automated the generation of .txt reports that calculate:
  • Total location counts and aggregate populations per hemisphere.
  • Statistical extremes (identifying the highest and lowest population centers).
  • Complex edge-case handling for population ties, listing all relevant place names.
• User Input Handling: Implemented a prompt-based system for custom directory and file naming, including automated file path string formatting.

Technical Takeaways: This project demonstrates proficiency in PyQGIS scripting, spatial attribute manipulation, and automated reporting. Future iterations aim to improve data visualization by outputting results in tabular formats and expanding the geographic attribute dataset.

Project Summary: Orthorectification Accuracy Assessment

Domain: Land Analysis Skill: Remote Sensing

Precision Orthorectification: Aerial Imagery Accuracy Assessment
This project focused on the high-resolution orthorectification of raw aerial photography using PCI Geomatica (Catalyst). By integrating a Digital Elevation Model (DEM) and georeferenced reference data, I transformed raw flightline imagery into a map-accurate product.

Key Technical Workflows:

• Source Data Management: Utilized a KML air photo index to select and isolate specific flightline imagery from the Annapolis Royal dataset.
• Orthorectification Process: Corrected geometric distortions by tying raw imagery to a 1m Digital Elevation Model (DEM) and a 25cm georeferenced base raster.
• Rigorous Accuracy Assessment: Collected Ground Control Points (GCPs) and independent Check Points (CPs) across the scene to validate spatial integrity.
• Error Optimization: Achieved a sub-pixel RMS error of less than 25cm, meeting strict project specifications for UTM Zone 20 NAD83 coordinate accuracy.
• Visual QA/QC: Conducted a final comparative analysis between the output ortho-image and reference datasets to ensure seamless alignment and feature consistency.

Project Summary: Portfolio December 2025

Domain: Professional Development Skill: Web Development

COGS Professional Identity: GIS & Full-Stack Integration Portfolio
Developed during the Geographic Information Systems Graduate Certificate program at NSCC, this comprehensive web project serves as a professional hub for a career transition. It integrates a decade of media expertise with modern spatial sciences, utilizing a video-integrated UI to showcase academic schedules, professional experience, and technical projects.

Key Technical Workflows:

• Dynamic Multimedia Background: Engineered a modern visual experience using a fixed-position 1080p MP4 video loop, providing a high-tech "digital globe" aesthetic across all site sections without impacting content scannability.
• Structural Semantics & Navigation: Built a multi-page architecture (Home, Experience, Schedule, Contact) using semantic HTML5 and a responsive CSS navbar with hover-active states and utility classes for layout alignment.
• Complex Data Visualization: Developed a color-coded academic schedule using HTML table structures with rowspan and colspan attributes to visualize concurrent GIS and Programming fundamental courses.
• Cross-Disciplinary Skill Matrix: Documented technical proficiency across three distinct domains: GIS Analysis (QGIS, ArcGIS Online), Software Development (Java, Python, C#, React), and Expert-Level Media Editing (12 years in After Effects and Premiere Pro).
• Project Management & Internship Reflection: Systematically detailed professional milestones, including backend development for Chebucto Community Net and leading the Park Buddy capstone project through Agile/Sprint methodologies.

Project Summary: Portfolio December 2024

Domain: Professional Development Skill: Web Development

Legacy Professional Portfolio: Multi-Disciplinary Digital Showcase
This project involved the design and development of a custom, responsive portfolio website built to bridge the gap between my background in Film Studies and IT Programming. It serves as a central hub to showcase full-stack development projects alongside a decade of professional media editing experience.

Key Technical Workflows:

• 3D Environment Integration: Implemented Three.js to render an interactive, mobile-responsive 3D globe within the hero section, utilizing modern importmap configurations for modular JavaScript.
• Responsive UI Framework: Built a fluid, mobile-first interface using Bootstrap 5, featuring sticky navigation, custom grid layouts, and theme-shadow styling for a modern aesthetic.
• Interactive Media Gallery: Integrated the Fancybox UI library to provide high-resolution, lightboxed previews of programming projects and cinematography work.
• Full-Stack Project Documentation: Curated detailed post-project reflections for various applications, including 3D interactive books (BookGlide), community-driven GIS tools (ParkBuddy), and database-driven explorers (IMDB Explorer).
• Cross-Platform Asset Management: Optimized a diverse range of media assets, highlighting proficiency in both programming languages (Java, C#, Kotlin) and creative software (Adobe Premiere Pro, After Effects, DaVinci Resolve).

Project Summary: Wind Turbine Data Analysis

Domain: Renewable Energy Skill: Data Analytics

Building an ETL Pipeline for Geospatial Data Analysis: Nova Scotian Turbine Report
This project involved developing a robust ETL (Extract, Transform, Load) workflow to analyze the relationships between wind turbine technical specifications. Utilizing R and the tidyverse, I processed raw geospatial data to examine correlations between Turbine Rated Capacity, Hub Height, and Rotor Diameter.

Key Technical Workflows:

• Environment & ETL Setup: Configured a data pipeline using GGally and patchwork libraries. Implemented data type enforcement using the mutate function to ensure high-precision numeric analysis.
• Numeric Variable Analysis: Generated comprehensive summary statistics (mean, median, SD, IQR) to establish a baseline for the Nova Scotia turbine dataset.
• Distribution Visualization: Engineered a multi-plot dashboard featuring Density Plots, Histograms, and Box Plots to identify data spikes, skewness, and significant outliers in turbine dimensions.
• Correlation Analysis: Applied the Spearman Method to assess statistical trends. Discovered a strong correlation (0.817) between Hub Height and Rotor Diameter, while identifying non-linear anomalies in capacity-to-height ratios.
• Advanced Matrix Reporting: Developed a Scatterplot Matrix to visualize all bivariate relationships simultaneously, providing a holistic view of how physical turbine constraints impact energy yield.
• Frequency modelling: Conducted frequency and proportion counts to identify industry standards within the region, identifying the 80m hub height and 2300kW capacity as the most frequent regional configurations.

Conclusion: This project demonstrates proficiency in statistical programming and geospatial data cleaning. The analysis successfully validated that while physical dimensions (height and diameter) scale linearly, electrical capacity follows a more complex optimization curve influenced by external technological factors.

Project Summary: The Rivers of South America

Domain: Land Analysis Skill: GIS / Cartography

The Rivers of South America is a high-resolution cartographic study that visualizes the continent's complex water networks. By processing HydroSHEDS global data, the project shows the relationship between geographic scale and water volume, specifically focusing on the massive physical presence of the Amazon drainage system. The map uses Strahler Stream Order attributes—a system that ranks rivers by their number of tributaries—to drive a visual hierarchy, ensuring the line thickness and color accurately reflect the size and flow of each river system.

Key Technical Workflows:

• Data Processing: Sourced and clipped HydroSHEDS shapefile data specifically to the South American continental boundary to isolate the primary drainage basins.
• Dynamic Symbology: Utilized the Expression Builder in QGIS to define line widths based on the Strahler Order ("ORD_STRA" / 10), creating a visual hierarchy that reflects physical river volume.
• Stream Order Classification: Applied categorized symbology to differentiate stream orders, utilizing a graduated color ramp from deep blue to white to represent the transition from major river trunks to high-altitude headwaters.
• Professional Layout Design: Developed a high-contrast print layout with a black canvas, disabling background rendering to allow the hydrological network to stand out as the primary focal point.

Outcomes: The resulting map effectively highlights the Amazon basin’s intricate structure, demonstrating advanced competency in vector data management and thematic cartography. This workflow can be adapted for any global region to support climatology, hydrology, or environmental planning studies.

Project Summary: Supervised Land Classification

Domain: Land Analysis / Forestry Skill: Remote Sensing / GIS

This project involved performing a complex Supervised Image Classification of Landsat 9 multispectral imagery covering the Annapolis Valley, Nova Scotia. Using Catalyst Focus and ArcGIS Pro, I transformed raw spectral data into a refined thematic map identifying six primary land cover information classes.

Key Technical Workflows:

• Image Preparation & Pan-sharpening: Processed Level 1 Landsat 9 bundles, performing pan-sharpening and clipping to a specific area of interest (AOI) to enhance spatial resolution for feature identification.
• Supervised Training & Signature Analysis: Manually digitized training areas to create distinct spectral classes. Evaluated signature quality using Bhattacharrya Distance for separability, scatter plots for spectral overlap, and histograms for class homogeneity.
• Class Aggregation & Post-Processing: Aggregated various spectral classes (e.g., bare soil, rock, and quarry) into higher-level Information Classes (e.g., Barren). Applied a Sieve Filter to reduce "salt-and-pepper" noise while maintaining critical linear features like transportation networks.
• Rigorous Accuracy Assessment: Conducted a non-biased accuracy assessment using 25+ independent random reference samples per class. Generated Confusion Matrices and Kappa Coefficients to statistically validate the classification reliability.

Outcomes: The final output was a 24” x 36” professional-grade map following NRCAN standards. The project demonstrated proficiency in the full remote sensing lifecycle—from raw sensor data ingestion and statistical validation to final cartographic production.

Project Summary: Subcatchment Mapping

Domain: Land Analysis / Hazard Skill: GIS / Cartography

This project involved the development of a professional topographic and hydrological map of Lesotho. Using ArcGIS Pro, I synthesized elevation gradients with sub-catchment data (WS1–WS10) to visualize the relationship between terrain and water management infrastructure.

Key Technical Workflows:

• Data Synthesis & Cleaning: Processed raw spatial layers including DEM-derived elevation gradients, river networks, and specialized hydrological/meteorological station data.
• Advanced Symbology: Styled 10 distinct sub-catchment areas (WS1-WS10) using unique categorical identifiers, overlaid on a graduated elevation color ramp to provide geographic context for drainage patterns.
• Layout Engineering: Designed a comprehensive map layout including a secondary map frame (extent indicator) to provide regional context within Southern Africa.
• In-Map Data Tabulation: Integrated dynamic data tables directly into the layout to display catchment-specific attributes, such as calculated area in hectares, for improved technical utility.

Outcomes: The final product is a technical-grade PDF/JPEG export featuring a full suite of cartographic elements: North arrows, scale bars, legend optimization, and ESRI basemap attributions. This map serves as a template for catchment-scale environmental reporting and water resource management.

Project Summary: "Relaxation Space" – Immersive Ambient Web Platform

Domain: User Experience Skill: Web Development

During a four-month Web Development internship, I assisted in development at Little Symphony Inc. with the production of "Relaxation Space", a sophisticated ambient soundscape generator. The platform empowers users to become "sound architects," blending high-fidelity geographic audio—ranging from forest environments to diverse river variants—with modular musical layers.

Core Technical Contributions:

• Full-Stack Development: Architected the front-end using React and Chakra-UI, while leveraging Supabase for user authentication and real-time database management of "Followed" spaces.
• Modular Audio Engine: Implemented multi-track slider functionality allowing users to balance nature sounds with customizable instrument layers (Cello, Piano, Synth Pads).
• Responsive UI/UX: Developed the platform with a "mobile-first" mindset using Tailwind CSS, ensuring a seamless experience across web and mobile browsers.
• Community Features: Engineered logic for "Public Searchable Spaces," allowing users to save, share, and follow custom-created ambient playlists.

Professional Growth: This role required an intensive, self-directed deep dive into React and modern web ecosystems. Under mentor supervision, I transitioned from fundamental GIS-based programming to deploying a complex, community-driven web application tailored for sleep, focus, and meditation.

Project Summary: ParkBuddy App for Capstone Project

Domain: User Experience / Project Management Skill: Web Development

ParkBuddy is a specialized social noticeboard designed to modernize urban living in Halifax by digitizing street cleaning schedules. As the Project Manager and Creator, I conceptualized the platform to solve a common municipal pain point: dated physical signage and the resulting parking citations. I led a multidisciplinary team through an intensive development cycle, transitioning from a formal Project Charter to a functional mobile application.

Management & Strategic Contributions:

• Project Lifecycle Oversight: Authored the Project Charter and defined the scope, focusing exclusively on residential street cleaning data to ensure a high-value, niche utility for Halifax residents.
• Agile Sprint Management: Orchestrated two distinct development sprints, managing the Work Breakdown Structure (WBS) and aligning team tasks to meet critical milestones, including ERD finalization and tech stack selection.
• UI/UX Design Vision: Directed the front-end aesthetic and user flow, ensuring the mobile experience (React Native/Expo) remained intuitive for crowd-sourced data entry and street-side search functionality.
• Stakeholder Engagement: Acted as the primary point of contact for project advisors and internal team members, facilitating technical decisions between WordPress/PHP back-end integration and GeoJSON data structures.
• Data Strategy: Defined critical success factors for data integrity, leading initial collection efforts to seed the database and validate the search-based notification model.

Outcomes: Under my leadership, the team successfully delivered a functional prototype that met all key deliverables, including comprehensive requirement documentation and a polished final presentation. The project highlights my ability to manage complex schedules, mitigate platform constraints, and guide a technical team from ideation to delivery.

Project Summary: Best Path Raster Analysis

Domain: Infrastructure Planning / Land Analysis Skill: Raster Analysis / Modelling

Best Path Raster Analysis is a geospatial modelling project focused on the principles of Map Algebra and Raster Analysis using ArcGIS Pro. This project explores the mathematical frameworks used to determine the "path of least resistance" across complex geographic surfaces. By leveraging Cost Functions and PathDistance algorithms, the project demonstrates how to model optimal routes—such as road corridors—by balancing engineering constraints, environmental impacts, and social costs.

Technical & Analytical Contributions:

• Map Algebra Implementation: Applied core raster modelling concepts, including CostDistance and CostBackLink, to transform geographic units into weighted cost units based on relative and absolute constraints.
• Corridor modelling Strategy: Developed a multi-criteria impedance grid for road construction, accounting for geotechnical factors (slope, soils, hydrography) and absolute barriers like national parks or water bodies.
• Advanced Path Analysis: Utilized the PathDistance function to incorporate 3D surface distance, vertical factors, and horizontal resistance, ensuring the model accounted for real-world topographical energy expenditures.
• Python & Scripting Integration: Conducted the analysis through the ArcGIS Pro Python Window, managing environment settings such as workspace extents, cell sizes, and scratch workspaces to ensure data integrity across iterative runs.
• Iterative Optimization: Generated directional "Back Link" grids to reconstruct the single most efficient route between designated start and stop source cells, validating the theoretical "least-cost path" against spatial variables.

Outcomes: The project resulted in a robust methodological workflow for automated route selection. By successfully integrating Spatial Analyst global functions with Python scripting, the analysis showcased the ability to translate qualitative site constraints into a quantitative, data-driven spatial model for infrastructure planning and environmental mitigation.

Project Summary: Point Classification: LiDAR Terrain Modelling

Domain: Land Analysis / Forestry Skill: LiDAR / Remote Sensing

Point Classification: LiDAR Terrain Modelling is a specialized LiDAR processing workflow focused on the spatial organization and management of point cloud data within the Microstation/TerraSolid environment. As a key component of LiDAR survey analytics, the project demonstrates a professional methodology for partitioning massive datasets into manageable 1km x 1km "blocks" to optimize system memory and ensure computational efficiency during complex classification tasks.

Technical & Data Management Contributions:

• Software Configuration & Integration: Managed the integration of TerraScan (TSCAN) applications within Microstation, utilizing configuration variables (.ucf) and dedicated TerraSolid workflows to establish a high-performance processing environment.
• Spatial Partitioning Strategy: Engineered a Block-Based Data Structure by defining project parameters (LAS 1.2 format) and generating automated block arrays. This ensured that high-density LiDAR surveys remained processable within hardware memory constraints.
• Precision Geometry Alignment: Leveraged AccuDraw and Element Selection tools to manually calibrate block origins and dimensions, ensuring a seamless 1000m x 1000m grid coverage across the specific Lawrencetown study area.
• Data Integrity & Filtering: Implemented Attribute-Based Selection to prune unneeded blocks and utilized "Inside Fence" import protocols to maintain strict data boundaries, resulting in a lean and accurate project database.
• Attribute Querying & Visualization: Established advanced Display Mode configurations, symbolizing point clouds by elevation, intensity, and flightline. This allowed for detailed point-level querying and the identification of misclassified features through red "cross-hair" location tracking.
• Multi-Platform Quality Assurance: Integrated Global Mapper into the post-processing workflow for visual confirmation and cross-verification of raster outputs, ensuring high-fidelity surface reconstruction and vertical accuracy.

Outcomes: The project successfully established a scalable LiDAR Project Management framework. By transitioning raw flightline data into a labeled, block-organized system, I followed this workflow that allows for targeted ground classification and feature extraction. The final deliverables included a comprehensive Block Import Report, validating the precise point counts and spatial distribution required for professional topographic modelling.

Project Summary: Bus Stop Accessibility Study

Domain: Infrastructure Planning Skill: GIS

Using Halifax Open Data, this project involved a full-cycle GIS workflow: from raw CSV data wrangling to the deployment of a professional-grade ArcGIS Instant App. The focus was on mapping Halifax Transit Bus Stops to analyze and display accessibility levels across the municipality.

Technical Workflow: Data Governance

• Data Wrangling & Integrity: Processed raw CSV datasets by creating custom Coded-Value Domains. For the 'ACCESSIBLE' attribute, I developed a standardized domain (A, I, N) to ensure data consistency and prevent entry errors.
• Geoprocessing: Executed XY Table to Point conversion using the WGS 1984 Web Mercator (3857) coordinate system, ensuring perfect alignment with global web maps.
• Database Optimization: Utilized tools such as Table to Domain and Assign Domain to Field to link semantic meanings to raw feature codes, improving the human-readability of the transit data.

Smart Mapping & User Experience

Beyond data processing, the project emphasized Geospatial UI/UX to make transit information accessible to the public:

• Smart Symbology: Applied scale-dependent rendering and custom effects in ArcGIS Map Viewer to reduce visual clutter in high-density urban areas.
• Enhanced Pop-ups: Designed custom attribute displays to transform technical codes into clear, natural language descriptions for stop accessibility.
• Instant App Deployment: Launched a responsive ArcGIS Instant App, providing a streamlined, mobile-friendly interface for citizens to explore transit infrastructure in real-time.

Outcome: This project successfully demonstrated the transition from "unstructured open data" to a "structured web product", highlighting the importance of data integrity in public-facing GIS applications.

Project Summary: Gold Mine Land Suitability

Domain: Land Usage Skill: GIS

This project involved developing an automated geoprocessing workflow to evaluate the environmental and administrative context of fictitious gold mining sites across Nova Scotia. The goal was to provide developers with instant reporting on county administration, forest value, and soil characteristics for any given site.

Technical Workflow:

• Automated Model Development: Built a custom ArcGIS Pro ModelBuilder tool to process site data. The model automated the creation of variable-distance buffers based on site-specific attributes.
• Multi-Criteria Overlay: Integrated disparate datasets—including Forest Species (wood value), Soil Type (extraction feasibility), and County Boundaries (administrative reporting)—using an Intersect overlay logic.
• Quantitative Summarization: Utilized the Frequency Tool and field calculations to generate information-laden summary tables, converting overlapping polygon areas into hectares for precise resource reporting.
• Cloud Integration: Managed data across both local NAS environments and ArcGIS Online (AGOL), ensuring the model was compatible with industry-standard cloud data management.

Deliverable: Interactive StoryMap

The results were synthesized into an ArcGIS Online StoryMap, designed as a digital briefing note for stakeholders. This deliverable bridged the gap between raw geoprocessing results and executive decision-making, featuring:

• Site-Specific Sketch Maps: Visualizing the "Interest Area" for nine distinct locations.
• Resource Matrices: Displaying height, species, and soil stoniness in streamlined summary tables.
• Model Transparency: Documentation of the tool parameters and geoprocessing logic to ensure reproducibility.

Outcome: By automating the spatial join and overlay process, the project demonstrated how GIS can significantly reduce the "time-to-insight" for resource exploration and site feasibility studies.

Project Summary: Spatial Database Design & Querying

Domain: Forestry Skill: Database Management / GIS

This project involved the end-to-end creation of a spatial database for "COGS Park." I architected a PostgreSQL/PostGIS database to store complex forestry data and performed advanced spatial joins and geometric queries to extract management insights.

Database Architecture (Part A):

• Schema Design: Created a relational structure for 5 core feature classes: Facilities (points), Rivers and Roads (lines), and Forest Stands (polygons).
• DDL Scripting: Developed a comprehensive SQL script to automate table creation, primary key generation, and the manual addition of geometry columns using AddGeometryColumn syntax.
• Manual Digitization: Populated the database with features based on coordinate grid units, ensuring topological integrity between forest stands and intersecting road/river networks.

Spatial Analytics & Management Reporting (Part B):

I utilized PostGIS spatial functions to answer complex management questions, including:

• Topological Overlays: Identified which forest stands are crossed by specific rivers (ST_Crosses) and which administrative facilities reside within the Spruce stands (ST_Within).
• Proximity Analysis: Calculated precise distances between ranger stations and water sources, and identified facilities within a 1-unit "buffer" zone of the road network (ST_Distance).
• Quantitative Reporting: Generated automated reports for total road lengths categorized by composition (Paved vs. Gravel) and area calculations for specific silvicultural stands.

Visualizing the Results

The backend data was brought into QGIS for final cartographic production. Key features include:

• Dynamic Labeling: Implemented curved road labels with text buffers for maximum readability.
• Categorized Symbology: Styled forest stands by species and road networks by composition to provide a clear operational overview.

Project Summary: Halifax Harbour Coastal Reclamation Analysis (1916–2025)

Domain: History Skill: GIS / Cartography

This project involved a comprehensive spatial analysis of shoreline modification in Halifax Harbour. By comparing century-old hydrographic charts with modern satellite data, I quantified the extent of human-induced land reclamation and morphological change.

Analytical Workflow:

• Georeferencing Historical Archives: Successfully aligned a 1916 Canadian Hydrographic Service chart (Bedford Basin sheet) with modern coordinate systems using 1st-order polynomial transformations.
• Gap Analysis & Vectorization: Manually digitized the historical high-water mark and overlaid it against 2025 satellite imagery to identify "fill" zones and infrastructure expansion.
• Area Calculation: Utilized geodesic geometry to calculate that 0.77 sq km of land has been reclaimed or significantly modified within the study area over the last 110 years.

Technical Cartography:

The final deliverable was produced in ArcGIS Pro, utilizing advanced layout techniques to convey complex historical data clearly:

• Comparative Map Frames: Developed a dual-frame layout featuring a wide-extent overview and a high-detail inset to showcase specific areas of reclamation.
• Engineering Standards: Implemented measured UTM grids (Zone 20N), dynamic text for automated area totals, and professional neatlines.
• Data Integrity: Integrated official metadata citations and clear symbology to distinguish historical baselines from modern coastal footprints.

Project Summary: Least-Cost Path & Terrain Modelling

Domain: Infrastructure Planning / Land Analysis Skill: Raster Analysis / Modelling

Least-Cost Path Raster Analysis is a geospatial modelling project focused on the principles of Map Algebra and Anisotropic Modelling using ArcGIS Pro. This project explores the mathematical frameworks used to determine the "path of least resistance" across complex geographic surfaces. By leveraging PathDistance algorithms and multi-criteria suitability grids, the project demonstrates how to model optimal routes by balancing topographical resistance, environmental sensitivities, and construction feasibility.

Technical & Analytical Contributions:

• Map Algebra Implementation: Applied core raster modelling concepts, including Weighted Overlay and Integer Conversion, to transform disparate environmental variables into a unified cost-impedance grid.
• Anisotropic Path Analysis: Utilized the Path Distance function to incorporate 3D surface distance and vertical factors (Topography), ensuring the model accounted for real-world energy expenditures over varying slopes.
• Directional Logic Modelling: Generated Back Link (out_b) rasters to establish a directional web across the study area, allowing the algorithm to trace the "downhill" cost gradient from any destination back to the source.
• Visual Data Slicing: Performed Equal Interval Slicing on cumulative surfaces to visualize cost-contours, providing a clear intuitive check of how resistance distorts travel time and effort across the island.
• Iterative Workflow Management: Managed complex environment settings, including Masks and Snap Rasters, to ensure perfect cell alignment between point-based source data and 20m resolution environmental grids.

Outcomes: The project resulted in a robust methodological workflow for automated route selection. By successfully integrating Spatial Analyst cost functions with high-resolution terrain data, the analysis showcased the ability to translate qualitative site constraints into a quantitative, data-driven spatial model for infrastructure planning and environmental mitigation.

Project Summary: Solar Power Plant Suitability Analysis

Domain: Renewable Energy / Infrastructure Planning Skill: Raster Analysis / Modelling

This multi-stage project involved a comprehensive raster-based suitability study to identify optimal locations for a solar power plant in Nova Scotia. By transitioning from a Binary Coincidence (Pass/Fail) model to a Weighted Ranking technique, the analysis provided a nuanced gradient of land feasibility based on topography and infrastructure proximity.

Technical Workflow:

• Surface Analysis & Terrain Modeling: Derived Slope and Aspect rasters from a Digital Elevation Model (DEM). A Hillshade was generated to provide 3D visual context for site morphology.
• Binary Coincidence (Phase A): Developed a boolean logic model using the Con Tool and Map Algebra. Sites were filtered to meet strict thresholds: Slopes (6°–18°), South-facing Aspects (112.5°–247°), and proximity to transmission lines (less than 2000m).
• Environmental Masking: Engineered a land-only study area by converting hydrographic vector data into a raster mask. Utilized IsNull and SetNull functions to ensure water bodies were excluded from geoprocessing calculations.
• Multi-Criteria Weighted Overlay (Phase B): Transitioned to a ranking system where variables were reclassified into a 1–9 scale. These were integrated using the Weighted Overlay tool to allow for trade-offs between criteria.

Infrastructure & Weighting Logic:

A critical component of the model was the proximity to the electrical grid. Using Euclidean Distance, the transmission line influence was calculated and integrated into the final weighted model.

Outcome: By applying advanced Map Algebra and the Reclass by ASCII File tool, the project successfully identified a refined list of candidate sites. The workflow demonstrated the ability to convert raw elevation and utility data into a decision-support tool for renewable energy development.

Project Summary: Sensor Calibration & Boresight Alignment

Domain: Remote Sensing / Geomatics Skill: LiDAR Calibration & TerraMatch

Sensor Calibration & Boresight Alignment is a technical post-processing project focused on mitigating systematic angular misalignments between a LiDAR laser head and its Inertial Measurement Unit (IMU). Working with the Middleton dataset, this workflow demonstrates the ability to transform raw SBET (Smoothed Best Estimate of Trajectory) data and uncalibrated point clouds into high-precision, geometrically consistent topographic models suitable for engineering-grade analysis.

Technical & Calibration Contributions:

• Advanced Trajectory Integration: Processed Smoothed Best Estimate of Trajectory (SBET) files, performing coordinate transformations from Geographic NAD83 to UTM Zone 20N and accounting for meridian convergence (Grid North vs. True North).
• Flightline Delineation & Logic: Utilized Split at Laser Gaps and manual polygon clipping to isolate valid data swaths from aircraft "turn-around" maneuvers, ensuring only linear survey data informed the calibration model.
• Boresight Error Diagnostics: Conducted Profile Analysis to identify specific error signatures: Pitch (along-track shifts), Roll (across-track horizontal shifts), and Heading (alternating pitch errors), quantifying the pre-calibration "mismatch" magnitude.
• Automated Data Scripting: Engineered TerraScan Macros to deduce flightline numbers for millions of points and prepared a specialized calibration dataset by classifying ground and building surfaces independently per flightline.
• Mathematical Optimization: Executed Find Match routines within TerraMatch to solve for systematic corrections, iterating through surface-matching algorithms to minimize the Root Mean Square (RMS) error across overlapping swaths.
• Vertical Bias Correction: Performed Z-Shift Adjustments on a per-flightline basis to eliminate elevation offsets, resulting in a seamless vertical integration of the global point cloud.

Outcomes: The project successfully reduced spatial misalignment from decimeter-level errors to within the hardware's expected precision limits. By delivering a comprehensive suite of Calibration Reports (*.tms and *.txt), the workflow established a verifiable audit trail for data accuracy. The final output—a fully calibrated, block-organized, and classified LiDAR project—serves as the rigorous foundation required for accurate Digital Terrain Model (DTM) generation.

Project Summary: Accuracy Assessment & Federal Compliance

Domain: Aerial Survey / Geomatics Skill: LiDAR / QA/QC

Accuracy Assessment of LiDAR is a high-level QA/QC project centered on the absolute vertical validation of drone-based LiDAR data (Zenmuse L1). The workflow adheres to the Government of Canada’s Federal Airborne LiDAR Data Acquisition Guidelines, requiring rigorous statistical testing against high-precision RTK GNSS check points to determine data suitability for federal and provincial repositories.

Core Competencies & Professional Deliverables:

• Federal Standard Compliance: Evaluated point cloud accuracy against CQL1 (Calibration Quality Level 1) specifications, ensuring the data met mandated vertical thresholds through formal statistical reporting.
• NVA & VVA Categorization: Stratified RTK control data into Non-vegetated Vertical Accuracy (NVA) for hard surfaces and Vegetated Vertical Accuracy (VVA) for complex land covers (grass, weeds, and brush).
• Drone Project Wizardry: Streamlined the ingestion of DJI Matrice 300 RTK data, utilizing automated flightline derivation and Match Passes for sensor-specific calibration and mirror angle correction.
• Advanced Statistical Computation: Derived metrics beyond standard software outputs, calculating the 95% Confidence Level for NVA (Normal Distribution) and the 95th Percentile for VVA (Non-normal Distribution) using Excel-based modeling.
• Anomalous Data Investigation: Conducted "Blunder Analysis" by cross-referencing high-error points against 5cm resolution orthomosaics, justifying the deactivation of outliers caused by physical obstructions or misclassification.
• Formal Technical Reporting: Authored a 20-page comprehensive project report featuring cartographic project maps, survey control descriptions, and detailed appendices as per industry-standard project deliverable protocols.

Outcomes: The project culminated in a professional-grade Accuracy Assessment Report and a validated 0.5m Bare Earth DTM. By proving that the vertical error Dz remained within strict 95% confidence intervals, the project successfully certified the L1 drone survey for topographic mapping and hydrological modeling applications.

Project Summary: Wildlife Corridor Modelling & Map Algebra

Domain: Conservation Biology / Ecology Skill: Raster Analytics & Cost-Path Analysis

Wildlife Corridor Modelling is a spatial decision-support project designed to restore ecological connectivity for White-tailed deer populations in Nova Scotia. Utilizing Map Algebra and Boolean/Fuzzy logic, the model identifies optimal migration swaths through fragmented landscapes, balancing biological requirements with human-made barriers like paved road networks.

Technical Methodology & Raster Operations:

• Multi-Criteria Impedance Modeling: Engineered a complex Corridor Impedance Raster by integrating Riparian buffers, Habitat Suitability indices, and Paved Road proximity. This included managing variable weights where road bisection represents a high-cost barrier to movement.
• Supervised Landsat Classification: Performed a probability-based classification of Landsat 8 spectral bands to delineate land cover types, specifically identifying forest edges and field-pasture boundaries critical for deer browse.
• Cost-Distance Analytics: Leveraged the CostDistance function to calculate the accumulative cost of movement from discrete habitat "clusters" (identified via RegionGroup) across the impedance surface.
• Corridor Function Execution: Applied the Corridor function to sum two cost surfaces, identifying a mathematical "swath" of least resistance rather than a singular linear path, allowing for more robust conservation planning.
• Fuzzy Variable Scaling: Implemented Linear Combination (WLC) and Slice functions to standardize disparate data types (e.g., proximity to water vs. forest density) onto a common suitability scale of 1–10.
• Riparian Delineation: Operationalized Expand and Con functions to model 150m riparian corridors, prioritizing these natural movement "highways" within the final connective model.

Outcomes: The model successfully identified a primary corridor with a cumulative cost threshold of 20,586 units, effectively linking isolated habitat clusters via established riparian zones. This spatial framework provides a quantitative basis for mitigating vehicle-wildlife collisions and informing land-use policy in Queens and Lunenburg Counties.

Esri Canada GIS Ambassador Program

Domain: Esri Canada / Community Involvement / Teaching Skill: Public Speaking / Geospatial Advocacy

As a GIS Ambassador for Esri Canada, I had the privilege of visiting a middle school to introduce students to the power of geospatial thinking. Using the National Geographic MapMaker, I led an interactive demo designed to transform abstract geography into a tangible, digital exploration of our world.

Educational Demo Workflow:

I guided the students through a live "Global Discovery" workflow, moving from basic navigation to complex environmental analysis:

• Introduction to Geospatial Tools: We began by exploring Basemaps and utilizing the measuring tool to grasp the vast physical scale of Canada.
• Human Impact Visualization: By layering Light Pollution data over global Population centers, students visualized the correlation between urbanization and environmental footprint in regions like Tokyo and Europe.
• Climatology & Orographic Effects: We analyzed the Tibetan Plateau, comparing its massive scale to the width of Canada. Students used the Split Tool to compare temperature and precipitation, discovering why the Himalayas force moisture out of clouds before they reach the plateau.
• 3D Terrain & Elevation Profiling: Switching to 3D Mode, we explored the Himalayan foothills. We utilized the elevation profile tool to visualize vertical gain, discussing how the software accounts for ridges and valleys between two points.

Applied Problem Solving: The "Ice-Free Road" Challenge

To conclude, I challenged the students to act as Civil Engineers. Their mission: Plan a strategic road connection in Nepal, linking the Kosi river region to Como Chamling Lake.

• Constraint Mapping: The road had to remain in areas >0°C to avoid icing hazards. Students had to analyze temperature pop-ups to ensure the route stayed within "safe" thermal zones.
• Route Optimization: Students identified traversable valleys using the legend and plotted a multi-point path through the rugged Nepalese terrain.
• Analysis: We generated an Elevation Gain Chart for their custom route to visualize the climb and ensure the road was feasible for construction.

GANS Future Strategy Committee

Domain: Community Involvement Skill: Geospatial Advocacy

I was selected as an early-career representative for the Geomatics Association of Nova Scotia (GANS) Future Strategy Committee. In this role, I contribute to a high-level collaboration with established leaders in the geomatics community.

Strategic Objectives:

The committee is tasked with analyzing the current state of the geomatics community in Nova Scotia and recommending a path forward. My contributions focus on:

• Community Needs Assessment: Identifying the modern requirements of industry, government, and academia.
• Next-Generation Advocacy: Influencing how GANS supports early-career professionals and students.
• Strategic Path Planning: Collaborating on a 4-month strategy to redefine GANS’ core priorities, partnerships, and membership values.

Impact: By serving as a bridge between established industry leadership and the early stage geomatics professionals in Nova Scotia, I contribute to a shared effort to guide the future of the association.

Timeline: January 2026 – Present

Esri Canada ECCE App Challenge 2026

Domain: Esri Canada / User Experience Skill: GIS / Web Development

I recently competed in the Esri Canada ECCE App Challenge as part of the team "Lay Down The Law(rencetown)". Alongside two teammates from my in-person cohort, we represented the Centre of Geographic Sciences (COGS) in a high-stakes, seven-day development sprint.

The Challenge:

From February 20–27, 2026, our team was tasked with designing, building, and documenting a custom geospatial application based on a secret theme revealed only at the start of the week. This experience required a fusion of conceptually interpreting the challenge theme, spatial data extraction, and front-end design. Our goal prioritized how the spatial tool we'd create can directly better a community by solving complex local problems through geographic analysis.

Note: Specific project details are currently under wraps while the competition continues at other institutions across Canada. Full documentation and project images will be released once the national evaluation period concludes

Core Contributions:

• Conceptual Theme Interpretation: Deconstructing the national challenge topic to identify a high-impact community need and translating that vision into a functional system design within 7 days.
• Spatial Data Extraction: Sourcing and refining critical datasets to ensure the application’s underlying logic was grounded in accurate, real-world geographic parameters.
• Community-Centric Design: Developing a front-end interface focused on accessibility and utility, ensuring the app serves as a practical resource for users.
• Agile Team Synchronization: Maintaining a high-velocity development cadence with teammates to meet strict competition deadline and deliver a polished final product.

Impact: While the specific results and application details remain under wraps until the national judging concludes, this project demonstrates my ability be collaborative and create with a real-world scenario through the use of innovative GIS solutions.

Team: Lay Down The Law(rencetown)

Timeline: February 20 – February 27, 2026

Esri Canada GIS in Education & Research Conference

Domain: Esri Canada / Professional Development Skill: Networking

Role: COGS Representative of Esri Canada ECCE Student Associate Program

Timeline: October 2025 - Present

As a COGS representative for the Esri Canada Centre of Excellence (ECCE), I attended the Esri Canada GIS in Education and Research Conference at the University of Toronto on October 16th, 2025. While the technical sessions were world-class, the highlight of the event was the opportunity to bridge the gap between digital and physical classrooms. I had the opportunity to meet a few of my online COGS classmates in person for the first time, strengthening our collaborative bonds outside of the virtual environment.

Beyond peer connections, I was happy to network with keynote speakers, researchers, and Esri Canada event organizers. These interactions allowed me to discuss emerging Geospatial trends directly with the people driving them, reinforcing my foundational knowledge as I launch my career in GIS. Discussing these research breakthroughs directly with the speakers has provided a profound sense of inspiration, illuminating the diverse paths my professional journey can take and the discoveries yet to be made.

Technical Highlights & Research Synthesis:

Attending these presentations provided deep insight into the current "state-of-the-art" in GIS. My notes from the day focused on the following pillars:

• GeoAI & Data Science: Observed the use of DBSCAN Python algorithms to clean SWOT satellite data and for spatial modelling of water quality in small lakes via Sentinel-2 imagery.
• Automated Natural Hazard Surveys: Explored the use of SLAM LiDAR (Zeb Horizon RT) for rapid post-storm damage assessments, specifically distinguishing between tornado and downburst patterns through automated point cloud analysis.
• Geospatial Ecology & Coastal Science: Reviewed hydrodynamic and sediment transport modelling tools used to evaluate bluff erosion risks in Canadian coastal environments.
• Equity in Urban Infrastructure: Analyzed research on Extreme Heat Exposure Time (EHET) within public transit systems, utilizing LiDAR-based microclimate simulations to identify infrastructure gaps in low-income neighborhoods.

Impact: As an Esri Canada Centre of Excellence (ECCE) Student Associate, this conference served as a foundation for aligning my academic work at COGS with national research topics. Engaging with these projects firsthand has provided a roadmap for how I can leverage the ECCE network to solve real-world problems through both advanced technology and human connection.

ECCE Student Associate Spotlight: Adam Nearing

Domain: Esri Canada / Community Involvement / Teaching Skill: Geospatial Advocacy / Public Speaking

I am proud to share my first official blog post as an Esri Canada Centre of Excellence (ECCE) Student Associate. This blog is an introduction to my background, my academic transition from IT programming to geomatics, and my current journey as a Graduate GIS student at the Centre of Geographic Sciences (COGS). Writing this post allowed me to reflect on how my diverse experiences in fine arts and technology have build a foundation for a career focused on spatial analysis and community engagement.

Featured Sections:

• My background: How childhood explorations of Cape Breton and the Cabot Trail sparked a lifelong fascination with spatial awareness.
• Navigating the Orient: Insights into a 5-month solo, self-supported cycling tour through Taiwan and Japan, utilizing spatial planning to navigate diverse terrains and cultures.
• Global Classroom Exchange: A deep dive into my time teaching at six K-12 schools across Taiwan, using side-by-side geographic comparisons to bridge the gap between their home island and Nova Scotia.
• GIS Advocacy: My work as an Esri Canada GIS Ambassador, guiding students to view the world through a spatial lens. The blog details my instructional workflow where I assisted students to reach their own conclusions by exploring 3D map views and correlating multiple specific datasets to solve geographic puzzles.

Project Summary: Skills in Development

Advanced Geospatial Skill Acquisition: Graduate Technical Development
Currently undergoing intensive technical training at The Centre of Geographic Sciences (COGS). This phase of development focuses on mastering high-precision spatial data to support GIS planning and energy logistics.

Enterprise Data Management & Infrastructure:

Mastering ArcGIS Enterprise to build robust back-end systems for multi-user databases.

Independent Professional Development:

Proactively pursuing self-taught skills in AutoCAD, FME, and windPRO for specialized planning, data transformation, and energy logistics.

Project Summary: Additional Softwares and Platforms

Multidisciplinary Technical Proficiency: Beyond Geospatial Analysis
Maintaining a diverse technical toolkit that bridges the gap between software engineering and professional post-production. This range of expertise allows for the development of custom technical solutions and high-fidelity visual communication.

Software Development & Programming:

Proficient in building structured logic and back-end systems using React, Java, Supabase, Leaflet, C, C++, and C#. These languages form the foundation of my ability to develop custom tools and integrate complex data structures.

Professional Media Production & Post-Processing:

Expertise in cinematic storytelling and asset creation using Adobe Premiere Pro, After Effects, and DaVinci Resolve, complemented by precision image editing in Photoshop and Lightroom.

Note: Due to licensing and project privacy, source code repositories and full video reels for these platforms are available upon request.