qgis-geospatial-portfolio

A professional portfolio showcasing QGIS-based geospatial analysis projects, including public health mapping, spatial data visualization, and GIS-driven decision support systems.

# 🧭 QGIS Geospatial Analysis Portfolio

A professional portfolio showcasing geospatial analysis projects built using QGIS, R (sf, ggplot2), and spatial data workflows. This repository demonstrates the application of GIS in public health mapping, field operations, and data-driven decision-making.

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🚀 Live Portfolio Website

👉 https://omisoclinton96.github.io/qgis-geospatial-portfolio/

(Replace yourusername with your actual GitHub username after publishing)

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📌 Project Highlights

🗺️ Health Facility Mapping and Accessibility Analysis — Kenya

Mapped health facilities across multiple counties to assess service coverage and geographic accessibility.

• Integrated shapefiles with facility datasets
• Performed buffer analysis to estimate service reach
• Identified underserved regions for targeted intervention

Impact: Supported evidence-based planning and resource allocation in healthcare systems.

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📍 Geospatial Tracking of Participants — OCV Trial

Developed spatial workflows to track participant distribution and support field coordination in a clinical trial.

• Visualized participant density and clustering
• Linked spatial data with operational datasets
• Improved follow-up planning using geographic insights

Impact: Enhanced field efficiency and participant tracking strategies.

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🔥 Spatial Hotspot Analysis for Risk Identification

Conducted spatial analysis to detect high-risk geographic zones using clustering and density mapping techniques.

• Generated heatmaps and hotspot visualizations
• Compared spatial patterns across regions
• Highlighted priority areas for intervention

Impact: Enabled targeted response strategies and improved monitoring.

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🔄 Geospatial Visualization of Field Operations & Sample Flow

Mapped operational workflows and sample movement across facilities to improve coordination and identify bottlenecks.

• Visualized movement between field and lab locations
• Identified delays and inefficiencies in workflows
• Supported operational decision-making

Impact: Improved visibility and efficiency in research operations.

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🛠️ Tools & Technologies

• GIS: QGIS (Spatial Analysis, Mapping, CRS)
• Programming: R (sf, ggplot2, leaflet)
• Data: Shapefiles, GPS data, spatial datasets
• Techniques: Buffer analysis, clustering, heatmaps, spatial joins

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🌍 How to Deploy This Portfolio (GitHub Pages)

1. Create a new repository named:
3. Upload the following files:
   • index.html
   • README.md
   • assets/ folder
4. Go to:
6. Under Source:
   • Select Deploy from a branch
   • Branch: main
   • Folder: /root
7. Click Save

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🌐 Your Portfolio Link

After deployment, your site will be available at:

👉 https://omisoclinton96.github.io/qgis-geospatial-portfolio/

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✏️ Customization

Before sharing your portfolio, update:

• Your name in index.html
• Your email and GitHub profile link
• Replace placeholder images with your actual QGIS map outputs

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📬 Contact

• Email: omisoclinton96@gmail.com
• GitHub: https://github.com/omisoclinton96

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💡 About This Portfolio

This portfolio reflects practical experience in applying geospatial analysis to real-world challenges, particularly in public health and research environments. It emphasizes not just map creation, but the ability to generate actionable insights from spatial data.

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1. Under Source:
   • Select Deploy from a branch
   • Branch: main
   • Folder: /root
2. Click Save

---

🌐 Your Portfolio Link

After deployment, your site will be available at:

👉 https://yourusername.github.io/qgis-geospatial-portfolio/

---

✏️ Customization

Before sharing your portfolio, update:

• Your name in index.html
• Your email and GitHub profile link
• Replace placeholder images with your actual QGIS map outputs

---

📬 Contact

• Email:omisoclinton96@gmail.com
• GitHub: https://github.com/omisoclinton96

---

💡 About This Portfolio

This portfolio reflects practical experience in applying geospatial analysis to real-world challenges, particularly in public health and research environments. It emphasizes not just map creation, but the ability to generate actionable insights from spatial data.

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