Projects using Leaflet in LahoreProjects using Leaflet in Lahore
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Cover image for 🗺️ Web GIS for Field
🗺️ Web GIS for Field Operations & Location-Based Data Collection I developed an interactive geospatial platform designed to help teams visualize, manage and update field-work information directly on a map. The application combines Web GIS, satellite imagery, spatial data management and field reporting in a single workflow. Key capabilities include: • Interactive field map with spatial work areas • Color-coded work / prescription classifications • Multiple GIS sub-maps and project views • Satellite and OpenStreetMap basemap switching • Work completion and status tracking • Location-based field-point creation • GPS coordinate capture • Field categorization and notes • Photo attachment support for field observations • Map-based project and team workflows The goal is to replace disconnected field records with a centralized spatial workflow, where teams can see exactly where work is required, record observations from the field, and maintain geographically accurate project information. Built around Web GIS, spatial databases and interactive mapping. Interested in projects involving GIS development, field-data collection, asset management, spatial dashboards and geospatial workflow automation.
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Cover image for 🚗🌍 Can a navigation system
🚗🌍 Can a navigation system recommend the most fuel-efficient route instead of simply the shortest one? This project was developed as part of my MPhil Remote Sensing & GIS thesis. I designed and developed an intelligent Web GIS routing system that generates and compares four alternative routes between an origin and destination and recommends the most suitable route using a Multi-Criteria Decision-Making (MCDM) approach. Instead of considering only distance, the system evaluates multiple factors such as: • 🌱 Fuel-efficiency / environmental suitability • ⏱ Travel duration • 🚧 Road hurdles and route conditions • 📏 Travel distance The alternatives are evaluated using a TOPSIS-based decision model, allowing the system to identify the route with the best overall balance rather than simply choosing the shortest path. I also integrated an AI assistant that explains route recommendations in natural language, helping users understand why one route is preferable to the alternatives. Key features: • Interactive Web GIS navigation • Four-route generation and comparison • MCDM/TOPSIS route ranking • Fuel-efficient route recommendation • Route distance and travel-time analysis • Road-condition / hurdle consideration • AI-generated route explanations • Interactive route visualization • Decision-support interface for sustainable mobility Built with Python, Django, GIS, Leaflet/OpenStreetMap, MCDM and AI integration. This research explores how GIS + decision science + AI can support smarter and more sustainable urban mobility.
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