Projects using ArcGIS in NorfolkProjects using ArcGIS in Norfolk

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Cover image for Geomorphological Mapping Project | GIS

Geomorphological Mapping Project | GIS Analysis Just wrapped up a geomorphological mapping project for a site located in Pasir Gadung Village, Pandeglang, Banten. This work focuses on identifying landform characteristics and terrain variation to support better spatial understanding and decision-making. In this map, I combined elevation data, contour analysis, and spatial interpretation to classify geomorphological units—highlighting areas dominated by undulating hill formations. The red polygons represent the project activity zones, supported by coordinate points collected from the field. I also included a cross-section (A–B) to visualize terrain changes more clearly, giving a better perspective of slope variation and landform structure across the site. Tools & Approach: - GIS processing and spatial analysis - Contour and elevation modeling - Geomorphological interpretation - Map layout and visualization This kind of analysis is essential for projects related to land development, environmental assessment, and infrastructure planning. Always open to feedback and collaboration—let’s connect 🚀

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Cover image for Designed and developed an interactive

Designed and developed an interactive web visualization application featuring dynamic maps, data dashboards, and user-friendly analytics. The platform enables efficient exploration of complex data through responsive and visually engaging interfaces.

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Cover image for AERIAL RENDERS - MANCHESTER AIRPORT HOTELS

AERIAL RENDERS - MANCHESTER AIRPORT HOTELS

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Cover image for Forest health assessment using GEOBIA

Forest health assessment using GEOBIA

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Cover image for From static maps → interactive

From static maps → interactive spatial experiences. 🚀 Recently experimented with building a Geo-inspired commute dashboard using Vibe Coding + geospatial visualization. The interesting shift for me: Instead of spending days moving between GIS software, frontend development, and UI iteration, ideas can become working interfaces much faster. Still early, but it opens up interesting possibilities: → spatial analytics that feel more accessible → interfaces ready for predictive layers and AI workflows → reducing the barrier between geographic data and end users Curious where GIS + AI + Vibe Coding goes next.

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Cover image for Fiber Optic Field Operations PWA (19,000 Lines)

Fiber Optic Field Operations PWA (19,000 Lines)

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Cover image for Professional Geomorphology Map & Terrain

Professional Geomorphology Map & Terrain Profile (ArcGIS/QGIS) I create precise and visually clear geomorphological maps like this, including: - Contour mapping (index & detailed) - Landform interpretation - River and infrastructure overlay - Project boundary mapping - Elevation cross-section analysis (A–B profile) Perfect for research, environmental analysis, mining, or land development projects.

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Cover image for Created a 3D urban parking

Created a 3D urban parking facility model for a city development project, showcasing efficient parking layouts, traffic circulation, and public accessibility. The visualization supported urban planning, infrastructure design, and decision-making processes.

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Cover image for Canopy crown indentification using LiDAR

Canopy crown indentification using LiDAR

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Cover image for One of the most interesting

One of the most interesting shifts in AI right now: Real estate AI systems are only as smart as the spatial data behind them. Just wrapped up a GeoAI-oriented automation project for large-scale parcel intelligence in Australia. Built a standalone workflow that automatically detects: → frontage roads → corner lots → parcel orientation → multi-road adjacency → spatial access relationships The interesting part wasn’t the GIS itself. It was converting messy spatial relationships into structured knowledge that downstream AI systems can actually understand. A lot of “AI for real estate” conversations focus on LLMs. But the real bottleneck is often: How do you turn geography into machine-readable reasoning context? Ended up packaging the entire workflow into a production-ready executable app for non-technical teams, with batch processing + configurable spatial rules. Feels like we’re moving from: “mapping data” to “building spatial reasoning infrastructure.” #GeoAI #PropTech #SpatialComputing #Automation #GIS #AIInfrastructure

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Cover image for Geospatial Analyst & 3D Modeling

Geospatial Analyst & 3D Modeling Specialist for Infrastructure, Mining & Urban Development

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Cover image for I create interactive 3D city

I create interactive 3D city visualizations showing how urban areas evolve over time. Using Kepler.gl (http://Kepler.gl), building footprint data is visualized in 3D with a time slider based on construction year, revealing the growth of a city. Each building is clickable and includes a direct link to street-level imagery in Google Street View, allowing users to explore the real-world view of the building. This visualization is ideal for urban planning, real estate analysis, city storytelling, and digital twin presentations.

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