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Portfolio

Applied GeoAI and Geospatial Systems

A selection of real-time applications, geospatial intelligence systems, and operational tools developed by SiwaLab across weather monitoring, emergency reporting, and flood hazard awareness.

Featured Applications

Operational GeoAI and Geospatial Systems in Practice

These projects reflect SiwaLab’s approach to applied geospatial intelligence by combining real-time data, spatial analysis, environmental modeling, and modern application development into decision-ready systems.

Texas Weather Dashboard

React · Node.js · PostgreSQL · MapLibre GL · Docker

● Live Application

Overview

A production-grade real-time weather intelligence platform that aggregates live observations from more than 450 stations across Texas, spanning TexMesonet, ASOS airport stations, and RAWS fire-weather stations. The system provides a unified geospatial interface for situational awareness, National Weather Service alert monitoring, and threshold-based environmental intelligence.

Key Features

Interactive MapLibre GL map with real-time station markers and alert-based symbology
Animated radar overlay with recent precipitation playback
NWS official alert integration with severity-aware display
Texas county boundaries with popup interaction
Rolling PostgreSQL observations database with automated retention
Scheduled ingestion and refresh workflows for multiple live data feeds
Mobile-responsive design for operational monitoring

Tech Stack

Frontend: React 18, Vite, MapLibre GL
Backend: Node.js, Express, scheduled jobs
Database: PostgreSQL 16 (Docker)
APIs: TexMesonet, Synoptic, NWS, RainViewer
Deployment: Docker Compose

Data Sources

TexMesonet API (TWDB)
Synoptic Data API (ASOS and RAWS)
NWS Alerts API
RainViewer radar imagery

Emergency Incident Reporting System

React · Leaflet · Supabase · Geolocation API

Overview

A location-aware emergency reporting application designed for field operations. Users can report incidents through an interactive map, classify emergency type, add descriptive notes, and synchronize submissions immediately through a live backend workflow.

Key Features

GPS-based user location and continuous position tracking
Click-to-report map interface for incident placement
Incident type classification and description entry
Real-time synchronization through Supabase
Local storage fallback for resilience in unstable conditions
Report history with map-focused navigation
Mobile-first interface for field usability
User feedback notifications for submission status

Tech Stack

Frontend: React 18, Vite
Maps: React-Leaflet, Leaflet 1.9
Backend: Supabase (PostgreSQL)
Services: Geolocation API, client-side storage
Build: Vite

Texas Flood Hazard Intelligence

GeoAI Application · Real-Time Data · Hazard Modeling

Overview

A near real-time flood intelligence platform designed to integrate rain rate observations, river stage data, river extent mapping, and elevation models to estimate evolving flood hazard conditions across Texas. The system is intended to support early warning awareness for roads, campsites, low-lying infrastructure, and other flood-prone locations.

Core Inputs and Capabilities

Near real-time rain rate observations
River stage and gauge-based hydrologic conditions
River extent and watershed spatial layers
Elevation-informed hazard screening using DEM data
Spatial identification of roads, campsites, and critical exposed areas
Early warning logic for elevated flood risk conditions

Primary Data Inputs

Rain rate observations
River stage and gauge feeds
River and watershed spatial layers
Digital elevation models
Critical location overlays

Interested in building something similar?

If you are planning a weather dashboard, field reporting tool, flood intelligence platform, or custom geospatial application, SiwaLab can help translate your concept into a practical operational system.

Discuss Your Project →