City Heat & Green

High-resolution satellite and drone imagery analyze urban green cover and surface temperatures to pinpoint heat islands, guiding sustainable city planning.

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How does it work?

Urban planners and public health officials lack accurate, up-to-date maps of green cover and urban heat islands, limiting targeted cooling strategies and green space investments. AI-driven geospatial analysis of multi-temporal satellite and drone data provides scalable, high-resolution environmental-quality maps, enabling effective mitigation and urban resilience planning.

High-Resolution Green Mapping

The platform classifies vegetation types and canopy density at sub-meter resolution using AI-driven image segmentation. This delivers precise green cover metrics for fine-grained urban forestry and park management.

Heat Island Detection

Surface temperature anomalies are identified with thermal band analysis, highlighting urban heat island hotspots. This supports targeted cooling measures like tree planting, reflective surfaces, and green roofs.

Temporal Change Tracking

Automated time-series analytics monitor shifts in green cover and thermal patterns over weeks or years. This reveals the impact of interventions and urban developments on environmental quality.

Scalable Data Processing

Cloud-based pipelines ingest satellite and drone imagery at city scale, ensuring rapid turnaround on large datasets. This enables analysis of thousands of square kilometers without manual processing.

Custom Alerts & Reports

Users can set thresholds for green loss or temperature rise to receive automated notifications. Detailed reports with maps and statistics facilitate stakeholder communication and compliance.

GIS & API Integration

Results integrate seamlessly via standard GIS formats and REST APIs into planning and asset management systems. This streamlines workflows and supports cross-department collaboration.

Frequently asked questions

Have a different question and can’t find the answer you’re looking for? Reach out to our support team by sending us an email and we’ll get back to you as soon as we can.

How does this solution compare to traditional in-situ temperature sensors?
Satellite-based thermal imaging provides comprehensive spatial coverage while sensors offer point-specific data. Combining both delivers high-resolution maps with on-the-ground validation for accurate heat island characterization.
Why is AI-driven mapping popular among urban planners?
AI accelerates image processing and delivers consistent classifications across large areas, reducing manual effort. This popularity stems from precise insights into green space distribution and thermal anomalies for evidence-based planning.
What are limitations of using drone imagery versus satellite data?
Drones offer higher spatial resolution but cover smaller areas and require flight permissions, making frequent mapping resource-intensive. Satellites provide regular, extensive coverage at coarser resolutions, which may miss fine-scale features.
Can the platform analyze other environmental indicators like air quality?
The core system supports multi-spectral and thermal data, and can integrate external pollutant datasets via APIs. While air quality requires ground sensor integration, the platform's flexible data model accommodates combined analyses.
How often can I update urban heat and green cover maps?
Update frequency depends on data sources: diurnal or weekly for drones and 5–10 days for satellites like Landsat or Sentinel. Automated pipelines process new imagery as soon as it's ingested, enabling near real-time monitoring.
Are there alternative methods for urban green mapping?
Index-based approaches like NDVI and EVI provide quick vegetation assessments but can struggle in densely built environments. AI segmentation offers more accurate canopy delineation by leveraging texture and context beyond simple spectral thresholds.

Geospatial AI Platform

Intelligence

AI & foundation models

Deep-learning and foundation models turn raw imagery into ready-to-use insights, so you ship answers instead of training pipelines.

Experience

Conversational workflow

Ask questions in plain language and the platform responds with charts, visualizations, and next step suggestions.

Speed

GPU-accelerated cloud

Cloud-native architecture spins up on-demand GPU clusters that scale from a single scene to global archives—no manual ops, no bottlenecks.

Data

Any sensor, any format

Optical, SAR, drone, IoT, vector or raster—ingest, fuse, and analyze without conversion headaches.

Visualization

Insight you can see

Real-time 2D / 3D maps and export-ready plots make results clear for engineers, execs, and clients alike.

Boost your productivity. Experience Geospatial AI.

Turn satellite, drone, and sensor data into clear, real-time insights using powerful AI – no complex setup, just answers you can see and act on.

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