Objectives of the Product

Portuguese municipalities manage complex territorial challenges, including urban sprawl, wildfire risk, invasive species, water quality and regulatory compliance, but lack the technical capacity to access and interpret the Earth observation data that could inform their decisions. Most of Portugal’s 308 municipalities have no GIS specialists as staff.

LandOS addresses this gap with an AI-powered conversational platform. Municipal staff ask questions in natural Portuguese, such as “How has urban sprawl changed in our municipality over the last five years?”, and receive evidence-based answers in the form of maps, charts, and downloadable PDF reports. The platform combines Sentinel-2 satellite imagery with Portuguese national datasets (CAOP administrative boundaries, COS land cover, REN/RAN ecological reserves) through an agentic AI system that autonomously selects and executes the appropriate geospatial analysis.

The project develops, deploys, and validates this platform in a 12-month product development cycle, piloting with three Portuguese municipalities (Fundão, Odemira, Mértola) and targeting TRL 7 readiness for commercial launch.

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Customers and their Needs

Target users: Municipal staff in Portuguese municipalities, specifically:

• Urban planning technicians (‘técnicos de urbanismo’): need to monitor urban expansion, validate development permits against REN/RAN protected zones, and support PDM (municipal master plan) revisions with evidence
• Environmental officers (‘técnicos de ambiente’): need to track water quality in reservoirs, monitor invasive species spread, and report on environmental indicators
• Civil protection coordinators: need seasonal fire risk assessments cross-referenced with ICNF wildfire records to prioritise prevention actions
• Municipal managers (‘gestores’): need high-level dashboards and reports for decision-making and compliance reporting

Key challenges: These users are domain experts but not GIS specialists. They cannot use traditional remote sensing tools. They need information delivered in Portuguese, in formats they already understand (reports, maps, simple dashboards), without requiring training in satellite data interpretation.

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Targeted customer/users countries

Country: Portugal (pilot municipalities: Fundão, Odemira, Mértola). Expansion target: Southern European municipalities

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Product description

LandOS provides a cloud-based Software-as-a-Service (SaaS) platform accessible through a web browser. The system has three main layers:

1. Conversational Interface – Municipal staff type questions in natural Portuguese. The system understands municipal terminology and context (e.g., parish names, regulatory references, land-use categories).
2. Agentic AI Engine – An AI based orchestration system automatically determines which data sources and analytical tools are needed, retrieves the relevant data, executes the analysis, and synthesises the results into a clear Portuguese-language response with supporting maps and charts.
3. Analytics & Visualisation – Five core analytics modules are delivered as part of the minimum viable product: urban sprawl detection (COS change analysis), water quality monitoring (Sentinel-2 spectral indices), fire risk assessment (multi-factor: NDVI, topography, weather), invasive species detection (Random Forest ML on Sentinel-2), and regulatory compliance checking (REN/RAN spatial intersection). Results are displayed as interactive maps, charts, and branded PDF reports.

The platform is built on Project Zeno, a proven open-source geospatial AI framework, and runs on cloud infrastructure that ensures EU data residency and GDPR compliance.

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Added Value

LandOS relies on Copernicus Sentinel-2 multispectral imagery as its primary Earth Observation data source, complemented by the European Digital Elevation Model (EU-DEM) from the Copernicus Land Monitoring Service.

Sentinel-2 enables four of the five core analytics: water quality monitoring through NDWI and chlorophyll-a spectral indices; fire risk assessment through NDVI vegetation health analysis; invasive species detection through spectral signature classification; and urban sprawl analysis through multi-temporal land cover comparison. Without satellite-derived data, these analyses would require costly and infrequent field surveys that most Portuguese municipalities cannot afford.

The space added value is the ability to provide consistent, repeatable, municipality-scale environmental monitoring at a frequency (every 5 days with Sentinel-2) and spatial coverage (all 308 Portuguese municipalities simultaneously) that no ground-based alternative can match. By combining this EO capability with AI-powered natural language access, LandOS removes the technical barrier that has historically prevented municipalities from benefiting from the Copernicus programme.

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Current Status

The project kicked off in March 2026 following contract signature with ESA under the InCubed “EO for Municipalities” call. The Kick-Off Meeting took place on 24 March 2026.

The first development phase (Months 1–2) focuses on deploying the cloud infrastructure foundation on AWS, implementing the authentication and monitoring systems, and completing the Portuguese localisation of the user interface and AI agent prompts. Three pilot municipalities, Fundão, Odemira, and Mértola, have confirmed their participation through signed Letters of Support, and pilot agreement formalisation is underway.

The Requirements Review (first milestone) is planned for June 2026