PISMA-WP: Platform for Intelligent Socio‑Environmental Monitoring and Analysis

What is PISMA-WP?

PISMA-WP is an Avanza UC research project that pilots a socio-environmental monitoring platform in the Exploradores Valley at UC’s Patagonia Station. It integrates open satellite imagery with local environmental instrumentation and socio-territorial indicators to produce actionable, explainable metrics for territorial planning and conservation.

Why it matters

Relying only on remote sensing limits local relevance and resolution. PISMA-WP addresses this by combining Earth observation with ground measurements and social signals under a FAIR-aligned governance model, improving reproducibility, traceability, and decision usefulness for regional stakeholders.

Objectives

1. Design data and governance architecture with reproducible ingestion, metadata, versioning, and a catalog of indicators with full lineage.
2. Implement multimodal fusion and explainable modeling with uncertainty quantification for priority processes.
3. Validate the prototype in the field and benchmark against current baselines to assess technical and operational value.

Methods and architecture

• Multimodal data cube: satellite, climate, cartography, administrative records, mobility/text data, and station time series aligned in space and time.
• Explainable GeoAI: models with feature importance, calibration curves, and uncertainty bands, evaluated with spatially aware validation.
• APIs and viewer: versioned access to indicators and time series for analysts and decision makers.
• Governance and FAIR: quality checks, provenance, roles and access policies, ethical safeguards, and documentation for reuse.

Deliverables

• Published variable and metadata catalog.
• ETL pipelines with orchestration and data quality controls.
• Model components for change detection, fragmentation, and tourism-climate interactions.
• Prototype API and web viewer in the test environment.
• Governance, security, ethics, and operations policies approved.

Pilot and validation

The pilot focuses on the Exploradores Valley with:

• Technical validation: metrics, thresholds, and reproducible results; temporal and spatial blocked cross-validation.
• Field validation: control points and local sensor comparisons.
• Operational exercises: user studies with regional actors to test usefulness, time-to-insight, and adoption barriers.

Connection with SAVIIA

PISMA-WP leverages SAVIIA as a backbone for hybrid local–cloud data governance and reproducible pipelines, enabling scalable integration across RCER stations.

PISMA-WP advances applied GeoAI for territorial management by operationalizing multimodal fusion, explainability, and uncertainty on top of governed, FAIR-compliant data workflows, so local decisions can rely on transparent, reusable evidence.

Project Team:

• Reseearchers: Alejandro Salazar, Rodrigo A. Carrasco
• Students: Sabina Lemunao