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Changelog

All notable changes to EcoTrack will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

Planned

  • Apache Kafka event streaming integration
  • Apache Airflow DAG orchestration
  • GraphQL API layer
  • ONNX model optimization pipeline

0.1.0 - 2026-02-18

Added

Platform Core

  • Initial release of the EcoTrack Planetary Environmental Intelligence Platform
  • Core domain models for 5 environmental domains: climate, biodiversity, health, food security, resource equity
  • Configuration management with environment-based YAML configs
  • Structured logging with correlation IDs and domain context
  • Prometheus metrics integration for all services
  • Security module with JWT/API key authentication, rate limiting, and input sanitization

Data Pipeline (ecotrack_data)

  • Extensible DataSource base class for building connectors
  • 7 real-world data source connectors:
    • Copernicus — Sentinel satellite imagery via SciHub API
    • NASA Earthdata — MODIS, Landsat, VIIRS products
    • NOAA Climate — Station observations and GFS forecasts
    • OpenAQ — Real-time air quality measurements from 100+ countries
    • GBIF — Species occurrence records from the Global Biodiversity Information Facility
    • ERA5 — Climate reanalysis data (1940–present) from Copernicus CDS
    • USDA CropScape — Cropland data layers for the United States
  • 3 data processor types: raster, tabular, and time-series
  • Multi-backend storage: local filesystem, S3/MinIO, PostgreSQL
  • Data source registry for dynamic connector management
  • Pipeline orchestration framework

Machine Learning (ecotrack_ml)

  • 5 model architectures:
    • Climate Forecaster — Temporal Convolutional Network + Transformer for multi-variate forecasting
    • Land Cover Segmenter — U-Net with ResNet encoder for semantic segmentation
    • Species Detector — CNN classifier (ResNet/EfficientNet) for species identification
    • Anomaly Detector — Variational Autoencoder for environmental anomaly detection
    • Crop Yield Predictor — Gradient-boosted ensemble for yield estimation
  • PyTorch 2.x training pipeline with mixed precision, torch.compile, and cosine scheduling
  • Evaluation framework with domain-specific metrics
  • ONNX export and inference engine with graph optimization
  • Weighted ensemble engine with uncertainty quantification
  • Feature store backed by PostgreSQL + pgvector
  • MLflow integration for experiment tracking and model registry

Geospatial (ecotrack_geo)

  • CRS transformation utilities
  • Raster processing (read, write, reproject, clip)
  • H3 hexagonal tiling at configurable resolutions
  • Vector geometry operations

Knowledge Graph (ecotrack_kg)

  • Neo4j 5 client with connection pooling
  • ENVO/SWEET environmental ontology builder
  • Cypher query builder and template library
  • Graph reasoning engine for causal and taxonomic queries

Multi-Agent System (ecotrack_agents)

  • Base agent framework with tool-use capabilities
  • 5 specialist agents: Climate, Biodiversity, Health, Food Security, Equity
  • Orchestrator with hierarchical task decomposition and synthesis
  • 16+ agent tools: data query, ML inference, geospatial analysis, visualization, knowledge graph
  • Shared conversation memory

Causal Inference (ecotrack_causal)

  • Causal discovery: Granger causality, PC algorithm
  • Causal estimation: IPTW, propensity score matching, regression adjustment
  • Counterfactual analysis for policy evaluation
  • Environmental causal analysis toolkit

Reinforcement Learning (ecotrack_rl)

  • 3 custom Gymnasium environments:
    • Water Allocation — Multi-stakeholder water resource optimization
    • Carbon Trading — Emissions trading market simulation
    • Conservation Planning — Protected area selection with budget constraints
  • DQN agent with experience replay and target networks
  • PPO agent with generalized advantage estimation
  • Reward shaping utilities and policy evaluator

Federated Learning (ecotrack_federated)

  • 4 aggregation strategies: FedAvg, FedProx, FedMedian, FedTrimmedMean
  • Differential privacy with configurable epsilon/delta budgets
  • Federated client and server framework
  • Support for heterogeneous data distributions

FastAPI Python API

  • 45+ REST endpoints organized by environmental domain
  • Pydantic request/response schemas with validation
  • JWT and API key authentication middleware
  • Rate limiting (free/researcher/institutional tiers)
  • Input sanitization and CSP headers
  • Health check, metrics, and version endpoints
  • Swagger/OpenAPI documentation at /docs

Next.js Dashboard

  • Geospatial analytics dashboard with MapLibre GL and deck.gl
  • Domain-specific pages: climate, biodiversity, health, food, equity
  • Alert panel with real-time updates
  • Metric cards and summary views
  • Responsive layout with Tailwind CSS

CLI

  • Click-based command-line interface
  • Data ingestion commands
  • Model training and evaluation commands

Celery Worker

  • Async task processing for data ingestion and model training
  • Redis broker with data and ml queues

Infrastructure

  • Docker Compose development stack (PostgreSQL, Redis, Neo4j, MinIO, MLflow)
  • Dockerfiles for API, worker, and web services
  • Kubernetes manifests with Kustomize base and overlays (staging, production)
  • HPA autoscaling, PodDisruptionBudgets, NGINX ingress
  • Terraform modules for AWS: VPC, EKS, RDS, ElastiCache, S3, ECR
  • Prometheus alerting rules and scrape configs
  • Grafana dashboard for platform overview

Testing

  • 60+ unit tests across all packages
  • Integration test suite for pipeline flows
  • pytest configuration with async support
  • Shared test fixtures and conftest

Documentation

  • System Architecture document with Mermaid diagrams
  • Technical Vision document
  • API reference documentation
  • Contributing guide with code style and PR process
  • Quickstart, data ingestion, model training, and agent development tutorials
  • Research whitepaper
  • Setup guide with troubleshooting

CI/CD

  • GitHub Actions workflows for lint, test, build, and deploy
  • Multi-stage Docker builds with layer caching
  • Security scanning with Trivy