Build, automate, and validate satellite-driven carbon accounting and
MRV (Measurement, Reporting, Verification) systems — from raw imagery to audit-ready inventories.
🌐 www.spatialpipelineengineering.org
Spatial Pipeline Engineering is a practitioner-focused technical library for the engineers who turn Earth observation into defensible carbon numbers. Modern carbon accounting has moved out of spreadsheets and into distributed, spatially explicit data pipelines — and treating that work as an afterthought is how an emissions inventory quietly becomes unreportable.
Every guide pairs production-ready Python with the compliance context behind it: deterministic geospatial
processing, rigorous uncertainty quantification, and cryptographically verifiable audit trails that stand
up to third-party verification. Examples favour real engineering over theory — structlog telemetry,
explicit coordinate-reference-system declarations, distortion and validation gates, and root-cause
troubleshooting you can apply directly to a running pipeline. External references are limited to primary
sources: the GHG Protocol, ISO 14064, CSRD ESRS E1, IPCC guidance, and the Verra and Gold Standard
methodologies.
The library spans 51 in-depth guides across four connected areas of practice.
The contracts every downstream component inherits — canonical schema design, deterministic coordinate-reference-system alignment, GHG Protocol Scope 3 spatial mapping, data lineage and provenance, registry integration, and the validation gates that decide whether a figure is reportable.
Turning Sentinel and Landsat archives into activity data — cloud masking, temporal aggregation, distributed tile processing with Dask, cloud-optimized formats, change detection, and real-time deforestation alerts.
Estimating how much carbon a landscape stores and proving it — LiDAR/SAR biomass fusion, emission-factor uncertainty mapping, ground-truth alignment, baseline threshold tuning, and forest-carbon baseline and additionality modeling.
Running and governing the whole system — orchestrating MRV pipelines with Airflow, Prefect, and Dagster, the canonical data-schema reference, and the registry standards and methodologies that outputs must satisfy, including tooling decision guides and CSRD ESRS E1 mapping.
ESG and climate data engineers, sustainability tech teams, and Python GIS developers who need to ship carbon and emissions pipelines that are reproducible, auditable, and compliant — not just plausible.
A fast, offline-capable static site: hand-authored, theme-aware inline SVG diagrams, structured data on every page, and a strict quality bar (accessibility, performance, link integrity, and structured-data validity are all gated before release). No trackers, no third-party scripts.
→ www.spatialpipelineengineering.org
Start with the area that matches your problem, or read a section overview end-to-end — every page links to its neighbours, so you are never more than a click or two from the context you need.