Planetary computing for data-driven environmental policy-making

TL;DR

This paper advocates for 'planetary computing' infrastructure to process and analyze global environmental data, enhancing science and policy-making through scalable, traceable, and reproducible geospatial data solutions.

Contribution

It introduces the concept of planetary computing for environmental data and classifies existing solutions based on scalability and trustworthiness, highlighting research gaps.

Findings

Existing solutions vary in scalability and trust features.

Identified challenges in handling evolving, sensitive datasets.

Highlighted need for access control in long-term environmental data.

Abstract

We make a case for "planetary computing" -- infrastructure to handle the ingestion, transformation, analysis and publication of global data products for furthering environmental science and enabling better informed policy-making. We draw on our experiences as a team of computer scientists working with environmental scientists on forest carbon and biodiversity preservation, and classify existing solutions by their flexibility in scalably processing geospatial data, and also how well they support building trust in the results via traceability and reproducibility. We identify research gaps in the intersection of computing and environmental science around how to handle continuously changing datasets that are often collected across decades and require careful access control rather than being fully open access.