Buyer’s guide to remote sensing data

If you're sourcing remote sensing data for a carbon project, you've probably tried comparing providers by matching their pixels against your own field plots. It's a natural instinct — but done the simple way, it can rank a stronger provider below a weaker one purely by chance.

This guide walks through why that happens, how to compare providers properly using the field data you already have, and what else to weigh — like independent validation and lidar reference data — when your field data alone isn't enough to decide.

In this guide:

• The 4 pitfalls that make simple plot-to-pixel comparisons unreliable
• 3 ways to compare providers using distributions, not single points
• How airborne and drone lidar can strengthen your reference data
• A checklist for choosing a provider on merit, not chance