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Short Abstract

Deep Time demonstrates how citizen science transforms landscapes and lives. Across 9 missions, 6,500 participants mapped heritage and habitats over 5,300 km², producing professional-grade, national-scale data and reporting improved wellbeing, eco-agency, connection to place and climate anxiety.

Abstract

Deep Time demonstrates that citizen science can transform both landscapes and lives. Designed by DigVentures, this UK-wide platform trains citizens to analyse satellite and LiDAR data, mapping heritage and habitats at a scale previously achievable only by professionals. Across nine missions covering 5,300 km² of priority landscapes, 6,500 participants created 70,000 validated data points supporting reforestation, climate resilience, and nature-recovery planning with partners including Natural England, the National Trust, and National Landscapes.

A mixed-methods evaluation (n = 6,500) measured environmental attitudes, behaviours, and wellbeing before and after participation. Ninety-two percent reported new pro-environmental choices; 68 percent felt stronger connection to place; and nearly a quarter experienced reduced climate anxiety. Half were first-time heritage or ecology volunteers, with balanced gender representation and 15 percent from non-white backgrounds.

By integrating Earth Observation data with collective intelligence, Deep Time created a national model for citizen-powered landscape intelligence. Its training ecosystem, accessible GIS tools, and live impact dashboards show how digital citizen science can produce professional-grade data while cultivating environmental agency and inclusion. These findings directly address this panel’s call to measure the “intangible” outcomes of participation—demonstrating how citizen science converts climate anxiety into agency and connects global citizens to the landscapes they help restore.

https://digventures.com/projects/deep-time/