Accuracy for Carbon: Visualizing and Financializing Forest Life

• In Event: Platform Practices and Predictive Seeing 1

Abstract

In 2011, following attempts to pursue growth in a ‘low-carbon economy’, Indonesia’s Ministry of Forestry and Ministry of Environment compared maps of primary forests to calculate areas eligible for a carbon financing scheme. The maps showed forest boundaries that did not match, stirring uncertainty about the accuracy of earth observatory systems and mapping technologies in Indonesia. Repeated accusations of inaccuracy prompted President Joko Widodo (2014 –) to implement One Map Policy in 2016, an integrated “super databank for all of Indonesia’s spatial data". The spatial data will be presented in ways that enable carbon investors to track changes of forest cover over time, accompanied by hypothetical scenarios of how forests might increase or decrease according to political and economic shifts. Models of forests’ future states will also enable the difference between a scenario and the observed amount of carbon to be sold and traded on financial platforms. In effect, an accurate map today underpins a plausible carbon trade on the ground, providing information to carbon investors to calculate risk and reward at a distance. But just how is the accuracy of a forest map known, especially one that is patterned to give rise to market action? My paper is an ethnographic study of how maps and attendant visualizations prefigure the development of carbon markets. I ask, what do data visualizations tell us about dominant modes of observation and claims to accuracy? How does what one see and measure become models for such visualizations in their very design and built?

Author

• Cindy Lin, University of Michigan, School of Information