Accuracy Assessment and Uncertainty in Baseline Projections for Land-Use Change Forestry Projects
Louis Paladino 1 and R Gil Pontius, Jr. 2
1 Research Scientist
685 Centre Street #207
Jamaica Plain, MA 02130
Clark University, Graduate School of Geography
Department of International Development, Community and Environment
950 Main Street, Worcester MA 01610-1477, USA
This paper uses state-of-the-art validation techniques to estimate uncertainty in the prediction of future disturbance on a landscape. Interpreted satellite imagery from 1975 to 1992 was used to calibrate the land change model. Data from 1992 to 2000 was used to assess the goodness-of-fit of validation as measured by the statistic Kappa for Location (Klocation), which is a variant of the traditional Kappa index of agreement. Based on the goodness-of-fit in the year 2000, Klocation is extrapolated to predict the goodness-of-fit for the year 2026. The extrapolation of Klocation allows the scientist to predict the model’s accuracy with regard to the location of future disturbance. Based on the extrapolated Klocation, the scientist can estimate the conditional probability that a location will be disturbed in the future, given that the model says it will be disturbed. For the validation year of 2000, Klocation is 0.22, which means that the model is 22% of the way between random and perfect in predicting the location of disturbed land versus undisturbed land. The predicted Klocation in the year 2026 is 0.008. Therefore, the estimated probability that a pixel will be disturbed in 2026, given that the model says it will be disturbed is 1.8%. The probability that a pixel will be disturbed given that the model says it will be undisturbed is 1.0%. The results allow us to understand the uncertainty when using models for land-use change forestry project baseline estimates. In this example, the uncertainty is very high, which means that either models need to dramatically improve or carbon trading and Kyoto Protocol policy needs to be reevaluated.
Keywords: carbon, Kappa, land use/land cover change, model prediction, validation.
In: McRoberts, R. et al. (eds). Proceedings of the joint meeting of The 6th International Symposium On Spatial Accuracy Assessment In Natural Resources and Environmental Sciences and The 15th Annual Conference of The International Environmetrics Society, June 28 – July 1 2004, Portland, Maine, USA.