Valuing map validation: the need for rigorous land cover map accuracy assessment in economic valuations of ecosystem services

Foody, Giles M.

Abstract

Valuations of ecosystem services often use data on land cover class areal extent. Area estimates from land cover maps may be biased by misclassification error resulting in flawed assessments and inaccurate valuations. Adjustment for misclassification error is possible for maps subjected to a rigorous validation program including an accuracy assessment. Unfortunately, validation is rare and/or poorly undertaken as often not regarded as a high priority. The benefit of map validation and hence its value is indicated with two maps. The International Geosphere Biosphere Programme’s DISCover map was used to estimate wetland value globally. The latter changed from US$1.92 trillion yr-1 to US$2.79 trillion yr-1 when adjusted for misclassification bias. For the conterminous USA, ecosystem services value based on six land cover classes from the National Land Cover Database (2006) changed from US$1118 billion yr-1 to US$600 billion yr-1 after adjustment for misclassification bias. The effect of error-adjustment on the valuations indicates the value of map validation to rigorous evidence-based science and policy work in relation to aspects of natural capital. The benefit arising from validation was orders of magnitude larger than mapping costs and it is argued that validation should be a high priority in mapping programs and inform valuations.

Citation

Foody, G. M. (2015). Valuing map validation: the need for rigorous land cover map accuracy assessment in economic valuations of ecosystem services. Ecological Economics, 111(March), https://doi.org/10.1016/j.ecolecon.2015.01.003

• Journal Article Type: Article
• Acceptance Date: Jan 12, 2015
• Online Publication Date: Jan 22, 2015
• Publication Date: Mar 1, 2015
• Deposit Date: May 22, 2015
• Publicly Available Date: May 22, 2015
• Journal: Ecological Economics
• Print ISSN: 0921-8009
• Electronic ISSN: 0921-8009
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 111
• Issue: March
• DOI: https://doi.org/10.1016/j.ecolecon.2015.01.003
• Keywords: Remote sensing, Map accuracy, Misclassification bias, Valuation error
• Public URL: https://nottingham-repository.worktribe.com/output/743981
• Publisher URL: http://www.sciencedirect.com/science/article/pii/S0921800915000166