Abstract

Accurate land use mapping in the Amazon is crucial to support the implementation of environmental policies. The new Brazilian Forest Code published in 2012 defines a “consolidated rural area” (CRA) as an area within a rural property and occupied by humans prior to July 22, 2008. Environmental infractions that occurred before that date are granted amnesty and landowners are exempted from the obligation to restore the degraded areas. To assess the compliance of rural property owners with the environmental legislation, the Brazilian government created the Rural Environmental Registry (CAR), for mandatory electronic self-declaration of all rural private properties. The successful implementation of the CAR relies on the accurate mapping of CRA before the reference date of July 2008. The objective of the present paper is to assess the accuracy of the 2008 map of consolidated rural areas (CRA2008) that is the result of a fruitful collaboration between a non-governmental organization (NGO), a state administration and academic institutions. The CRA2008 map was produced by photo-interpretation of high resolution remote sensing images and validated after comparison with 90 aerial photographs. The validation metrics (overall accuracy = 0.926, Kappa index = 0.851 and F-score = 0.924) confirmed the reliability of the CRA2008 map. Most errors identified were due to imprecision at the edges between CRA and native vegetation because of different spatial resolutions of the CRA2008 and the aerial photographs. Consequently, the results were slightly lower (although still high; Kappa = 0.835) in the Amazon biome where landscapes are more fragmented. Finally, in a context of severe criticisms expressed by national government leaders towards Brazilian research institutions and NGOs, our results clearly demonstrate the benefits of combining institutional efforts and of working in synergy to produce relevant information with the aim of ensuring the implementation of public environmental policies and thereby improving land use sustainability in the Amazon.

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