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Importance of Input Classification to Graph Automata Simulations of Forest Cover Change in the Peruvian Amazon

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Reforesting Landscapes

Part of the book series: Landscape Series ((LAEC,volume 10))

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Abstract

The forests of the Amazon arguably represent the single-most reported upon ecosystem globally, with the “Arc of Deforestation” having captured scientific and popular attention. Critiques establishing deforestation as a myth present evidence of an incomplete if not erroneous assessment of forest processes as interacting within larger institutional and climatic systems. As remote assessments of deforestation or reforestation may be strongly dependent upon the seasonality of input images, this work brackets the potential range of forest-change findings by running graph automata simulations while varying forest cover inputs. Results confirm that model results are quite sensitive to input amounts of forest cover as small as those detected even in one intra-annual cycle previously. These findings are interpreted in light of the seasonality of previous work throughout the Amazon and suggest that the overestimation of deforestation may be systematically underestimating reforestation processes at work in the Amazon.

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Acknowledgments

Authors are grateful to collaborating team members Sahotra Sarkar for his help in the original formulation of the mathematical framework of the graph automata, Christopher D. Kelley for programming assistance, and Kenneth R. Young for overall field and project analysis and for the chapter photograph. Field assistance and classification work was aided by Amy L. McCleary and Mario Cardozo. This work was supported in part by a National Science Foundation Small Grant for Exploratory Research (SGER) and Doctoral Dissertation Improvement Grant BCS – 0623229 as well as by the GIScience Center at the University of Texas at Austin.

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Authors and Affiliations

  1. Department of Geography and the Environment, The University of Texas at Austin, Austin, TX, USA

    Kelley A. Crews

  2. Pritzker School of Medicine, The University of Chicago, Chicago, IL, USA

    Alexander Moffett

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  1. Kelley A. Crews
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  2. Alexander Moffett
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Correspondence to Kelley A. Crews .

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Editors and Affiliations

  1. Ecology & the Environment (ATREE), Ashoka Trust for Research in, Royal Enclave, Srirampura, Bangalore, 560064, India

    Harini Nagendra

  2. Dept. Geography, University of Florida, Turlington Hall 3141, Gainesville, 32611-7315, U.S.A.

    Jane Southworth

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Crews, K.A., Moffett, A. (2009). Importance of Input Classification to Graph Automata Simulations of Forest Cover Change in the Peruvian Amazon. In: Nagendra, H., Southworth, J. (eds) Reforesting Landscapes. Landscape Series, vol 10. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9656-3_9

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