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GeoJournal

, Volume 78, Issue 5, pp 833–850 | Cite as

Mapping and spatial analysis of the soybean agricultural frontier in Mato Grosso, Brazil, using remote sensing data

  • Damien ArvorEmail author
  • Vincent Dubreuil
  • Margareth Simões
  • Agnès Bégué
Article

Abstract

The main pioneer frontier considered by geographers is the Amazonian pioneer frontier. The occupation of the Brazilian territory has been carried out through successive economic cycles. Currently, the expansion of soybean crops in Amazonia is considered as the last economic cycle involving new migrations to still unexplored areas. Mapping this frontier is necessary in order to better understand its drivers and think about efficient land use policies to struggle its progress. In this paper, we propose an innovative methodology for mapping the agricultural frontier in the Amazonian state of Mato Grosso (Brazil) using satellite data acquired during the 2000–2006 period. We assume that the frontier evolves through successive land-use stages such as wildlands, non-croplands, extensive croplands and intensive croplands areas. The transitions between two stages can then be monitored through land-use change analysis. A particular emphasis is given on three land-use transitions named “deforestation”, “economic” and “intensification sub-frontiers”. In order to adapt this model for the use of remote sensing data, we defined (1) a relevant spatial scale corresponding to an agrarian locality, (2) relevant indices to qualify the land-use types and (3) rules applied on land-use types to define the frontier’s location. Our results highlight the dynamic of the agricultural frontier towards northern areas. We identified four main agricultural regions with different levels of agricultural intensification. We finally discuss these results with respect to governmental policies and economics for a better understanding of the frontier’s dynamic.

Keywords

Amazonia Agricultural frontier Remote sensing Crop expansion Agricultural intensification Deforestation 

Notes

Acknowledgments

The authors wish to thank the French Ministry for Research and Higher Education, which funded a PhD fellowship, the Agence Nationale de la Recherche (DURAMAZ-ANR-06-BLAN-0176), the CNPq-Conselho Nacional de Desenvolvimento Científico e Tecnológico-National Council of Technological and Scientific Development (CNPq CT-Agro grant N. 520268/2005-9), the Institut National de Recherche en Informatique et en Automatique (INRIA) (ENVIAIR grant CNPq/INRIA 490089/2005-4), the Inter-American Institute for Global Change Research (grant CRN II 2031), the US National Science Foundation (Grant GEO-0452325) and the International Development Research Centre (IDRC) (grant # 104358).

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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Damien Arvor
    • 1
    Email author
  • Vincent Dubreuil
    • 2
  • Margareth Simões
    • 3
    • 4
  • Agnès Bégué
    • 5
  1. 1.UMR ESPACE-DEV 228IRDMontpellier Cedex 5France
  2. 2.COSTEL UMR 6554 CNRS-LETGUniversité Rennes 2RennesFrance
  3. 3.ProgramaLabEx EuropeEmbrapaMontpellierFrance
  4. 4.Departamento de Engenharia de Sistemas e Computação – Programa de Pos Graduação em Meio Ambiente (PPGMA)Universidade do Estado do Rio de Janeiro –UERJRio de JaneiroBrazil
  5. 5.UMR TETISCIRADMontpellier Cedex 5France

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