Geointelligence against Illegal Deforestation and Timber Laundering in the Brazilian Amazon

Due to the characteristics of the Southern Amazonas Mesoregion (Mesorregiao Sul do Amazonas, MSA), conducting on-site surveys in all licensed forestry areas (Plano de Manejo Florestal, PMFS) is an impossible task. Therefore, the present investigation aimed to: (i) analyze the use of geointelligence (GEOINT) techniques to support the evaluation of PMFS; and (ii) verify if the PMFS located in the MSA are being executed in accordance with Brazilian legislation. A set of twenty-two evaluation criteria were established. These were initially applied to a “standard” PMFS and subsequently replicated to a larger area of 83 PMFS, located in the MSA. GEOINT allowed for a better understanding of each PMFS, identifying illegal forestry activities and evidence of timber laundering. Among these results, we highlight the following evidences: (i) inconsistencies related to total transport time and prices declared to the authorities (48% of PMFS); (ii) volumetric information incompatible with official forest inventories and/or not conforming with Benford’s law (37% of PMFS); (iii) signs of exploitation outside the authorized polygon limits (35% PMFS) and signs of clear-cutting (29% of PMFS); (iv) no signs of infrastructure compatible with licensed forestry (17% of PMFS); and (v) signs of exploitation prior to the licensing (13% of PMFS) and after the expiration of licensing (3%).

[1]  C. Souza,et al.  An alternative approach for detecting and monitoring selectively logged forests in the Amazon , 2000 .

[2]  Silvia Castro Marcelino A contribuição da biblioteca para a construção e difusão do conhecimento no Instituto Nacional de Pesquisas Espaciais (Inpe) , 2009 .

[3]  T. Stone,et al.  Using multi-temporal satellite data to evaluate selective logging in Para, Brazil , 1998 .

[4]  G. Asner Biophysical and Biochemical Sources of Variability in Canopy Reflectance , 1998 .

[5]  F. Mendonça,et al.  A pluviosidade na Amazônia meridional: variabilidade e teleconexões extra-regionais , 2016 .

[6]  P. Brancalion,et al.  Fake legal logging in the Brazilian Amazon , 2018, Science Advances.

[7]  Marconde Carvalho de Noronha,et al.  Desflorestamento no sul do Amazonas: embate entre o desenvolvimento econômico e a conservação ambiental , 2016 .

[8]  Simon Newcomb,et al.  Note on the Frequency of Use of the Different Digits in Natural Numbers , 1881 .

[9]  Larry Kahaner,et al.  Competitive Intelligence: How to Gather Analyze and Use Information to Move Your Business to the Top , 1996 .

[10]  E. R. Pinagé,et al.  Detecção da Infraestrutura para Exploração Florestal em Rondônia Utilizando Dados de Sensoriamento Remoto , 2015 .

[11]  M. Keller,et al.  Selective Logging in the Brazilian Amazon , 2005, Science.

[12]  Satya S. Chakravorty,et al.  Testing the accuracy of employee-reported data: An inexpensive alternative approach to traditional methods , 2008, Eur. J. Oper. Res..

[13]  M. Keller,et al.  Remote sensing of selective logging in Amazonia: Assessing limitations based on detailed field observations, Landsat ETM+, and textural analysis , 2002 .

[14]  J. A. Schell,et al.  Monitoring vegetation systems in the great plains with ERTS , 1973 .