2017•Unpublished venueOpen access

Monitoring deforestation and forest degradation using multi-temporal fraction images derived from Landsat sensor data in the Brazilian Amazon

Yosio Edemir Shimabukuro, Egídio Arai, Erone Ghizoni Santos, Jorge Anderson

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Abstract

This work presents a semi-automated procedure for monitoring deforestation and forest degradation in the Brazilian Amazon using a multi-temporal dataset of satellite imagery. Degradation in forest cover in the Brazilian Amazon region is mainly due to selective logging of intact/un-managed forests and to uncontrolled fires. For this study, part of a Landsat TM scene located in the State of Mato Grosso, in the “deforestation arc” of the Brazilian Amazon was selected. Landsat TM images acquired in years 2005, 2006, 2007, 2008, 2009, 2010 and 2011 and one RapidEye image acquired in 2013 was used in this study. The proposed approach can be used for monitoring deforestation and forest degradation activities by selective logging and fires. The current availability of high spatial resolution data such as Sentinel-2 is expected to allow improving the assessment of deforestation and forest degradation processes using the proposed method and, consequently, facilitating the implementation of actions of forest protection.

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This work presents a semi-automated procedure for monitoring deforestation and forest degradation in the Brazilian Amazon using a multi-temporal dataset of satellite imagery. Degradation in forest cover in the Brazilian Amazon region is mainly due to selective logging of intact/un-managed forests and to uncontrolled fires. For this study, part of a Landsat TM scene located in the State of Mato Grosso, in the “deforestation arc” of the Brazilian Amazon was selected. Landsat TM images acquired in years 2005, 2006, 2007, 2008, 2009, 2010 and 2011 and one RapidEye image acquired in 2013 was used in this study. The proposed approach can be used for monitoring deforestation and forest degradation activities by selective logging and fires. The current availability of high spatial resolution data such as Sentinel-2 is expected to allow improving the assessment of deforestation and forest degradation processes using the proposed method and, consequently, facilitating the implementation of actions of forest protection.

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Available abstract

This work presents a semi-automated procedure for monitoring deforestation and forest degradation in the Brazilian Amazon using a multi-temporal dataset of satellite imagery. Degradation in forest cover in the Brazilian Amazon region is mainly due to selective logging of intact/un-managed forests and to uncontrolled fires. For this study, part of a Landsat TM scene located in the State of Mato Grosso, in the “deforestation arc” of the Brazilian Amazon was selected. Landsat TM images acquired in years 2005, 2006, 2007, 2008, 2009, 2010 and 2011 and one RapidEye image acquired in 2013 was used in this study. The proposed approach can be used for monitoring deforestation and forest degradation activities by selective logging and fires. The current availability of high spatial resolution data such as Sentinel-2 is expected to allow improving the assessment of deforestation and forest degradation processes using the proposed method and, consequently, facilitating the implementation of actions of forest protection.

Key concepts: Amazon rainforest, Forest degradation, Deforestation (computer science), Logging, Remote sensing, Environmental science, Satellite imagery, Vegetation (pathology)

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