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Identifying classes of degraded forests in an Amazonian landscape from remote-sensing

Bourgoin C., Baghdadi N., Blanc L., Ferreira J.N., Gond V., Mazzei L., Ozwald Y.. 2015. In : Visconti P. (ed.), Game E. (ed.), Mathevet R. (ed.), Wilkerson M. (ed.). Proceedings of the 27th International Congress for Conservation Biology and 4th European Congress for Conservation Biology " Mission biodiversity: choosing new paths for conservation". Washington : Society for conservation biology, p. 85-85. International Congress for Conservation Biology. 27, 2015-08-02/2015-08-06, Montpellier (France).

ln the Brazilian Amazon, deforestation and forest degradation have resulted in a complex mosaic of forest types. Nearly 20% of the Brazilian Amazonian forests have been cleared. ln this area, abandon ment of fields led to regrowth of secondary forests of varying ages. A fraction of the remaining forested land has also suffered from anthropic degradation (mainly over-logging and fire). Human-modified Amazonian landscapes are therefore an assemblage of these various forests associated with pastures and agricultural lands. These landscapes are now at the centre of political concerns. Coercive measures taken by the Brazilian government to curb deforestation, associated with private initiatives (soy and beef moratoria) drastically reduced deforestation rates. The colonization of the Amazonian territory through agricultural expansion over forest areas is now severely restricted. Consequently, conciliation between agricultural production and environmental conservation should be pursued in all human-impacted forests. However these secondary and degraded forests have not received the necessary attention. While identification and characterization of degraded forests became a critical task, there is an overall limitation in the remote sensing analyses developed so far.To define management plans for these areas and to understand their role in the maintenance of ecological services, the first challenge is to identify and characterize the forests that result from different disturbance trajectories. We carried out a study aiming at classifying the large spectrum of degraded forests into forest classes based on degradation levels using satellite data. The study area took place in the municipality of Paragominas (eastern Amazonia). A large range of captors (optical, radar and lidar) have been tested combining with ground-truth validation. This classification has important applications in ecological studies as well as in supporting decisions for land-use planning.

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