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Spatiotemporal dynamics of forest disturbances caused by selective logging in the Brazilian Amazon

University of British Columbia

Selective logging is one of the main causes of forest degradation in the Brazilian Amazon. However, when compared to deforestation, logged forests retain much more biomass and carbon stocks, maintaining important ecosystem services. In several tropical countries selective logging has been promoted as an alternative to the conversion of forests into other land use types. In Brazil, legal logging activities are mainly conducted in privately owned forests, hereafter called forest management units (FMUs). Little is known about the implementation of authorized logging in these areas. This thesis had the objective of characterizing selective logging activities in FMUs located in a focused area within the Brazilian State of Amazonas. The performance of two satellites, Landsat 8 and Sentinel-2, for mapping selective logging were compared. A robust change detection approach was applied for imagery of both satellites. Based on these analyses, Sentinel-2 was chosen as input data set for a spatial pattern analysis. Landscape metrics were computed over multiple scales and then combined into a single map, with five classes of disturbances. Then, this map was used to produce a forest disturbance intensity score. Different weights, meant to account for the heterogeneity associated with harvest operations, were assigned for each disturbance class to score and rank FMUs. Both satellites showed the same performance in terms of accuracy. However, due to its larger spatial resolution, Landsat 8 overestimated the area of logging compared to Sentinel-2. Therefore, Sentinel-2 data was chosen for all further analyses. The five disturbance intensity classes showed a good association with real disturbances. The ranking system, compared to a traditional disturbance indicator, showed very different results for FMUs with intermediate disturbance scores. The most disturbed and the least disturbed areas kept the same position wherever weighting system was assigned. This thesis presents important results towards a better understanding of the spatiotemporal patterns of logging related disturbances in tropical forests. The methodology developed here is simple but robust, it is transparent and easy to be reproduced. The mapping scheme, the spatial pattern analysis and the score system can be used by institutions concerned with the monitoring of tropical forests.

Text

2019-08-29

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/71523

Forestry

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/