Remote assessment of extracted volumes and greenhouse gases from tropical timber harvest. (4th June 2018)

• Record Type: Journal Article
• Authors: Pearson, Timothy R H; Bernal, Blanca; Hagen, Stephen C; Walker, Sarah M; Melendy, Lindsay K; Delgado, Grace
• Is Part Of: Environmental research letters. Volume 13:Number 6(2018:Jun.)
• Publication Date: 2018-06-04
• Subjects: tropical forest -- timber harvest -- extraction volume -- remote sensing -- LiDAR -- greenhouse gas emissions; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/aac1fa
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: Timber harvest from tropical regions generates seven billion dollars annually in exports and is estimated to occur across 20% of the area of remaining tropical forests. This timber harvesting is estimated to account for more than one in eight of all greenhouse gas emissions from tropical forests. Yet there is currently no means to independently estimate extracted volumes and associated greenhouse gas emissions. In this study, we built upon an earlier paper that used an automated algorithm applied to LiDAR to accurately identify area of timber harvest impact in the categories of roads/decks, skid trails and gaps. This algorithm was applied to 2014 harvest areas in four concessions in Kalimantan, Indonesia. In two of these concessions, total harvested timber volumes and greenhouse gas emissions were measured and calculated in the field using data from 188 harvested and extracted trees. In order to relate remote sensing data with the estimated extracted volumes, we calculated factors that linked extracted timber volumes with greenhouse gas emissions, and applied three different regression equations. The parameters of the most accurate equation were the areas of roads, skid trails and gaps, explaining 87% of the variation in the data. For situations where rivers are used in place of roads for extracting timber and for instances of non-mechanized, often illegal logging, a second equation was created in which only skid trail and gap attribute data were used, and in this equation 86% of the variation was accounted. The final equation, intended for use in scenarios where LiDAR data are not available but moderate resolution imagery could be used, associated length of roads only with extracted volumes. In this case, 78% of the variation was explained. Application of the first equation permitted estimation of extracted volumes and associated greenhouse gas emissions from two additional logging concessions. We discuss the application of these equations to areas that have been identified as illegal logging concessions, and propose that these may be applied to larger regions across the country. These equations offer a way to estimate volumes of timber extraction when no ground data is available, and to calculate greenhouse gas emissions associated with extracted volumes, providing a simple methodology useful across forested tropical countries.