Download Bioenergy from Wood: Sustainable Production in the Tropics by Thomas Seifert PDF

By Thomas Seifert

This publication is written for scientists and practitioners drawn to deepening their wisdom of the sustainable creation of bioenergy from wooden in tropical and sub-tropical nations. making use of the worth chain proposal, this booklet outlines the mandatory points for dealing with sustainable bioenergy creation. quite a lot of issues is roofed together with biomass localization, modelling and upscaling, construction administration in woodlands and plantations, and delivery and logistics. Biomass caliber and conversion pathways are tested with a view to fit the conversion expertise with the to be had biomass. a bit is devoted to concerns surrounding sustainability. the problems, lined in a life-cycle evaluate of the bioenergy method, contain socio-economic demanding situations, neighborhood results on water, biodiversity, nutrient-sustainability and worldwide affects. via this holistic method and helping examples from tropical and sub-tropical international locations, the reader is guided in designing and imposing a price chain because the major administration tool for sustainable wood.

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6 shows a graphical representation of the interaction between object size, in this case a tree canopy, and spatial resolution (pixel size) of some common satellite sensors. , high spatial resolution IKONOS imagery, should ideally be coupled to and scaled with lower spatial resolution sensors, such as the Landsat suite of sensors. This approach effectively enables a tree-to-stand-to-landscape type inventory approach. 2 Localisation of Biomass Potentials 21 Fig. 2 LiDAR Estimates of Stand Parameters Airborne LiDAR sensors are operated using an aircraft-mounted scanning laser altimeter, which emits short burst laser pulses.

Many efforts have been made to assess LiDAR accuracy and precision when it comes to forest inventory, and while most such studies report these values, a couple of efforts or implications deserve special mention: 2 Localisation of Biomass Potentials 23 Duncanson et al. (2010) used an airborne LiDAR dataset in combination with forest inventory data to explore the relationship between their model error and canopy height, aboveground biomass (AGB), stand age, canopy rugosity, mean diameter at breast height (DBH), canopy cover, terrain slope, and dominant species type.

25 % of the study area. The premise of the study was that the transect type sampling scheme would reduce the cost of the LiDAR survey and thus make incorporation of the sensor more cost effective within an operational scenario. , using spectral reflectance and age as predictor variables. While the LiDAR accurately measures tree heights, the RMSE values associated with validation data were outside the acceptable error margins employed in operational scenarios (˙5 %). Over-prediction of tree heights suggested that the proposed methodology was not perfectly attuned to accurate estimation of tree height for areas external to the LiDAR collection framework.

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