By Thomas Seifert
This e-book is written for scientists and practitioners drawn to deepening their wisdom of the sustainable construction of bioenergy from wooden in tropical and sub-tropical international locations. making use of the price chain suggestion, this ebook 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 shipping and logistics. Biomass caliber and conversion pathways are tested which will fit the conversion expertise with the on hand biomass. a piece is devoted to matters surrounding sustainability. the problems, coated in a life-cycle overview of the bioenergy method, comprise socio-economic demanding situations, neighborhood results on water, biodiversity, nutrient-sustainability and worldwide affects. via this holistic strategy and assisting examples from tropical and sub-tropical international locations, the reader is guided in designing and enforcing a cost chain because the major administration device for sustainable wood.
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Additional info for Bioenergy from Wood: Sustainable Production in the Tropics
All of these studies have approached the challenge by subsetting the hyperspectral data to those wavelengths necessary for separation of a specific set of species. In other words, an operational workflow should be preceded by a pilot study: (i) identify the species of interest, (ii) acquire hyperspectral data, (iii) determine which wavelengths are necessary to separate the species on a spectral basis, and (iv) assess the classification accuracy. , we have more data than we need. We therefore need to subset the data to the wavelengths required for a specific application in order to develop statistically robust models, or models with a reasonable number of independent or explanatory variables.
1 Case Study: LiDAR Data The study area was surveyed in November 2006 using an Optech ALTM 3033 LiDAR sensor mounted on a Cessna Caravan 206 aircraft. The sensor operated in the near infrared portion of the electromagnetic spectrum (1,064 nm) and was configured to capture first and last LiDAR returns. 2 mrad. 2 m. 28 m, respectively. Pre-processing was undertaken by the vendor who classified returns into ground and non-ground data sets using Terrasolid TerraScan® . The classification process involved an initial automated classification, with the accuracy influenced by the underlying terrain.
Mach Learn 45(1):5–32 Bundeswaldinventur (2008) The National Forest Inventory. Bundesministerium für Ernährung, Landwirtschaft und Verbraucherschutz. Berlin. html Butson C, King DJ (1999) Semivariance analysis of forest structure and remote sensing data to determine an optimal sample plot size. In: Proceedings of the 4th international airborne remote sensing conference, Ottawa, 21–24 June 1999. Environmental research institute of Michigan, Ann Arbor, vol II, pp 155–162 Cartus O, Santoro M, Schmullius C, Li Z (2011) Large area forest stem volume mapping in the boreal zone using synergy of ERS-1/2 tandem coherence and MODIS vegetation continuous fields.
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