**4.1. Energy plantations**

many field plots are needed to attain the threshold error [24, 27]; (3) short time cycles can be used for data collection, contrary to forest inventory, where cycles shorter than 5–10 years are unfeasible [24, 26]; (4) different scales can be used as function of imagery spatial resolution [26, 27]; and (5) it applies to all the area, thus extrapolation methods are

The biomass functions that use satellite image data are mathematical functions that use data derived from satellite optical sensors for the explanatory variable [33], such as spectral reflectance, crown diameter, crown horizontal projection, crown cover, original bands and/ or vegetation indices [32, 34–36, 54–58]. The statistical methods and techniques used to fit the functions are varied. Examples are linear and nonlinear regression, regression k-nearest neighbor, neural networks, regression tree, random forest, and support vector machine

For an optical sensor (passive sensor), the spatial resolution is the main distinctive feature of the satellite images and can be grouped in three broad classes: coarse, medium, and high. The *coarse spatial resolution* satellite imagery (>100 m) comprises: National Oceanic and Atmosphere Administration (NOAA) with the Advanced Very High Resolution Radiometer (AVHRR) sensor, Moderate Resolution Imaging Spectroradiometer (MODIS), and Satellite *Pour l'Observation de la Terre* (SPOT) Vegetation [55, 59–62]. The *medium spatial resolution* satellite imagery (10 to 100 m) includes Landsat, Sentinel, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and Wide Field Sensors (WiFS) [55, 63–65], as well as recently Landsat 8 and Sentinel, free global-scale remote sensing data. The *high spatial resolution* satellite imagery consists of: IKONOS, QuickBird, WordView, and GeoEye satellites, with a pixel size smaller than 5 m [33–36, 66, 67].

The active sensors, Radio Detection and Ranging (RADAR) and Light Detection and Ranging (LiDAR), have gained relevance for biomass estimation in the last years [68–72]. The RADAR use microwaves to obtain information of surface target. It has the advantage of data acquisition being independent of the hour of the day and atmospheric conditions. More recently, the synthetic aperture radar (SAR) sensor, C-band RADARSAT-2, and X-band TerraSAR provide more accurate biomass estimation due to the spatial resolution variability, polarization, and incidence angles [73]. LiDAR systems allow to obtain detailed information about the structure of vegetation (horizontal and vertical tree dimension), considering the distances measured to the object surface [74, 75]. It can be supported by spaceborne, airborne, and terrestrial platforms that create a very precise 3D-point cloud data from vegetation [76] and are used to develop models for several vegetation biophysical parameters, such as tree height, crown dimensions, volume, and canopy density [52]. The statistical methods most frequently used to develop biomass functions are linear and multilinear regression [52] and machine learning

Some studies used a combination of LiDAR and multispectral or hyperspectral data to identify the different forest areas where the spectral response is similar, to improve the biomass estimation [77–81]. Related to the satellite spatial resolution is the target area of estimation, which can be at regional or local scales [32, 34–36, 82–86] or national scales [87–90]. However, some difficulties in the estimation of biomass with accuracy may arise due to the variability of

the stands and forests, especially in the tropical forests [91, 92].

[27, 52]. Remote sensing data is derived from passive or active sensors.

not required [32, 34–36].

26 Renewable Resources and Biorefineries

algorithms [70, 71].

Several terms have been used to describe the forest systems whose main, and frequently the only, production is biomass for energy [94, 101, 102] and that are characterized by specific spatial and temporal features [93, 99]. The most important features of these systems, when compared with agricultural crops or other forest systems, are their low risks, high economic viability, harvest flexibility, availability worldwide, biodiversity enhancement (especially if incorporated in agricultural crops portfolio), and the possibility of use for phytoremediation purposes [97, 100, 103–107]. The energy plantations are well represented in Europe, though to a lesser extent in the southern countries [103, 105], USA [108, 109], Canada [110], and China [111]. For the establishment of the energy plantations, the selection of species, density, rotation, harvest cycles, site, and management practices has to be considered.

The *selection of species* is of primordial importance. The species better suited for energy plantations are those that have high biomass production in dry weight, good sprouting ability, fast juvenile growth, narrow crowns or large-sized leaves in the upper crown, biomass with high specific energy and quality, adaptability to a wide range of sites, and resistance to biotic and abiotic agents [100, 112, 113]. Hybrids are frequently used to increase productivity, for their adaptation to the environmental conditions and resistance to pathogens [104, 114, 115]. From the many potential species suited for energy plantations, the three most referred in literature are: *Populus* spp. [101, 111, 112, 115–118], *Salix* spp. [101, 112, 114, 116, 118], and *Eucalyptus* spp. [97, 101, 112, 119, 120].

*Density*, *rotation,* and *harvest cycles* are strictly linked, since the main goal of energy plantations is to attain the highest production in the shortest time (*e.g.*, [104, 116, 117]). Thus, three principles regulate density and rotation; namely the law of final constant yield, the development of social classes in a stand, and self-thinning law [93]. However, there is a large variability of densities from 1000 stems ha−1 to 310,000 stems ha−1 [99, 108, 114, 116, 118, 121, 122] and rotation lengths between 1 and 20 years [99, 108, 114, 116, 118, 121, 122]. Also, a dichotomy seems to exist between density and rotation [101], frequently higher densities and shorter rotations [104, 114, 115, 121, 122], or lower densities and longer rotations [97, 118–120]. Harvest cycles depend on stump mortality and ability to resprout and cutting cycles of 10 to 30 years are indicated in the literature [83, 99, 104, 117].

mainly derived from thinnings and prunings but also from sanitary cuttings or trees that have

Solid Biomass from Forest Trees to Energy: A Review http://dx.doi.org/10.5772/intechopen.79303 29

One of the advantages of biomass over other renewable energy sources is its versatility. Biomass in general, and forest biomass in particular, can be converted into electricity, heat, or transportation fuels. In practice, though, forest biomass is mainly used for heat and electricity production. The transformation of forest biomass into biofuels that can be used in the transport sector still faces various challenges, which have hindered its commercialization [146, 147].

Despite its advantages and despite being the most used renewable energy source, the current share of bioenergy in the world is still very limited. In 2015, bioenergy and renewable wastes accounted for 9.4% of the world's energy supply [2]. Among the various biomass sources, solid biofuels accounted for 63.7% of the global renewables supply (liquid biofuels, biogas, and renewable municipal waste accounted respectively for 4.3, 1.7, and 0.9% and the other renewable energy sources for the rest) [2]. In OECD countries, where biomass is mostly used in modern systems, the share of biomass and renewable wastes is even lower, with these fuels accounting for 5.2% of the total primary energy supply in 2015 and solid biomass accounting

Solid biofuels, which are almost entirely composed of wood, wood residues, and wood fuels, are used to produce electricity and heat. Direct heat is by far the most common application of solid biomass. In this case, biomass is used directly by the end users (*e.g.*, residential, industrial, commercial, agriculture) and not by the energy transformation sector (*e.g.*, power plants, combined heat and power (CHP) plants or heating plants). The dominance of the use of solid biomass for heating applications is mostly justified by its traditional use in the African and

Looking at the situation in Europe, where biomass is mostly used in a modern way, the utilization of solid biomass by the energy transformation sector has a bigger prevalence. Power plants for the production of electricity have a 9% share, CHP plants both for the production of electricity and heat 16% and district heating plants 5% [148]. In total, the European energy transformation sector accounts for 30% of the solid biomass consumption, contrasting with

Biomass for energy uses comes from various sources. Generically, it can be divided into forest, agricultural, and residual biomass. From these three categories, biomass from forestry is by far the most significant source of biomass for energy production. In 2014, it generated more than 87% of the world biomass feedstock, while agriculture contributed with 10% and

reached the end of their lifetime cycle [142, 144, 145].

**5. Uses of forest biomass for energy**

for 36.1% of the renewable energy supply [2].

Asian countries for heating and cooking [1].

the world average, which is around 9%.

municipal solid wastes and landfill gas with 3% [1].

**5.2. Feedstock characterization**

**5.1. Current status**

*Site selection* is directly related to survival, growth, and yield of the tree species or clones. To obtain high productivities, sites should be of good quality with long growing seasons [83, 100, 101], and steep slopes should be avoided when mechanization is foreseen [99, 101, 104]. Control of natural vegetation to reduce competition between spontaneous vegetation and energy plantations is better suited during site preparation [101, 104, 115], though it might also be necessary after each harvest [93, 104, 123].

Two main options are available for the *selection of planting techniques*: plantation of cuttings or seedlings. While the former is use with *Salix* spp. [101, 104, 124–126], the latter is chosen for *Populus* spp. or *Eucalyptus* spp. [101, 124, 126]. Similarly, two approaches are available for management: the plantation with a cut after 1 year in order to promote coppicing or first harvest at the end of the rotation length [93, 104, 121, 122].

Other management practices include fertilization to promote yield [93, 101], though there is some controversy in the literature, with some authors stating that fertilization does not increase yield (*e.g.*, [124, 126, 127]), while others state the opposite (*e.g.*, [128, 129]). The control of pathogens should be primordially done by choosing resistant species or clones or by the increasing diversity (*e.g.*, [101, 130]) and, if this is not enough, with phytopharmaceuticals [93, 98, 101, 115]. Irrigation should be used when water stress and growth reduction are expected [93, 131, 132].
