Assessment of bioenergy potential in Sicily: A GIS-based support methodology

Beccali, Marco; Columba, Pietro; D’Alberti, Vincenzo; Franzitta, Vincenzo

doi:10.1016/j.biombioe.2008.04.019

Cited by 94 publications

(39 citation statements)

References 8 publications

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“…The biomass potential can be further divided into the theoretical total biomass potential, which is an estimate of the standing biomass based on calculation or measurement of the net primary productivity of a biome [51], and the technical biomass potential that is subject to the available technology (harvest, collection, amount of residues, etc.) [52,53]. On the other hand, deterministic crop growth models aim at estimating the total biomass amount as function of several abiotic factors (weather, soil type), farm management (soil tillage, planting density, sowing date, weeding intensity, fertilizer rates, crop protection against pests and diseases, harvest techniques, post-harvest losses, degree of mechanization), land development (field size, terracing, drainage, irrigation) and socio-economic drivers [54][55][56][57].…”

Section: Discussionmentioning

confidence: 99%

Retrieving the Bioenergy Potential from Maize Crops Using Hyperspectral Remote Sensing

Udelhoven

Delfosse²,

Bossung

et al. 2013

Remote Sensing

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Biogas production from energy crops by anaerobic digestion is becoming increasingly important. The amount of biogas that can be produced per unit of biomass is referred to as the biomethane potential (BMP). For energy crops, the BMP varies among varieties and with crop state during the vegetation period. Traditional ways of analytical BMP determination are based on fermentation trials and require a minimum of 30 days. Here, we present a faster method for BMP retrievals using near infrared spectroscopy and partial least square regression (PLSR). PLSR prediction models were developed based on two different sets of spectral reflectance data: (i) laboratory spectra of silage samples and (ii) airborne imaging spectra (HyMap) of maize canopies under field (in situ) conditions. Biomass was sampled from 35 plots covering different maize varieties and the BMP was determined as BMP per mass (BMP FM , Nm 3 biogas/t fresh matter (Nm 3 /t FM)) and BMP per area (BMP area , Nm 3 biogas/ha (Nm 3 /ha)). We found that BMP FM significantly differs among maize varieties; it could be well retrieved from silage samples in the laboratory approach (R cv 2 = 0.82, n = 35), especially at levels >190 Nm 3 /t. In the in situ approach PLSR prediction quality declined (R cv 2 = 0.50, n = 20). BMP area , on the other hand, was found to be strongly correlated with total biomass, but could not be satisfactorily predicted using airborne HyMap imaging data and PLSR.

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Section: Discussionmentioning

confidence: 99%

Retrieving the Bioenergy Potential from Maize Crops Using Hyperspectral Remote Sensing

Udelhoven

Delfosse²,

Bossung

et al. 2013

Remote Sensing

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“…Esto permitiría plantear un escenario de viabilidad económica en un proyecto de suministro energético que considere todos los procesos y acciones en el marco de la gestión territorial. Una aplicación rápida para alcanzar la zonificación de este recurso se puede conseguir integrando los SIG y percepción remota (Beccali et al 2009). Dan constancia de ello, múltiples trabajos efectuados tanto en Europa, África, Asia y en menor grado en Sudamérica, en donde se han identificado a nivel de prospección zonas de aprovechamiento energético, así como superficies y sitios óptimos para la generación de electricidad a base de biomasa forestal residual (Byrne et al 2007, MacFarlane 2008.…”

Section: Introductionunclassified

Zonificación del potencial energético de la biomasa residual forestal en la cuenca del lago Ranco, Chile: Antecedentes para la planificación energética regional

Torres-Álvarez

Peña‒Cortés

2011

Bosque (Valdivia)

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SUMMARYLand planning comprises a stage of land management whose aim is to generate proposals from analyzing the information of the territory, which represents multiple variables of the geographic space. Some of the most recent lines of planning are renewable energies and particularly residual forest biomass since this is a non used environmental element but with a high growth potential. For this task, using technological tools like geographic information systems or remote sensing permits to handle these topics and express them in a spatial zoning for decision making. According to this, a prospective work was made in the watershed of Ranco Lake, where optimum spaces were defined to obtain residual forest biomass in four vegetational units (coigüe-raulí-tepa, roble-raulí-coigüe, evergreen and forest plantations). The results showed that there exists an overall potential surface to handle of 45,555 hectares, from which the forest type coigüe-raulí-tepa highlights with a 62.4 % of the surface. Under the assumption of availability of residual forest biomass in the watershed and a scene of energetic crisis, the importance of prioritizing regional policies and research concerning the development of non conventional renewable energies is recognized.Key words: territorial zoning, GIS and remote sensing, residual forest biomass, NCRE. RESUMENLa planificación territorial constituye una etapa del ordenamiento del territorio que tiene por objeto generar propuestas a partir del análisis de información obtenida de múltiples variables del espacio geográfico. Algunas de las líneas más recientes de planificación la constituyen las energías renovables, y entre éstas la biomasa residual forestal, puesto que constituye un pasivo ambiental no utilizado pero con gran potencial de crecimiento. En esta tarea, el uso de herramientas tecnológicas como el sistema de información geográfica y la percepción remota permiten manejar información territorial asociada a la biomasa residual forestal y expresarla en una zonificación espacial para la toma de decisiones. En este marco, se efectuó un trabajo prospectivo en la cuenca del lago Ranco donde se determinaron los espacios potenciales de extracción de biomasa residual forestal en cuatro unidades de vegetación (coigüe-raulí-tepa, roble-raulí-coigüe, siempreverde y plantaciones forestales) bajo las actuales condiciones de cosecha. Los resultados mostraron que existe una superficie potencial total a manejar de 45.555 ha, de éstas el tipo forestal coigüe-raulí-tepa, con 62,4 % de la superficie, representó la mayor proporción. Bajo el supuesto de la actual disponibilidad de biomasa residual forestal en la cuenca y un escenario de crisis energético, se reconoce la importancia de priorizar las políticas regionales y la investigación en torno al desarrollo del sector de las energías renovables no convencionales.Palabras clave: zonificación territorial, SIG y percepción remota, biomasa residual forestal, energías renovables no convencionales. BOSQUE 32(1): 77-84, 2011 77 INTRODUCCIÓN La planificació...

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“…To begin ensuring long term feedstock availability and sustainability, it is important to gain an understanding of the spatial distribution of the current feedstock, its location relative to the road network for harvesting accessibility, general land ownership, and changes in land use/cover patterns with reference to natural or undisturbed condition. The use of GIS facilitates incorporation of disparate spatial datasets in bioenergy feasibility and feedstock production assessment, including agricultural, economic, biophysical, and infrastructural data [21][22][23] to determine feedstock land availability and estimate biomass for energy production [24,25]. Furthermore, GIS-based decision support tools have been developed to evaluate the transportation cost of energy crop feedstock and associated environmental implications [26][27][28][29][30][31], which are crtical for bioenergy production planning.…”

Section: Introductionmentioning

confidence: 99%

Assessing Site Availability of Aspen and Northern Hardwoods for Potential Feedstock Development in Michigan: A Case Study

Alian¹,

Maclean²

2015

Land

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Abstract:The importance of wood and wood byproducts as biomass feedstocks is of increasing interest as a source of ethanol and electricity. Second generation woody feedstock sources in Michigan, e.g., hybrid poplar and hybrid willow (Populus spp.), and native forests, particularly aspen and northern hardwoods, are a potential source of woody biomass for these uses. This study provides a geographic information system (GIS) framework for assessing the current spatial extent of aspen and northern hardwoods) and their proximity to roads. Additionally, the potential for expanding the area of these feedstock sources based on pre-European settlement vegetation cover is assessed. Utilizing GIS technology to compile, edit and analyze available geospatial data (e.g., present day and pre-European settlement land use/cover, soils, road infrastructure, and land ownership) for counties located in the eastern half of the Upper Peninsula and northern half of the Lower Peninsula of Michigan provides a robust framework for various management scenarios to be evaluated in a cost effective manner and foster better decision making.

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Assessment of bioenergy potential in Sicily: A GIS-based support methodology

Cited by 94 publications

References 8 publications

Retrieving the Bioenergy Potential from Maize Crops Using Hyperspectral Remote Sensing

Retrieving the Bioenergy Potential from Maize Crops Using Hyperspectral Remote Sensing

Zonificación del potencial energético de la biomasa residual forestal en la cuenca del lago Ranco, Chile: Antecedentes para la planificación energética regional

Assessing Site Availability of Aspen and Northern Hardwoods for Potential Feedstock Development in Michigan: A Case Study

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