Abstract
Sustainable development strategy promotes activities related to clean energy and energy saving. In this context, actions in forest and agricultural areas which add value to immediate productions and positive externalities are prioritized. The use of agricultural waste is often not viable due to high costs of harvesting and transport operations. In order to consider biomass as an agro forestry sustainable resource to produce biofuels, a high-level system based on the operational concept of the Biofuels Supply Chain sets the basis for a strategic framework which helps to overcome such sustainability. This chapter presents advanced techniques applied by the authors for the detection and quantification of biomass (LiDAR and multispectral images). From these results, logistic models are developed for determining the optimal collection points, managing the best transportation routes and deciding on the desirable location of the processing industries.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ahokas E, Kaartinen H, Hyyppa J (2003) A quality assessment of airborne laser scanner data. In: Proceedings of ISPRS working group III/3 workshop on 3-D reconstruction from airborne laser scanner and InSAR data. Dresden
Annevelink E, de Mol RM (2007) Biomass logistics. 15th European biomass conference, Berlin, Germany
Asrar G, Fuchus M, Kanemasu ET, Hatfield JL (1984) Estimation absorbed photosynthetic radiation and leaf area index from spectral reflectance in wheat. Agron J 76:300–306
Baltsavias EP (1999) A comparison between photogrammetry and laser scanning: existing systems and firms and other resources. ISPRS J Photogramm Remote Sens 54(2–3):83–94
Callejón-Ferre AJ, Velázquez-Martí B, Lopez-Martinez JA, Manzano-Agugliaro F (2011) Greenhouse crop residues: energy potential and models for prediction of their higher heating value. Renew Sustain Energy Rev 15:948–955
Chen J, Pan JC, Lin C (2008) A hybrid genetic algorithm for the re-entrant flow-shop scheduling problem. Expert Syst Appl 34(1):570–577
Cobby DM, Mason DC, Davenport IJ (2001) Image processing of airborne scanning laser altimetry data for improved river flood modelling. ISPRS J Photogramm Remote Sens 56(2):121–138
Davis L (1985) Job shop scheduling with genetic algorithms, pp 136–140
Donoghue DNM, Watt PJ, Cox NJ, Wilson J (2007) Remote sensing of species mixtures in conifer plantations using LiDAR height and intensity data. Remote Sens Environ 110(4):509–522
Estornell J, Ruiz LA, Velázquez-Martí B, Hermosilla T (2010) Analysis of the factors affecting LiDAR DTM accuracy in a steep shrub area. Int J Digit Earth. doi:10.1080/17538947.2010.533201
Estornell J, Ruiz LA, Velazquez-Marti B (2011) Study of shrub cover and height using LiDAR data in a Mediterranean area. For Sci 57(4):171–179
Fensholt R, Sandholt I, Rasmussen MS (2004) Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements. Remote Sens Environ 91:490–507
Forzieri G, Guarnieri L, Vivoni ER, Castelli F, Preti F (2009) Multiple attribute decision making for individual tree detection using high-resolution laser scanning. Forest Ecol Manage 258:2501–2510
García M, Riaño D, Chuvieco E, Danson FM (2010) Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data. Remote Sens Environ 114(4):816–830
Garey MR, Johnson DS (1979) Computers and intractability: a guide to the theory of NP-completeness. W. H. Freeman & Company, Nueva York
Hermosilla T, Ruiz LA, Recio JA, Estornell J (2011) Evaluation of automatic building detection approaches combining high resolution images and LiDAR data. Remote Sens 3:1188–1210
Hollaus M, Wagner W, Eberhöfer C, Karel W (2006) Accuracy of large-scale canopy heights derived from LiDAR data under operational constraints in a complex alpine environment. ISPRS j photogramm remote sens 60(5):323–338
Hopkinson C, Chasmer LE, Sass G, Creed IF, Sitar M, Kalbfleisch W, Treitz P (2005) Vegetation class dependent errors in LiDAR ground elevation and canopy height estimates in a boreal wetland environment. Can J Remote Sens 31(2):191–206
Hyyppä J, Kelle O, Lehikoinen M, Inkinen M (2001) A segmentation-based method to retrieve stem volume estimates from 3-d tree height models produced by laser scanners. IEEE Trans Geosci Remote Sens 39(5):969–975
Hyyppä J, Hyyppä H, Leckie D, Gougeon F, Yu X, Maltamo M (2008) Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests. Int J Remote Sens 29(5):1339–1366
Markevičius A, Katinas V, Perednis E, Tamašauskienė M (2010) Trends and sustainability criteria of the production and use of liquid biofuels. Renew Sustain Energy Rev 14(9):3226–3231
Martin O, Otto SW, Felten EW (1991) Large-step markov chains for the travelling salesman problem. Complex Syst 5(3):299–326
Meng X, Currit N, Zhao K (2010) Ground filtering algorithms for airborne LiDAR data: a review of critical issues. Remote Sens 2(3):833–860
Myneni RB, Hall FG, Sellers PJ, Marshak AL (1995) The interpretation of spectral vegetation indexes. IEEE Trans Geosci Remote Sens 33:481–486
Næsset E (1997) Determination of mean tree height of forest stands using airborne laser scanner data. ISPRS J Photogramm Remote Sens 52(2):49–56
Nelson R, Short A, Valenti M (2004) Measuring biomass and carbon in delaware using an airborne profiling LiDAR. Scand J For Res 19(6):500–511
Pascual C, García-Abril A, García-Montero LG, Martín-Fernández S, Cohen WB (2008) Object-based semi-automatic approach for forest structure characterization using LiDAR data in heterogeneous Pinus sylvestris stands. For Ecol Manage 255(11):3677–3685
Paruelo JM, Garbulsky MF, Guerschman JP, Jobbágy EG (2004) Two decades of NDVI in South America: identifying the imprint of global changes. Int J Remote Sens 25:2793–2806
Popescu SC (2007) Estimating biomass of individual pine trees using airborne LiDAR. Biomass Bioenergy 31(9):646–655
Priestnall G, Jaafar J, Duncan A (2000) Extracting urban features from LiDAR digital surface models. Comput Environ Urban Syst 24(2):65–78
Qi J, Chehbouni A, Huete AR, Kerr YH, Sorooshian S (1994) A modified soil adjusted vegetation index. Remote Sens Environ 48(2):119–126
Reutebuch SE, Andersen H-E, McGaughey RJ (2005) Light detection and ranging (LiDAR): an emerging tool for multiple resource inventory. J For 103(6):286–292
Ripple WJ (1985) Asymptotic reflectance characteristics of grass vegetation. Photogramm Eng Remote Sens 43:1915–1921
Shrestha R, Carter W, Slatton K, Luzum B, Sartori M (2005) Airborne laser swath mapping: quantifying changes in sandy beaches over time scales of weeks to years. ISPRS J Photogramm Remote Sens 59(4):222–232
Sithole G, Vosselman G (2004) Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds. ISPRS J Photogramm Remote Sens 59(1–2):85–101
Velázquez-Martí B (2006) Aprovechamiento de los residuos forestales para uso energético. Ed UPV. ISBN: 97-8848-363049-5. Ed. UPV. Ref. 2006.799
Velázquez-Martí B, Annevelink E (2009) GIS application to define biomass collection points as sources for linear programming of delivery networks. Trans ASABE 52(4):1069–1078
Velázquez-Martí B, Fernandez-Gonzalez E (2009a) Analysis of the process of biomass harvesting with collecting-chippers fed by pick up headers in plantations of olive trees. Biosyst Eng 52(4):225–236
Velázquez-Martí B, Fernández-González E (2009b) Evaluation of mechanized methods for harvesting residual biomass from Mediterranean fruit tree cultivations. Conference LAND.TECHNIK VDI-AgEng 2009 “Innovations to meet future challenges” Hannover, 6–7 Nov 2009
Velázquez-Martí B, Fernandez-Gonzalez E (2010a) Mathematical algorithms to locate factories to transform biomass in bioenergy focused on logistic network construction. Renew Energy 35(9):2136–2142
Velázquez-Martí B, Fernandez-Gonzalez E (2010b) The influence of mechanical pruning in cost reduction, production of fruit and biomass waste in citrus orchards. Appl Eng Agric 26(4):531–540
Velázquez-Martí B, Fernández-González E, Estornell J, Ruiz LA (2010) Dendrometric and dasometric analysis of the bushy biomass in Mediterranean forests. For Ecol Manage 259:875–882
Velázquez-Martí B, Fernández-González E, López-Cortes I, Salazar-Fernández DM (2011a) Quantification of the residual biomass obtained from pruning of trees in Mediterranean almond groves. Renew Energy 36:621–626
Velázquez-Martí B, Fernández-González E, López-Cortes I, Salazar-Hernández DM (2011b) Quantification of the residual biomass obtained from pruning of trees in Mediterranean olive groves. Biomass Bioenergy 35(2):3208–3217
Velázquez-Martí B, Fernández-González E, López-Cortes I, Salazar-Hernández DM (2011c) Quantification of the residual biomass obtained from pruning of vineyards in Mediterranean area. Biomass Bioenergy 35(3):3453–3464
Wang C And, Lu J (2010) An effective evolutionary algorithm for the parctical capacited vehicle routing problems. J Intell Manuf 21:363–375
Zheng D, Rademacher J, Chen J, Crow T, Bresee M, Le Moine J, Ryu S-R (2004) Estimating aboveground biomass using Landsat 7 ETM + data across a managed landscape in Northern Wisconsin. USA. Remote Sens Environ 93(3):402–411
Acknowledgments
The techniques shown in this chapter were developed by the project AGL2007-62328 funded by the Ministry of Education and Science of Spain, and FEDER funds.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Velázquez-Martí, B., Gracia, C., Estornell, J. (2012). Logistic Models to Ensure Residual Agroforestry Biomass as a Sustainable Resource. In: Golinska, P., Romano, C. (eds) Environmental Issues in Supply Chain Management. EcoProduction. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23562-7_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-23562-7_10
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23561-0
Online ISBN: 978-3-642-23562-7
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)