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ISPRS Int. J. Geo-Inf. 2018, 7(4), 156; https://doi.org/10.3390/ijgi7040156

New Geospatial Approaches for Efficiently Mapping Forest Biomass Logistics at High Resolution over Large Areas

1
Rocky Mountain Research Station, U.S. Forest Service, Missoula, MT 59801, USA
2
Department of Forest Engineering, Resources and Management, College of Forestry, Oregon State University, Corvallis, OR 97331, USA
*
Author to whom correspondence should be addressed.
Received: 13 February 2018 / Revised: 13 April 2018 / Accepted: 15 April 2018 / Published: 20 April 2018
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Abstract

Adequate biomass feedstock supply is an important factor in evaluating the financial feasibility of alternative site locations for bioenergy facilities and for maintaining profitability once a facility is built. We used newly developed spatial analysis and logistics software to model the variables influencing feedstock supply and to estimate and map two components of the supply chain for a bioenergy facility: (1) the total biomass stocks available within an economically efficient transportation distance; (2) the cost of logistics to move the required stocks from the forest to the facility. Both biomass stocks and flows have important spatiotemporal dynamics that affect procurement costs and project viability. Though seemingly straightforward, these two components can be difficult to quantify and map accurately in a useful and spatially explicit manner. For an 8 million hectare study area, we used raster-based methods and tools to quantify and visualize these supply metrics at 10 m2 spatial resolution. The methodology and software leverage a novel raster-based least-cost path modeling algorithm that quantifies off-road and on-road transportation and other logistics costs. The results of the case study highlight the efficiency, flexibility, fine resolution, and spatial complexity of model outputs developed for facility siting and procurement planning. View Full-Text
Keywords: biomass; logistics; operations; function modeling; raster analysis biomass; logistics; operations; function modeling; raster analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Hogland, J.; Anderson, N.; Chung, W. New Geospatial Approaches for Efficiently Mapping Forest Biomass Logistics at High Resolution over Large Areas. ISPRS Int. J. Geo-Inf. 2018, 7, 156.

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