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Function modeling: improved raster analysis through delayed reading and function raster datasets

Year:

2013

Publication type:

Paper (invited, offered, keynote)

Primary Station(s):

Rocky Mountain Research Station

Source:

In: Proceedings of the 36th Annual Meeting of the Council on Forest Engineering; July 8-10, 2013, Missoula, MT. Morgantown, WV: Council on Forest Engineering. Online: http://web1.cnre.vt.edu/forestry/cofe/documents/2013/Hogland_Anderson_Jones.pdf

Description

Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space, often limiting the types of analyses that can be performed. To address this issue, we have developed Function Modeling. Function Modeling is a new modeling framework that streamlines the raster modeling process by utilizing lazy reading methodologies. To assess the efficacy of Function Modeling, we compared the processing time and storage space required to execute six simulation using our newly developed methodology and conventional modeling techniques. Our findings indicate that Function Modeling substantially reduces both processing time and storage space when compared to conventional modeling. Outside of simulations, we have used Function Modeling to characterize the impacts of fuel treatments on soil erosion given fire disturbance, estimate basal area, trees, and tons of above ground biomass per acre, identify locations in need of forest management, calculate forest residuals given multiple management prescriptions, and integrate spatially explicit delivery cost models with forest residual estimates in a fraction of the time and storage space it would take to perform similar analysis using conventional modeling methodologies. Overall, Function Modeling significantly improves how raster models are processed. To facilitate the use of Function Modeling, we built an object oriented .NET library called RMRS Raster Utility. RMRS Raster Utility is free, readily available, has an intuitive user interface, and directly plugs into Environmental Science Research Institute (ESRI)'s software as an ESRI add-in.

Citation

Hogland, John S.; Anderson, Nathaniel M.; Jones, J .Greg. 2013. Function modeling: improved raster analysis through delayed reading and function raster datasets. In: Proceedings of the 36th Annual Meeting of the Council on Forest Engineering; July 8-10, 2013, Missoula, MT. Morgantown, WV: Council on Forest Engineering. Online: http://web1.cnre.vt.edu/forestry/cofe/documents/2013/Hogland_Anderson_Jones.pdf

Publication Notes

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  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
https://www.fs.usda.gov/treesearch/pubs/44804