Agave production as a bioenergy feedstock: a fuzzy GIS model

Fuzzy GIS model for A. tequilaLewis, S., S. Gross, A. Visel, M. Kelly, and W. Morrow. 2015. Fuzzy GIS-based multi-criteria evaluation for U.S. Agave production as a bioenergy feedstock. Global Change Biology - Bioenergy 7:84–99. doi: 10.1111/gcbb.12116

In the United States, renewable energy mandates calling for increased production of cellulosic biofuels will require a diversity of bioenergy feedstocks to meet growing demands. Within the suite of potential energy crops, plants within the genus Agave promise to be a productive feedstock in hot and arid regions. The potential distributions of Agave tequilana and Agave deserti in the United States were evaluated based on plant growth parameters identified in an extensive literature review. A geospatial suitability model rooted in fuzzy logic was developed that utilized a suite of biophysical criteria to optimize ideal geographic locations for this new crop, and several suitability scenarios were tested for each species. The results of this spatially explicit suitability model suggest that there is potential for Agave to be grown as an energy feedstock in the southwestern region of the United States – particularly in Arizona, California, and Texas – and a significant portion of these areas are proximate to existing transportation infrastructure.

Click to read more ...

in biofuels, gis, lulc, modeling, rangelands

Monday

Mar312014

What is "marginal land"? a review of the ways GIS is used to model (and define) "marginal land" for biofuel production

Monday, March 31, 2014 at 8:20AM

Lewis, S. and M. Kelly. 2014. Mapping the potential for biofuel production on marginal lands: differences in definitions, data and models across scale. International Journal of Geo-Information 3(2), 430-459; doi:10.3390/ijgi3020430

As energy policies mandate increases in bioenergy production, new research supports growing bioenergy feedstocks on marginal lands. Subsequently there has been an increase in published work that uses Geographic Information Systems (GIS) to map the availability of marginal land as a proxy for bioenergy crop potential. However, despite the similarity in stated intent among these works a number of inconsistencies remain across studies that make comparisons and standardization difficult. We reviewed a collection of recent literature that mapped bioenergy potential on marginal lands at varying scales, and found that there is no common working definition of marginal land across all of these works. Specifically we found considerable differences in mapped results that are driven by dissimilarities in definitions, model framework, data inputs, scale and treatment of uncertainty.

Click to read more ...

in biofuels, error, gis, modeling, open access, spatial analysis

Thursday

Mar062014

Mapping potential for switchgrass as a biofuel in the US

Thursday, March 6, 2014 at 8:19PM

One model outcome from the analysis.Lewis, S.M., G. Fitts, M. Kelly, L. Dale. 2014. A fuzzy logic-based spatial suitability model for drought-tolerant switchgrass in the United States. Computers and Electronics in Agriculture 103:39-47

Switchgrass (Panicum virgatum) has been targeted by the U.S. Department of Agriculture as an exemplary bioenergy crop, however it requires a significant amount of water and experiences reduced yields in water-stressed conditions. To avoid competition for prime agricultural areas, lands that receive adequate rainfall but are marginal due to highly variable timing of rain are potentially ideal locations to grow drought-tolerant biofuels. As scientists develop a modified variety of switchgrass that can withstand periods of drought while not substantially affecting overall yield, it is important to identify the potential geographical niche for this xerophytic crop to maximize its environmental and economic sustainability. This project uses a spatial suitability modeling approach that incorporates fuzzy logic and utilizes both physical and economic variables.

Click to read more ...

in biofuels, gis, modeling

What is "marginal land"? a review of the ways GIS is used to model (and define) "marginal land" for biofuel production

Lewis, S. and M. Kelly. 2014. Mapping the potential for biofuel production on marginal lands: differences in definitions, data and models across scale. International Journal of Geo-Information 3(2), 430-459; doi:10.3390/ijgi3020430

As energy policies mandate increases in bioenergy production, new research supports growing bioenergy feedstocks on marginal lands. Subsequently there has been an increase in published work that uses Geographic Information Systems (GIS) to map the availability of marginal land as a proxy for bioenergy crop potential. However, despite the similarity in stated intent among these works a number of inconsistencies remain across studies that make comparisons and standardization difficult. We reviewed a collection of recent literature that mapped bioenergy potential on marginal lands at varying scales, and found that there is no common working definition of marginal land across all of these works. Specifically we found considerable differences in mapped results that are driven by dissimilarities in definitions, model framework, data inputs, scale and treatment of uncertainty.

Click to read more ...

Mapping potential for switchgrass as a biofuel in the US

One model outcome from the analysis.Lewis, S.M., G. Fitts, M. Kelly, L. Dale. 2014. A fuzzy logic-based spatial suitability model for drought-tolerant switchgrass in the United States. Computers and Electronics in Agriculture 103:39-47

Switchgrass (Panicum virgatum) has been targeted by the U.S. Department of Agriculture as an exemplary bioenergy crop, however it requires a significant amount of water and experiences reduced yields in water-stressed conditions. To avoid competition for prime agricultural areas, lands that receive adequate rainfall but are marginal due to highly variable timing of rain are potentially ideal locations to grow drought-tolerant biofuels. As scientists develop a modified variety of switchgrass that can withstand periods of drought while not substantially affecting overall yield, it is important to identify the potential geographical niche for this xerophytic crop to maximize its environmental and economic sustainability. This project uses a spatial suitability modeling approach that incorporates fuzzy logic and utilizes both physical and economic variables.

Click to read more ...