SPATIO-TEMPORAL DYNAMICS OF PERENNIAL ENERGY CROPS IN THE U.S. MIDWEST AGRICULTURAL LANDS.pdf
Spatio-temporal dynamics of perennial energy crops in the U.S. Midwest agricultural lands Cuizhen (Susan) Wang Associate Professor, Dept. of Geography, University of Missouri E-mail: firstname.lastname@example.org; Tel: 1-573-884-0895 with co-authors Gary Stacey, Center for Sustainable Energy, MU Felix B. Fritschi, Division of Plant Sciences, MUWyatt Thompson, FAPRI, and Dept. of Agricultural/Applied Economics, MU Timothy C. Matisziw, Dept. of Geography, Dept. of Civil/Environmental Engineering, MU Zhengwei Yang, USDA/NASS 1 / 18
Introduction Biomass exceeds 3% of energy supplies and is the largest source of renewable energy in the United States; Upon an optimistic estimate, biomass feedstocks could replace 30% of domestic petroleum consumption by 2030 (Perlack et al. 2005); Corn ethanol currently constitutes 99% of US biofuel (Farrel et al. 2006). The US biofuel refiners budgeted 4.2 billion bushels of corn (1/3 of US corn production) in the 2009-2010 marketing year (Economic Research Service 2010). Environmental Ecological socio-economic concerns 2 / 18
Native prairie grasses are identified by DOE as a model cellulosic crop, an alternative of bioenergy feedstock. Warm-season native grasses currently grow in mixed conditions with cool-season forage grasses, and have not been mapped in any published agricultural databases. Current spatial distributions and temporal dynamics? 3/ (Source: Oak Ridge National Lab)18
Study area and data sets The Midwest agricultural regionValidation sites:Flint Hills, KSThe largest unplowedtallgrass prairie remn.(>80% native grasses).Cherokee Plain, MOSandhills uplandprairie, NE 4 / 18
Satellite imagery and published maps• 500-m, 8-day MODIS surface reflectance products (MOD09A1); - 4 scenes; -NDVI time series (46 scenes/year) - 10-year period (00-09);• Cropland Data Layers (CDL) - USDA NASS - 12 states - 2007• Major crops in the Great Plains - Grass (tall/short/cool-season); - Corn+Soybean; - Winter wheat - Spring wheat 5 / 16
Approach Time series analysis• median filter spikes removal• Savitzky-Golay filter curve smoothing• Asymmetric Gaussian simulation• extracting phenology matrices Source: Jonsson and Eklundh 2004. TIMESAT 6 / 18
Example time series: (Source: Wang et al. 2011) Corn Soybean Winter wheat WSG grass CGS grass 7 / 35 7 / 18
Phenology metrics TIMESAT extracted (3 out of 11): • End of season: when NDVI decrease to 20% of amplitude; • Growing length: number of dates in start-end of seasons; • Cumulative growth (∑NDVI):NDVI integral in start-end of seasons; Self-identified: • peak date: dates of peak NDVI; - Early: peak date falls in DOY 1-161 (Jan – Mid June) - Middle: peak date falls in DOY 145-193 (May - Mid July) - Late: peak date falls in DOY 161-313 (Mid June – Mid Nov) • Summer dry-down (∆NDVI): decrease of NDVI in spring-summer if peak NDVI falls in early stage (especially useful for winter wheat); 8 / 18
Longitudal shifts Peak Date: (2days/degree) Source: Wang et al. 2011 9 / 18
Phenology-based decision tree (concept framework) W. wheat; Y W. wheat Peak in CSG Summer dry- early spr. down Short grow Corn/Soy; Y Time S. wheat; season Early end S. wheat series Short grs Late peak date Y Corn/Soy Long grow WSG; Y Low peak value Short grs season CSG Shorter season Y WSG CSG
(thresholds flowchart)For more details, please refer to Wang et 13 / 18al., Annuals of AAG, 101(4), 2011.
Results The Midwest crop maps, 2000-2009 14 / 15
Cherokee Plain, MO (with past studies) DOY Date Sensor 52 2/21/2007 ASTER Taberville 73 3/14/2006 TM Pr. 92 4/2/2007 TM A 2-year MDC project 106 111 4/16/2007 4/21/2007 AWIFS (A) AWIFS (A) 134 5/14/2007 AWIFS (B) 140 5/20/2007 AWIFS (A) WKT Pr. 153 06/02/2006 TM 172 06/21/2007 TM Osage Pr.. 188 07/07/2007 AWIFS (A) 192 7/11/2007 AWIFS (B) 202 7/21/2007 ASTER 220 8/8/2007 TM 228 8/16/2007 ASTER 240 8/28/2007 AWIFS (B) 271 9/27/2008 TM 292 10/19/2007 ASTER Pr. State Park 303 10/29/2008 TM 313 11/9/2006 TM 16 / 16
Summary and future research Native warm-season grasses in the Midwest hold unique phenology metrics (time series analysis); Phenology metrics vary with inter-annual climate dynamics (phenology metrics inventory); The 20+ million ha of native grasses (upon validation) in the Midwest indicates its high bioenergy potential; The spatially explicit energy crop map is a quantitative supplement to county-level biomass supplies.Next……? Future investigation: • region-wide validation! • biomass quant. of energy crops; • Bioenergy policy and LULC. ORNL Switchgrass production. 18 17 /
Thanks!Acknowledgement: This research is supported by the Mizzou AdvantageProject. We would like to thank Le T. Ngan, Wei Zhang, Qing Chang inDept. of Geography and D.J. Donahue at FAPRI in data process. Also ourthanks to USDA/NASS for providing the CDL data that serve as excellentreference in this research. 18 / 18
A particular slide catching your eye?
Clipping is a handy way to collect important slides you want to go back to later.