1. AZ State Technical Committee Meeting September 7 th, 2011

2. Geospatial tools can complement, but not replace, field data in the ranking process Field data limitations Remote sensing strengths

3. FIELD OFFICES vs REMOTE SENSING Field Office Ranking Remote Sensing Ranking Equal Ranking Field Office *Field Office ranking includes other factors unrelated to land conditions. The Ranking Difference

4. Value (%)

6. i-cubed 15m eSAT Imagery 2010 30m Landsat 2010 500m MODIS 60% 0%

7. Loamy Upland Reference Area A Loamy Upland Mesquite-Dominated Eroded State

8. Total CoverIdeal Soil CanopyLitter, basal area Water InterceptionRoughness, infiltration Air CanopyProtection from wind Plants Amount of vegetation Composition, forage Animals CanopyHabitat requirements

9. 60% 0% 2002 30m Landsat

11. Total Vegetation Fractional Cover is scaled from Ground Measurements to LANDSAT (30 m) ….

12. Cover: 5% measured 10% Landsat (ID: 123-0.022) Cover: 5% measured 12% Landsat (ID: 59-0.030) Cover: 17% measured 22% Landsat (ID: 54-0.094) Cover: 10% measured 14% Landsat (ID: 115-0.042)

13. 1 2 3 4 5 6 1 - USGS 2002-2004 2 - USGS 2002-2004 3 - Marsett 2010 4 - Marsett 2008 5 - Marsett 2000-2007 6 - Marsett 2001-2002

15. 1. Create polygons of ranch boundaries 2. Average MODIS and Landsat cover images 3. Average PRISM precipitation, max and min temps ‘07-’10 4. Exploratory plotting 5. Create statistical model of cover 6. Compare observed cover to expected cover 7. Rank and assign points

17. 1. Create polygons of ranch boundaries 2. Average MODIS and Landsat cover images 3. Average PRISM precipitation, max and min temps ‘07-’10 4. Exploratory plotting 5. Create statistical model of cover 6. Compare observed cover to expected cover 7. Rank and assign points

18. Value (%)

19. Value (in) 40

23. 1. Create polygons of ranch boundaries 2. Average MODIS and Landsat cover images 3. Average PRISM precipitation, max and min temps ‘07-’10 4. Exploratory plotting 5. Create statistical model of cover 6. Compare observed cover to expected cover 7. Rank and assign points

26. 1. Create polygons of ranch boundaries 2. Average MODIS and Landsat cover images 3. Average PRISM precipitation, max and min temps ‘07-’10 4. Exploratory plotting 5. Create statistical model of cover 6. Compare observed cover to expected cover 7. Rank and assign points

28. 1. Create polygons of ranch boundaries 2. Average MODIS and Landsat cover images 3. Average PRISM precipitation, max and min temps ‘07-’10 4. Exploratory plotting 5. Create statistical model of cover 6. Compare observed cover to expected cover 7. Rank and assign points

30. FARM (Financial Assistance Ranking Model) Ranking Admin Tool & Geospatial Ranking Tool Currently piloting in 8 states

31. The Proposal: Looking for a recommendation from the State Technical Committee in favor of using this technology in 5 or 6 field offices for the FY2012 EQIP ranking process. Looking to apply Statewide in FY2013.

32. Soil brightness (L Factor) Snow, clouds, shadow (North facing slopes) Fire Need smoothing at the pixel level Testing across vegetation communities Incorporating soil, slope, aspect, other factors into statistical models Sustaining funding

33. R = 0.65

35. i-cubed 15m eSAT Imagery

36. 1. Create polygons of ranch boundaries 2. Average MODIS and Landsat cover images 3. Average PRISM precipitation, max and min temps ‘07-’10 4. Exploratory plotting 5. Create statistical model of cover 6. Compare observed cover to expected cover 7. Rank and assign points