Hyperspectral Imagery For Production Agriculture
- 1. AERIAL IMAGERY SERVICE OVERVIEW PRECISE INFORMATION ADVANCING PRECISION AGRICULTURE
- 2. Current Market Sectors • Agriculture: Information for crop analysis • Defense: IED detection/counter narcotics Near-Term Additional Markets • Geology • Natural recourses • Environmental assessment • Forestry • Aquaculture/mariculture 2
- 3. ARC’S TECHNOLOGY • Visible / near infrared & thermal • 151 spectral bands • Uses full spectrum of information
- 4. Why Hyperspectral 4
- 5. Imagery Today - Multispectral 5 1 0.45 to 0.52 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0.40 0.47 0.53 0.59 0.64 0.71 0.78 0.99 1.15 1.30 1.45 1.62 1.87 2.17 longitud de onda (micrones) reflectancia Visible Reflected infrared Near infrared Short wave infrared Leaf pigments Leaf cell structure Water content Region of Spectrum Wavelength (microns) Reflectance 2 0.52 To 0.60 3 0.63 To 0.69 4 0.79 To 0.90 5 1.55 to 1.75 7 2.08 To 2.35 Band 3 Band 1 Band 2 Band 4 • Current analysis based on only 4 bands • Data is normalized • Variability Limited • Ratio of 2 bands to create NDVI • Relative Index Collection to Analysis
- 6. Hyperspectral Imagery “The Next Generation” 6 In real life, plants are much more complicated, and every soil difference or farming decision shows up in the spectral details Collection to Analysis Every color in the AgVu image shows real information: • Crop Health • Effect of Nitrogen/ Sulfur • Invasive Species • From 151 Spectral Bands We pick this up 100s of bands in hyperspectral images show more detail by splitting the spectrum into smaller pieces than multispectral The Next Generation is Now
- 7. MMOORREE IINNFFOORRMMAATTIIOONN,, BBEETTTTEERR DDEECCIISSIIOONNSS 44 bbaannddss:: WWhhaatt ddoo yyoouu sseeee?? 7
- 8. MMOORREE IINNFFOORRMMAATTIIOONN,, BBEETTTTEERR DDEECCIISSIIOONNSS 77 bbaannddss:: WWhhaatt ddoo yyoouu sseeee?? 8
- 9. MORE INFORMATION, BETTER DECISIONS 115511 bbaannddss:: WWhhaatt ddoo yyoouu sseeee?? 9
- 10. 10 How the Techniques Compare Multispectral NDVI RGB
- 11. 11 How the Techniques Compare Hyperspectral Imaging—How to See It Early The most subtle distinctions are picked out over the entire vegetative region—allowing images to show farmers crop health and stress earlier than ever before
- 12. More Information, Better Decisions 50X as much information means subtle issues are evident earlier 12 True Color NDVI AgVu Decisions are limited by the amount of information available ARC’s hyperspectral sensor removes this limitation
- 13. More Information, Better Decisions Crop Varieties Crop Growth Inhibitors 13 SSooyybbeeaannss What Hybrid is Planted? Waterway - grass Farmstead Terraces Grass Waterway Farmstead Line OOlldd ffeennccee lliinnee Corn - 2 Hybrids Alternate 16 rows Corn - different hybrid Beans RR STS Conventional Corn Soybeans Different Varieties VVaarr II VVaarr IIII VVaarr IIIIII VVaarr IIVV VVaarr 33 VVaarr 22 VVaarr 33 VVaarr 44 Corn - different hybrid CRP - (10 year reserve) grass with areas mowed (dark) for thistle control 30 in row soybeans Corn Roundup Ready STS Conventional VVaarr 22 VVaarr 11 VVaarr 11 VVaarr 22 VVaarr 44
- 14. Efficient Monitoring AgVu identifies weed pressure early in the season, saving the grower lost crop and June 25 July 10 Aug 14 Sep 11 Sep 25 14 lost yield by allowing them to treat the problem early. Provides information for improving yields, reducing costs, and increasing sales
- 15. Operations 15
- 16. How We Schedule 100 Example Timing of Imagery Capture Tasseling “Charter” flights • Customer monitors for growth stages • Increased infrastructure • Loss of efficiency • Scheduling harder for customers “Commercial” flights • Automatic monitoring of growth stages • Less infrastructure • High efficiency • Scheduling easy for customers 0 Cumulative Temperature/GDDs Harvest Crop Growth Status (%) Bare soil V5-V10 Fertility Requirements Pre-senescence Yield predictions Emergence 16
- 17. Order Submission Back Office Work Flow Order Validation Mission Planning Flight Scheduling Flight Plan Delivery 1 2 3 4 5 Customer provided shp files Online interface Chose acquisition window Imagery specifications Validate shp files Validate all customer information Operations plans Determine Regions of Interest (ROI) Compile Operations/flight plans Provide flight plans and timing of flights Ensure pilot availability Raw Images Captured Image Delivery QA/QC Image Processing Customer Access 10 9 8 7 6 Via web interface Export/Import to precision ag software True Color Analysis map (AgVu) Push to web interface Check for inconsistencies Shadows Reprocess ARC process via proprietary algorithm Mosaic and orthorectification Clipped to boundary Data sent from field site to ARC server 24 hours 24 hours 7 Day Flight Range 12 hours 48 Hours 17 Order Entry to Delivery
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