Challenges of UAV platforms
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Remote sensing –Beyond images ...

Remote sensing –Beyond images
Mexico 14-15 December 2013

The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)

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Challenges of UAV platforms Presentation Transcript

  • 1. Challenges of UAV platforms Lúcio André de Castro Jorge lucio.jorge@embrapa.br Beyond Diagnostics: Insights and Recommendations from Remote Sensing Mexico, 2013
  • 2. Evolution of Agriculture in Brazil EMBRAPA
  • 3. Embrapa Mission To design research, development and innovation solutions for the sustainability of Brazilian agriculture for the benefit of the Brazilian society. Institutional Profile » Established in 1973 » 9,801 employees » 2,428 researchers » 2,039 PhD researchers » 47 Research Centers and Services » International Cooperation: Americas, Europe, Asia and Africa » Yearly Budget: US$ 1 billion Updated employee data, 03/31/2013, DGP
  • 4. Embrapa Institutional Capacity Building MSc PhD/DSc Number of Employees BSc Source: Embrapa, DGP
  • 5. Embrapa Instrumentation Automation, Nanotecnology, Precision Agriculture ... Nanotecnology Laboratory for Agriculture National Precision Agriculture Lab
  • 6. Evolution of Agriculture in Brazil UAV at Embrapa Instrumentation
  • 7. Embrapa Precision Agriculture Network
  • 8. Use of UAV to Crop Monitoring Grass Crop Soil Weeds
  • 9. Start in 1998
  • 10. UAVs platforms
  • 11. Toy Model
  • 12. HELICOPTER
  • 13. PROJECT ARARA - 2003
  • 14. Patente EMBRAPA 2004
  • 15. Control Station - 2004
  • 16. Autonomous Operation - 2004
  • 17. Taking off in Farms
  • 18. PROJECT PRECISION AGRICULTURE - 2010
  • 19. UAV 2012 Precision Agriculture Network
  • 20. UAV QuadCopter – 2012 Small Farmers
  • 21. UAV - BRASIL 2013
  • 22. Evolution of Agriculture in Brazil Sensors
  • 23. SENSORS Digital Câmera – Visible bands Digital Video Câmera visíble
  • 24. SENSORS Cámara multiespectral NIR Cámara multiespectral – NIR + RGB
  • 25. Multispectral 6 bands
  • 26. SENSORS • Hyperspectral
  • 27. LIDAR Scanner Lucier et. al (2012)
  • 28. Evolution of Agriculture in Brazil Images
  • 29. Forest
  • 30. Citrus
  • 31. Soy and Corn
  • 32. CORN - 30 Days
  • 33. Sugar-cane
  • 34. Evolution of Agriculture in Brazil Image Processing
  • 35. Image Processing Applications Sugar-cane Grass Soil
  • 36. Spectral Analysis
  • 37. Soy bean – weeds and Deseases LEGENDA LEGENDA Doença - Nematóide Planta invasora Solo nu Solo nu
  • 38. Counting trees to yield evaluation
  • 39. Shape analysis
  • 40. Corn production LEGENDA Palha Cultura Solo Planta invasora
  • 41. NIR x NDVI
  • 42. WATER STRESS NDVI 0 - 0.1 0.1 - 0.2 0.2 - 0.3 0.3 - 0.4 0.4 - 0.5 0.5 - 0.6
  • 43. Evolution of Agriculture in Brazil Mosaics
  • 44. EMBRAPA Soy bean experimentation Softwares: - Agsoft - Pixel4D - SIFT (Embrapa)
  • 45. MOSAIC - Soy bean
  • 46. MOSAIC - Soy bean
  • 47. NIR Mosaic – Sugar-cane
  • 48. Visible MOSAIC sugar-cane
  • 49. Mosaic + DEM
  • 50. CITRUS images
  • 51. Mosaic - CITRUS
  • 52. Number of Images
  • 53. Mosaic and photos positions
  • 54. Mosaic Citrus
  • 55. Mosaic with SIFT
  • 56. MOSAIC HyperSpectral Citrus
  • 57. LIDAR points Wallace et. al (2012)
  • 58. Evolution of Agriculture in Brazil Flight Control
  • 59. Ardupilot - free
  • 60. Precision on position – strong wind
  • 61. Position With OctoCopter Wallace et. al (2012)
  • 62. Kinds of System • For small areas: free systems or very cheap – autonomous and visible flights; • For big areas: industrial solutions, with certification from regulators.
  • 63. Evolution of Agriculture in Brazil Challenges
  • 64. Challenges • OPERATION/SYSTEM – Quality of images • Systems to control Distortion: Pitch, roll, etc. Wide angle lenses • Maping pixels onto cm resolution model – Registration • Need more higher altitudes to have good results • 3D imaging cameras and 360 degrees pano images – Lighting Conditions: • Clouds, Shadows, Weather – Safety System • to avoid crashes and accidents; – Airplanes Certification • Brazil all models need on – Calibrations: • Solutions for easy correction geometric and radiometric
  • 65. Challenges • SOFTWARES – Complex softwares to process Multi and HyperSpectral Images, not for a researcher, but for farmers and final users; – Data management and extraction are a challenge; – Cloud processing could help to process a big volume of images but need permit big datas uploads; – Recomendations for final users are not available; – A complete solution for a final user is a big challenge, and could be done for each application.
  • 66. Lúcio André de Castro Jorge, PhD Brazilian Agricultural Research Corporation lucio.jorge@embrapa.br