Challenges of UAV platforms

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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

  1. 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. 2. Evolution of Agriculture in Brazil EMBRAPA
  3. 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. 4. Embrapa Institutional Capacity Building MSc PhD/DSc Number of Employees BSc Source: Embrapa, DGP
  5. 5. Embrapa Instrumentation Automation, Nanotecnology, Precision Agriculture ... Nanotecnology Laboratory for Agriculture National Precision Agriculture Lab
  6. 6. Evolution of Agriculture in Brazil UAV at Embrapa Instrumentation
  7. 7. Embrapa Precision Agriculture Network
  8. 8. Use of UAV to Crop Monitoring Grass Crop Soil Weeds
  9. 9. Start in 1998
  10. 10. UAVs platforms
  11. 11. Toy Model
  12. 12. HELICOPTER
  13. 13. PROJECT ARARA - 2003
  14. 14. Patente EMBRAPA 2004
  15. 15. Control Station - 2004
  16. 16. Autonomous Operation - 2004
  17. 17. Taking off in Farms
  18. 18. PROJECT PRECISION AGRICULTURE - 2010
  19. 19. UAV 2012 Precision Agriculture Network
  20. 20. UAV QuadCopter – 2012 Small Farmers
  21. 21. UAV - BRASIL 2013
  22. 22. Evolution of Agriculture in Brazil Sensors
  23. 23. SENSORS Digital Câmera – Visible bands Digital Video Câmera visíble
  24. 24. SENSORS Cámara multiespectral NIR Cámara multiespectral – NIR + RGB
  25. 25. Multispectral 6 bands
  26. 26. SENSORS • Hyperspectral
  27. 27. LIDAR Scanner Lucier et. al (2012)
  28. 28. Evolution of Agriculture in Brazil Images
  29. 29. Forest
  30. 30. Citrus
  31. 31. Soy and Corn
  32. 32. CORN - 30 Days
  33. 33. Sugar-cane
  34. 34. Evolution of Agriculture in Brazil Image Processing
  35. 35. Image Processing Applications Sugar-cane Grass Soil
  36. 36. Spectral Analysis
  37. 37. Soy bean – weeds and Deseases LEGENDA LEGENDA Doença - Nematóide Planta invasora Solo nu Solo nu
  38. 38. Counting trees to yield evaluation
  39. 39. Shape analysis
  40. 40. Corn production LEGENDA Palha Cultura Solo Planta invasora
  41. 41. NIR x NDVI
  42. 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. 43. Evolution of Agriculture in Brazil Mosaics
  44. 44. EMBRAPA Soy bean experimentation Softwares: - Agsoft - Pixel4D - SIFT (Embrapa)
  45. 45. MOSAIC - Soy bean
  46. 46. MOSAIC - Soy bean
  47. 47. NIR Mosaic – Sugar-cane
  48. 48. Visible MOSAIC sugar-cane
  49. 49. Mosaic + DEM
  50. 50. CITRUS images
  51. 51. Mosaic - CITRUS
  52. 52. Number of Images
  53. 53. Mosaic and photos positions
  54. 54. Mosaic Citrus
  55. 55. Mosaic with SIFT
  56. 56. MOSAIC HyperSpectral Citrus
  57. 57. LIDAR points Wallace et. al (2012)
  58. 58. Evolution of Agriculture in Brazil Flight Control
  59. 59. Ardupilot - free
  60. 60. Precision on position – strong wind
  61. 61. Position With OctoCopter Wallace et. al (2012)
  62. 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. 63. Evolution of Agriculture in Brazil Challenges
  64. 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. 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. 66. Lúcio André de Castro Jorge, PhD Brazilian Agricultural Research Corporation lucio.jorge@embrapa.br

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