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)

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

28. LIDAR Scanner
Lucier et. al (2012)

29. Evolution of Agriculture in Brazil
Images

30. Forest

32. Citrus

33. Soy and Corn

34. CORN - 30 Days

35. Sugar-cane

36. Evolution of Agriculture in Brazil
Image Processing

37. Image Processing Applications
Sugar-cane
Grass
Soil

38. Spectral Analysis

39. Soy bean – weeds and Deseases
LEGENDA
LEGENDA
Doença - Nematóide
Planta invasora
Solo nu
Solo nu

40. Counting trees to yield evaluation

41. Shape analysis

42. Corn production
LEGENDA
Palha
Cultura
Solo
Planta invasora

43. NIR x NDVI

44. 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

45. Evolution of Agriculture in Brazil
Mosaics

46. EMBRAPA
Soy bean experimentation
Softwares:
- Agsoft
- Pixel4D
- SIFT (Embrapa)

47. MOSAIC - Soy bean

48. MOSAIC - Soy bean

49. NIR Mosaic – Sugar-cane

50. Visible MOSAIC sugar-cane

51. Mosaic + DEM

52. CITRUS images

53. Mosaic - CITRUS

54. Number of Images

55. Mosaic and photos positions

56. Mosaic Citrus

57. Mosaic with SIFT

58. MOSAIC HyperSpectral Citrus

59. LIDAR points
Wallace et. al (2012)

60. Evolution of Agriculture in Brazil
Flight Control

61. Ardupilot - free

62. Precision on position – strong wind

63. Position With OctoCopter
Wallace et. al (2012)

64. Kinds of System
• For small areas: free systems or very cheap
– autonomous and visible flights;
• For big areas: industrial solutions, with
certification from regulators.

65. Evolution of Agriculture in Brazil
Challenges

66. 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

67. 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.

68. Lúcio André de Castro Jorge, PhD
Brazilian Agricultural Research Corporation
lucio.jorge@embrapa.br