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Site specific weed management: mapping the tempo-spatial development of purple nutsedge ( Cyperus rotundus ) Hanan Eizenberg

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The 2 nd International Conference on: Novel and Sustainable Weed Management in Arid and Semi-Arid Agro-Ecosystems. Site specific weed management: mapping the tempo-spatial development of purple nutsedge ( Cyperus rotundus ) Hanan Eizenberg Tal Naamat, Ran Lati , Tal Miller and Roy Efron

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Presentation Transcript
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The 2nd International Conference on: Novel and Sustainable Weed Management in Arid and Semi-Arid Agro-Ecosystems

Site specific weed management: mapping the tempo-spatial development of purple nutsedge (Cyperusrotundus)

Hanan Eizenberg

Tal Naamat, Ran Lati, Tal Millerand Roy Efron

Dept. of Weed Research, ARO, NeweYa’ar Research Center, Ramat Yishay 30095, Israel

slide2

Objective:

  • The main objective of the entire study is to develop a multiple approach for the detection of purple nutsedge spatial development
  • To achieve our objective, the state of art in detection technologies for both above and sub-surface spatial development were used
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Our approach thus includes:

  • Spectral analysis of purple nutsedge obtained from satellites or airborne
  • Leaf shape analysis obtained from image data
  • photogrammetric (3D) analysis obtained from image data and laser (LIDAR)
  • Modeling spatial sprouting of the weed under different environmental conditions
  • Modeling the soil-subsurface development and its reflectance on purple nutsedge spatial sprouting
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Topic

Technology

Modeling spatial growth for the above and sub-surface

RGB high resolution camera; 0.5x0.5 mm pixel size. Lati et al. Minirhyzotronnon destructive video camera. Naamat et al.

RGB high resolution camera; 0.5x0.5 pixel size. 3D LIDAR

scenes and photogrammetric. Lati et al. RGB high resolution camera; 1x1mm pixel size. Efron et al.

Close range remote sensing

Aerial RGB high resolution camera; 50x50mm pixel size.

Tal Miller et al.

Far range remote sensing

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Examples 1.

Monitoring the sub-surface development of purple nutsedge using minirhyzotron video camera

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13.2.08

9.3.08

23.3.08

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Examples 2.

Developing a robust method for purple nutsedge detection under varies light conditions

or

How to overcome the shading effect?

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Fig. 1

1-a

1-b

1-c

2-b

2-a

2-c

3-a

3-b

3-c

4-a

4-b

4-c

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Biological model

Above soil surface

growth model

Purple nutsedge spatial growth model

Sub surface

growth model

laser scanner description
Laser Scanner (description)

Color digital camera

Laser Scanner

slide12
Ranging - travel time based measurement

Knowledge of the laser beam direction  determination of point in space

Direct measurement of 3D coordinates of the objects in space

Panoramic scan - complete 3D depiction of the surveyed scene can be achieved – generates 3D point clouds

Laser Scanner (principles)

slide16

Remote sensing using close range, high resolution (2 mega-pixel) RGB cameras

  • Collecting geospatial information using dGPS (sub-meter accuracy)
  • Logging information onto an onboard computer
slide17

GPS Antenna

Camera

1

Field Of View

Camera

2

Field Of View

Computer

ECPA - July 2008

slide18

14_right_cam.avi

MOV07482.MPG

slide22

Weed Map

  • Number of weeds per image
  • Area of the weeds
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Summary

Biology

Technology

Remote sensing for purple nutsedge detection

Input of meteorological data (T°C; PAR)

Close range

Terrestrial sensors

RGB, NIR, LIDAR

Far range

aerial sensors

Satellite; airborne

Soil Sub-surface model

Above surface growth sub-model

Developing an algorithm for weed detection – range related

Purple nutsedge

growth model

Fixing data into GIS (using GPS)

Creating a purple nutsedge spatial distribution map

Field history

slide24

Taking home massage

Integration of the biological and technological means for purple nutsedge detection support and complements each other, and may provide a new dimensions in its precision management.

message

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Thanks

  • To my students, Tal N., Tal M., Ran, Roy.
  • To my colleagues from the department of Weed Research Yosi, Radi, Dani, Tal L., Guy, Evgeni.
  • To Victor, Yafit and Sagi.
  • To the Chief Scientist from the Ministry of Agriculture for funding the research.
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