Processing harvest yield data to grid / raster

The process to convert point data to raster (or grid) for can differ dramatically depending on who you ask and the purpose of the conversion. Generally data is processed for two main functions. The first being ‘stacking’ or ‘layering’ to later develop prescription maps or other further processing. The second is improved visual representation of the data. My process aims to satisfy both with minimal processing time. My method does contain some compromises; since I use a coarse resolution it is not as pleasing on the eye as some other methods. In addition, my data smoothing technique is quite broad which means you will loose some detail in the grid.

At this point in time I follow these steps:

  1. Clean up point data either manually manually or with a filter to remove any obvious errors such as where header turns in paddock. EDIT: I am currently trying Yield Editor for this step.
  2. Produce a grid over the top of the point data. Any cells that share a points average the point values.
  3. Gaps in the grid are filled in.
  4. Gaussian Filter is used to ‘smooth’ the data.

In QGIS this is the process:

Note: You will need to have SEXTANTE and additional toolboxes setup to follow these steps. Instructions are available here.

  1. Load paddock boundary (shape file polygon)
  2. Load yield data points (You will need these in shape file format – use export function in SMS or FOViewer if your yield monitor does not produce ESRI shape file)
  3. SEXTANTE > SAGA Toolbox > Shapes – Points > Points Filter
    1. Radius: 100
    2. Minimum Number of Points: 25
    3. Maximum Number of Points: 200
    4. Quadrants: No
    5. Filter Criterion: Remove Below Percentile
    6. Percentile: 15-20
  4. SEXTANTE > SAGA Toolbox > Shapes – Points > Points Filter (use output from step 3)
    1. Radius: 100
    2. Minimum Number of Points: 25
    3. Maximum Number of Points: 200
    4. Quadrants: No
    5. Filter Criterion: Remove Above Percentile
    6. Percentile: 90
  5. SEXTANTE > SAGA Toolbox > Grid – Gridding > Shapes to Grid
    1. Preferred Target Grid Type: Floating Point
    2. Cell Size: 15
    3. Method for Multiple Values: Mean
  6. SEXTANTE > SAGA Toolbox > Grid – Tools > Close Gaps
  7. SEXTANTE > SAGA Toolbox > Shapes – Grid > Clip Grid with Polygon
  8. SEXTANTE > SAGA Toolbox > Gaussian Filter
    1. Standard Deviation: 3
    2. Search Mode: Circle
    3. Search Radius: 50

Make sure you do a visual comparison with original point data to ensure the final grid is a good representation of the original data.

Visually check to see that processed grid file is a fair representation of the original point data.
Visually check to see that processed grid file is a fair representation of the original point data. Note I was lazy in this photo and used un-filtered yield data.

To generate useful color maps to represent the grid data try http://colorbrewer2.org/. One day I will explain this process, but it is not too hard to try it yourself.

Now when we get clever we can use the SEXTANTE Modeler to automate this process. More on this later! –Edit: Here is the modeler info.

 

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