Traffic intensity classes versus visual disturbance and soil physical property data

3.1.7 Traffic intensity classes versus visual disturbance and soil physical property data

The traffic intensity data represent the estimated number of passes by a skidder. The majority of these data apply to the snig track network. Thus, we compared traffic intensity with observations of snig track disturbance and soil physical properties. The aim was to determine whether there was a correlation between snig track grade (minor, moderate, major) and the number of passes.

The greatest challenge, and potential limitation, to this analysis, is the precise co-location of observation and soil sampling points with the “tracks” defined by the GPS traffic pass data of Figure 10. Overlaying sampling points and traffic data in a GIS resulted in a high level of misclassification. (Points we classified as snig track during sampling did not fall on a defined traffic path according to the GPS data.) We attempted to overcome this by using a radius search for each snig track point identified in the grid-point intersect survey. We attached the closest traffic pass data within either a 3, 5 or 10 m radius of the point. There was little difference between the data sets produced by each search radius, other than that more points were attached using a 10-m search radius.

Histograms (Fig. 16a) and box plots (Fig. 16b) using the 10-m search radius show some differentiation in the number of passes data between snig track classes. The notable differences were that the moderate tracks had an exceptionally high frequency of between five and ten passes, and the major snig tracks had a couple of points classified as having more than 120 passes.

A plot of bulk density and penetration resistance against traffic passes is shown in Figure 17. There is no real evidence of a relationship for either parameter. If the data points in the lower right of the penetration resistance plot are omitted, the suggestion of a relationship would certainly be quite strong, but there is no basis for omitting these data, and the variability must be accepted.

There are two major sources of measurement error in this analysis. One is the calculation of traffic passes when processing GPS data, and the other is getting an accurate spatial match between the independently positioned tracking data and the survey data. If the disturbance survey was controlled by the spatial positioning data obtained during machine tracking, there may be a closer relationship between traffic passes, visual disturbance classification, and soil physical properties. We cannot rule out, however, that the major trend of the data is real, and that the number of traffic passes only loosely reflects apparent disturbance and soil physical properties for this operation.

a)

b)

Minor snig Moderate snig

Major snig

equenc 60 er of 60

Minor snig Moderate snig Major snig Number of passes

Figure 16. Histograms and box plot of number of passes recorded by machine tracking by each snig track class. The histogram bars are in categories of 5 passes.

a)

b)

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an ity 1.20 st si 1.5

ns

De lk 1.00 o ti u 1.0 a B

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0.80 n e 0.5

Number of passes Number of passes

Figure 17. Snig track bulk density (a) and penetration resistance (b) against number of passes recorded by machine tracking.