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Automated Blocking

The automated blocking strategy used in FSSAM groups together stands that are in the timber harvest land base into cutblocks. This is done in such a way that the distribution of the areas of the cutblocks will conform as far as possible to a target distribution. For example, the target distribution could specify that 20% of the area should be in blocks of size between 80 and 250 hectares, 40% of the area in blocks between 40 and 80 hectares, and the remaining 40% in blocks less than 40 hectares.

The actual blocking is done by grouping stands together on the basis of similarity. Three overall types of similarity category are used to determine whether adjacent stands may be grouped:

  • Numeric range. In this category, segmentation into bins is done on the basis of a numeric attribute of the stand. For example, stands could be grouped together by age, with age bin boundaries at 20, 50, 100, and 200 years.
  • String match. In this category, a non-numeric stand attribute like leading species is used to perform the separation. Lists of leading species that can be grouped together are specified by the user. These lists could take the form {['pine, fir'], ['spruce, hemlock, cedar'], ['deciduous'], ['other']}. Then pine stands, for example, could be blocked together with fir stands but not with anything else.
  • String category. In this category, each different value of a non-numeric stand attribute is used to define a separate bin for grouping. For example, if the attribute chosen is BEC zone (Biogeoclimatic Ecological Classification), then each stand with a particular BEC value could only be grouped together with those that have the same value.
  • The actual blocking of compatible stands is done by fusing adjacent stands with sufficiently similar properties (as outlined above). The stand blocking process starts with the selection of a large stand as a "seed block", and, in an iterative process, fuses suitable adjacent stands with the growing block until a threshold determined by the block size distribution is reached.

    This approach to grouping on the basis of attribute similarity and adjacency provides a flexible and powerful way of designing cutblocks.

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