Creating jigsaw puzzles in ArcMap
(New page: ==The concept of cluster inclusionzones for fixed area sample plots== The so called '''jigsaw puzzle view''' (Roesch et al. 1993<ref name="roesch1993">Roesch, F.A.; Green, E.J.; Scott, C....) |
(→The concept of cluster inclusionzones for fixed area sample plots) |
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==The concept of cluster inclusionzones for fixed area sample plots== | ==The concept of cluster inclusionzones for fixed area sample plots== | ||
| − | The so called '''jigsaw puzzle view''' (Roesch et al. 1993<ref name="roesch1993">Roesch, F.A.; Green, E.J.; Scott, C.T. 1993. An Alternative View of Forest Sampling. Survey Methodology 19 (2), 199-204.</ref>) is a decomopsition of the total domain of interest in non-overlapping inclusion zones for exclusive clusters of trees. | + | The so called '''jigsaw puzzle view''' (Roesch et al. 1993<ref name="roesch1993">Roesch, F.A.; Green, E.J.; Scott, C.T. 1993. An Alternative View of Forest Sampling. Survey Methodology 19 (2), 199-204.</ref>) is a decomopsition of the total domain of interest in non-overlapping inclusion zones for exclusive clusters of trees. In the [[infinit population approach]] sample elements are dimensionless points drawn from an infinit sample frame. Observations are derived as generalization over a number of nearest neighbours (trees) to a certain sample point. In fixed area sampling neighbours are considered up to a fixed distance (the radius of a circular sample plot). This "inclusion distance" can be assigned to every tree in the domain of interest, as a sample point falling in that distance would lead to a selection of the respective tree. This single tree inclusion zones are overlapping (as in most cases more than only one tree is selected by a sample point) whereas the resulting pattern is a decomposition of the total area in non-overlapping polygons, that would lead to a selection of a particular cluster of trees. |
| + | This article describes briefly, how jigsaw puzzles can be created from a map with tree locations in ArcGIS. | ||
| + | ===Workflow=== | ||
| + | *Basis for this decomposition is a map with tree locations (x and y coordinates) that might be generated or the result of a full assessment of a forest stand as shapefile or layer. | ||
==References== | ==References== | ||
<references/> | <references/> | ||
Revision as of 15:26, 21 January 2009
The concept of cluster inclusionzones for fixed area sample plots
The so called jigsaw puzzle view (Roesch et al. 1993[1]) is a decomopsition of the total domain of interest in non-overlapping inclusion zones for exclusive clusters of trees. In the infinit population approach sample elements are dimensionless points drawn from an infinit sample frame. Observations are derived as generalization over a number of nearest neighbours (trees) to a certain sample point. In fixed area sampling neighbours are considered up to a fixed distance (the radius of a circular sample plot). This "inclusion distance" can be assigned to every tree in the domain of interest, as a sample point falling in that distance would lead to a selection of the respective tree. This single tree inclusion zones are overlapping (as in most cases more than only one tree is selected by a sample point) whereas the resulting pattern is a decomposition of the total area in non-overlapping polygons, that would lead to a selection of a particular cluster of trees. This article describes briefly, how jigsaw puzzles can be created from a map with tree locations in ArcGIS.
Workflow
- Basis for this decomposition is a map with tree locations (x and y coordinates) that might be generated or the result of a full assessment of a forest stand as shapefile or layer.
References
- ↑ Roesch, F.A.; Green, E.J.; Scott, C.T. 1993. An Alternative View of Forest Sampling. Survey Methodology 19 (2), 199-204.
