Nearest-tree and Variable Polygon Sampling
HTML Source EditorWord Wrap Sampling a nearest neighbor is often presented as a Hansen-Hurwitz or Horvitz-Thompson estimation process. This may not be the most informative viewpoint, and measuring the probability of selection is not necessary. The measurement of the nearest object as a “depth” over...
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| Veröffentlicht in: | International journal of mathematical and computational forestry & natural-resource sciences Jg. 15; H. 1; S. 1 |
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| 1. Verfasser: | |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Athens
The MCFNS Publisher
30.04.2023
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| Schlagworte: | |
| ISSN: | 1946-7664 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | HTML Source EditorWord Wrap Sampling a nearest neighbor is often presented as a Hansen-Hurwitz or Horvitz-Thompson estimation process. This may not be the most informative viewpoint, and measuring the probability of selection is not necessary. The measurement of the nearest object as a “depth” over the selection area can be done by a sampling process, and the total estimated without the polygon areas. The process is unbiased, quite general, and easy to understand. It can be extended to more than just the nearest object to a sample point and to many different polygon shapes. This paper is an extension, simplification and generalization of an earlier paper in this journal (Iles, K. 2009 “Nearest-tree" estimations - A discussion of their geometry, MCFNS 1(2), pages 47 51.) , and does not require a random orientation or weighting for the direction of measurement from the tree to the polygon border. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1946-7664 |