| 1. | Title | Title | Mission Impossible: Positions determined by basic mapping-grade and recreation-grade GNSS receivers cannot emulate the actual spatial pattern of trees |
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| 2. | Creator | Author / affiliation / country | TaeYoon Lee; University of Georgia; University of Georgia; United States |
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| 2. | Creator | Author / affiliation / country | Pete Bettinger; University of Georgia; University of Georgia; United States |
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| 2. | Creator | Author / affiliation / country | Krista Merry; University of Georgia; University of Georgia |
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| 2. | Creator | Author / affiliation / country | Volkan Bektas; University of Georgia; University of Georgia |
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| 2. | Creator | Author / affiliation / country | Chris Cieszewski; University of Georgia; University of Georgia |
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| 3. | Subject | Keywords | Global navigation satellite system; complete spatial randomness; regular pattern; clustered pattern; root mean squared error; GPS receivers |
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| 3. | Subject | Discipline(s) | Forest technologies; Mensuration |
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| 4. | Description | Abstract | Global navigation satellite systems (GNSS) can provide valuable spatial information for effectively mapping and navigating through complex terrain and forest conditions. Relatively accurate positional information is essential for certain algorithms and models that base analyses on the spatial arrangement of trees, and for management of forestry operations. The accuracy of GNSS receivers has been well-tested under many environmental conditions. Depending on the technology selected and conditions within which it is employed, different amounts of variation will occur in the determination of a horizontal position. However, studies involving the spatial pattern and distribution of tree locations (point positions) observed by independent GNSS receivers generally have not considered the horizontal position error inherent in the spatial data. We conducted this study to investigate whether tree locations determined by recreation- and mapping-grade GNSS receivers can adequately represent the real point pattern of trees in a forest. The study area was a pine seed orchard located at the Whitehall Forest in Athens, Georgia (USA), that consisted of a regular pattern of trees. We tested three different GNSS receivers: one mapping-grade receiver and two recreation-grade receivers (traditional, handheld-type, and non-traditional types, GPS watch). With each receiver we determined tree locations at cardinal points around the stems of 112 trees (at North, South, East, and West, sides of the stems) and estimated the middle point measurement of two cardinal points (North-South and East-West). In addition, we used the average of all cardinal points (All) to determine tree locations. We compared these observed tree locations to actual tree locations, which were determined through precise field measurements and high-precision GPS base points. This study confirmed that the horizontal positional error of mapping grade receivers was significantly lower than those of recreation grade receivers, regardless of measurement method. However, the observed point pattern of trees from the GNSS observations of both recreation- and mapping-grade receivers failed to adequately represent the actual regular point pattern of the trees, as the positional error observed was not consistently projected in the same direction and with the same magnitude. |
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| 5. | Publisher | Publisher | Contemporary Journal Concept Press |
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| 6. | Contributor | Contributors / supporting agencies | |
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| 7. | Date | Publication date | 2022-04-30 |
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| 8. | Type | Type | Text.Serial.Journal; Point pattern analysis; positional acuracy |
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| 9. | Format | Format | PDF; application/pdf |
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| 10. | Identifier | Article URL | https://mcfns.com/index.php/Journal/en/article/view/14.2 |
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| 11. | Source | Journal / volume / issue / year / pages | Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS); Vol. 14 No. 1: MCFNS April 30, 2022; 15-31 (17) |
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| 11. | Source | Online ISSN | 1946-7664 |
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| 12. | Language | Language | en |
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| 13. | Relation | Supplementary files | |
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| 14. | Coverage | Geographical coverage | |
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| 15. | Rights | Rights / copyright | Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS) 2022 |
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