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| Format: | Artículo científico |
| Language: | en |
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Universidade Federal de Lavras
2018
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| Online Access: | https://www.redalyc.org/articulo.oa?id=74460167002 https://www.redalyc.org/journal/744/74460167002/ https://www.redalyc.org/journal/744/74460167002/html/ https://www.redalyc.org/journal/744/74460167002/74460167002.epub https://www.redalyc.org/journal/744/74460167002/movil |
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| _version_ | 1866811854200766464 |
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| author | Diego dos Santos Vieira |
| author_facet | Diego dos Santos Vieira |
| contents | SAMPLING PROCESSES FOR Carapa guianensis AUBL. IN THE AMAZON Diego dos Santos Vieira Marcio Leles Romarco de Oliveira João Ricardo Vasconcellos Gama Bruno Lafetá Oliveira Anna Karyne Costa Rego Talita Godinho Bezerra Agrociencias Systematic samplingn Simple random sampling Adaptive cluster sampling The objective of this study was to analyze the adaptive cluster sampling (ACS), simple random sampling (SRS) and systematic sampling (SS) processes to obtain the number of ha-1 trees of Carapa guianensis Aubl. in the Amazon. The data were obtained through 100% inventory and sampling simulations, considering a DBH ≥ 25 cm, a sampling intensity of 4%, a maximum error of 10% and plots of 0.09, 0.16 and 0.25 ha. The last two sizes were only used to analyze their effect on the ACS estimators. The processes were evaluated for accuracy, precision (E%) and confidence interval (CI), while the mean ha-1 of the processes were compared with that of the 100% inventory by the Z test. The ACS process showed no significant difference between its average ha-1 trees and the 100% inventory, and it was also the most accurate and the only one whose CI was true. However, it presented a final sample intensity 3.6 times greater than the simple and systematic random samplings, in addition to E% above 10%, which makes it unacceptable, legally, and economically unfeasible. The other processes had densities significantly higher than the 100% inventory, with sample intensities lower than ACS and E% lower than 10%, making them legally viable. The use of larger plots in the ACS implies larger clusters and a greater tendency to underestimate the number of trees, resulting in larger sample errors and less accuracy. 2018 artículo científico 0104-7760 https://www.redalyc.org/articulo.oa?id=74460167002 https://www.redalyc.org/journal/744/74460167002/ https://www.redalyc.org/journal/744/74460167002/html/ https://www.redalyc.org/journal/744/74460167002/74460167002.epub https://www.redalyc.org/journal/744/74460167002/movil 10.1590/01047760201824032514 en http://www.redalyc.org/revista.oa?id=744 CERNE application/pdf Universidade Federal de Lavras CERNE (Brasil) Num.3 Vol.24 |
| format | Artículo científico |
| id | redalyc_74460167002 |
| language | en |
| publishDate | 2018 |
| publisher | Universidade Federal de Lavras |
| spellingShingle | SAMPLING PROCESSES FOR Carapa guianensis AUBL. IN THE AMAZON Diego dos Santos Vieira Agrociencias Systematic samplingn Simple random sampling Adaptive cluster sampling SAMPLING PROCESSES FOR Carapa guianensis AUBL. IN THE AMAZON Diego dos Santos Vieira Marcio Leles Romarco de Oliveira João Ricardo Vasconcellos Gama Bruno Lafetá Oliveira Anna Karyne Costa Rego Talita Godinho Bezerra Agrociencias Systematic samplingn Simple random sampling Adaptive cluster sampling The objective of this study was to analyze the adaptive cluster sampling (ACS), simple random sampling (SRS) and systematic sampling (SS) processes to obtain the number of ha-1 trees of Carapa guianensis Aubl. in the Amazon. The data were obtained through 100% inventory and sampling simulations, considering a DBH ≥ 25 cm, a sampling intensity of 4%, a maximum error of 10% and plots of 0.09, 0.16 and 0.25 ha. The last two sizes were only used to analyze their effect on the ACS estimators. The processes were evaluated for accuracy, precision (E%) and confidence interval (CI), while the mean ha-1 of the processes were compared with that of the 100% inventory by the Z test. The ACS process showed no significant difference between its average ha-1 trees and the 100% inventory, and it was also the most accurate and the only one whose CI was true. However, it presented a final sample intensity 3.6 times greater than the simple and systematic random samplings, in addition to E% above 10%, which makes it unacceptable, legally, and economically unfeasible. The other processes had densities significantly higher than the 100% inventory, with sample intensities lower than ACS and E% lower than 10%, making them legally viable. The use of larger plots in the ACS implies larger clusters and a greater tendency to underestimate the number of trees, resulting in larger sample errors and less accuracy. 2018 artículo científico 0104-7760 https://www.redalyc.org/articulo.oa?id=74460167002 https://www.redalyc.org/journal/744/74460167002/ https://www.redalyc.org/journal/744/74460167002/html/ https://www.redalyc.org/journal/744/74460167002/74460167002.epub https://www.redalyc.org/journal/744/74460167002/movil 10.1590/01047760201824032514 en http://www.redalyc.org/revista.oa?id=744 CERNE application/pdf Universidade Federal de Lavras CERNE (Brasil) Num.3 Vol.24 |
| title | SAMPLING PROCESSES FOR Carapa guianensis AUBL. IN THE AMAZON |
| topic | Agrociencias Systematic samplingn Simple random sampling Adaptive cluster sampling |
| url | https://www.redalyc.org/articulo.oa?id=74460167002 https://www.redalyc.org/journal/744/74460167002/ https://www.redalyc.org/journal/744/74460167002/html/ https://www.redalyc.org/journal/744/74460167002/74460167002.epub https://www.redalyc.org/journal/744/74460167002/movil |