| dc.creator |
Ozcelik, Ramazan |
|
| dc.creator |
Cao, Quang V. |
|
| dc.creator |
Trincado, Guillermo |
|
| dc.creator |
Gocer, Nilsun |
|
| dc.date |
2018-06-30T21:00:00Z |
|
| dc.date.accessioned |
2020-10-06T11:01:25Z |
|
| dc.date.available |
2020-10-06T11:01:25Z |
|
| dc.identifier |
b5ab4810-3366-4344-a21f-0742dcf8b348 |
|
| dc.identifier |
10.1016/j.foreco.2018.03.051 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/b5ab4810-3366-4344-a21f-0742dcf8b348/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/69985 |
|
| dc.description |
Height-diameter models were developed for Brutian pine (Pinus brutia Ten.) and Taurus cedar (Cedrus libani A. Rich.) in Turkey. A modified Chapman-Richards model that includes dominant height was used to predict tree height from diameter. Using the twofold evaluation scheme, five alternative modeling approaches were evaluated: (1) fixed-effects model, (2) calibrated fixed-effects model, (3) calibrated mixed-effects model, (4) three-quantile regression method, and (5) five-quantile regression method. Parameters of fixed-effects, mixed-effects and quantile regression models were calibrated by use of a subset of height measurements, ranging from 1 to 10 sample trees per plot. Evaluation statistics show that both quantile regression models produced similar results, and that the mixed-effects model approach yielded the best results in predicting tree heights. Model performance improved with increasing sample size; but gains in performance generally increased at a decreasing rate. A sample size of four trees per plot appears to be a good compromise between sampling cost and predictive accuracy and precision. |
|
| dc.language |
eng |
|
| dc.rights |
info:eu-repo/semantics/closedAccess |
|
| dc.title |
Predicting tree height from tree diameter and dominant height using mixed-effects and quantile regression models for two species in Turkey |
|
| dc.type |
info:eu-repo/semantics/article |
|