Provider: Ingenta Connect
Database: Ingenta Connect
Content: application/x-research-info-systems
TY - ABST
AU - Arner, Stanford L.
AU - Westfall, James A.
AU - Scott, Charles T.
TI - Comparison of Annual Inventory Designs Using Forest Inventory and Analysis Data
JO - Forest Science
PY - 2004-04-01T00:00:00///
VL - 50
IS - 2
SP - 188
EP - 203
KW - natural resources
KW - environmental management
KW - natural resource management
KW - forest management
KW - forest resources
KW - forest
KW - generalized least squares
KW - forestry
KW - moving average estimates
KW - forestry science
KW - Rotating panel design
KW - forestry research
N2 - Three annual inventory designs, a periodic design, and a periodic measurement with midcycle update design are compared using a population created from 14,754 remeasured Forest Inventory and Analysis plots. Two of the annual designs and the midcycle update design allow updating of plots
not measured using sampling with partial replacement procedures. Comparisons are based on root mean square error and estimator bias determined for net volume (m^{3}/hectare) and mean annual net volume change. For the annual designs, both individual year and moving average estimates
are investigated. The latter are compared to both the population means of the most recent year used in the average and to population means covering the same period as the estimate. Among annual designs, a rotating panel design, in which an equal portion of the total sample is measured each
year without remeasurement until the start of the next measurement cycle, produced the smallest root mean square error for estimates of mean net volume. For multiple-year comparisons, the rotating panel and periodic designs resulted in the smallest root mean square errors; for single-year
comparisons, the periodic design resulted in the smallest root mean square error. For mean annual volume change, the smallest root mean square error was produced by the periodic design. Among annual designs, the rotating panel design resulted in the smallest root mean square error for multiple-year
comparisons of volume change, while a design allowing annual updates of estimates using generalized least squares resulted in the smallest root mean square error for single-year comparisons. FOR. SCI. 50(2):188–203.
UR - http://www.ingentaconnect.com/content/saf/fs/2004/00000050/00000002/art00005
ER -