Article
 

Small-Area Estimation of County-Level Forest Attributes Using Ground Data and Remote Sensed Auxiliary Information

公开 Deposited

可下载的内容

下载PDF文件
https://ir.library.oregonstate.edu/concern/articles/12579s87t

Descriptions

Attribute NameValues
Creator
Abstract
  • Small-area estimation (SAE) is a concept that has considerable potential for precise estimation of forest ecosystem attributes in partitioned forest populations. In this study, several estimators were compared as SAE techniques for 12 counties in the northern Oregon Coast range. The estimators that were compared consisted of three indirect estimators, multiple linear regression (MLR), gradient nearest neighbor imputation (GNN), and most similar neighbor imputation (MSN), and five composite estimators based on MLR, MSN, and GNN with county-level direct estimates. Forest attributes of interest were density (trees/ha), basal area (m2/ha), cubic volume (m3/ha), quadratic mean diameter (cm), and average height of 100 largest trees per ha. The sample consisted of 680 annual Forest Inventory Analysis plots, a spatially balanced sample across all conditions and ownerships. The auxiliary data consisted of 16 Landsat variables, a land cover classification, tree cover, and elevation. Overall, the composite estimators were superior when both precision and bias of estimation were considered. FOR. SCI. 59(5):536 –548.
  • Keywords: Pacific Northwest, Landsat, nearest neighbor imputation, composite estimation, Forest Inventory Analysis
Resource Type
DOI
Date Available
Date Issued
Citation
  • Goerndt, M., Monleon, V., & Temesgen, H. (2013). Small-area estimation of county-level forest attributes using ground data and remote sensed auxiliary information. Forest Science, 59(5), 536-548. doi:10.5849/forsci.12-073
Journal Title
Journal Volume
  • 59
Journal Issue/Number
  • 5
权利声明
Funding Statement (additional comments about funding)
  • This research was supported in part by funds provided by the USDA Forest Service, Pacific Northwest Research Station, Forest Inventory and AnalysisProgram.
Publisher
Peer Reviewed
Language
Replaces

关联

Parents:

This work has no parents.

单件

缩略图 标题 上传日期 公开度 行动
file details TemesgenHailemariamForestEngineeringResourcesManagementSmallAreaEstimation.pdf 2017-07-10 公开 下载