Methods for evaluating the utilities of local and global maps for increasing the precision of estimates of subtropical forest area

作     者：McRoberts, Ronald E. Vibrans, Alexander C. Sannier, Christophe Naesset, Erik Hansen, Matthew C. Walters, Brian F. Lingner, Debora V. 

作者机构：US Forest Serv No Res Stn St Paul MN USA Univ Reg Blumenau Blumenau SC Brazil Syst Informat Reference Spatiale Villeneuve Dascq France Norwegian Univ Life Sci Dept Ecol & Nat Resource Management As Norway Univ Maryland Dept Geog Sci College Pk MD 20742 USA 

出 版 物：《CANADIAN JOURNAL OF FOREST RESEARCH》 (加拿大林业研究杂志)

年 卷 期：2016年第46卷第7期

页      面：924-932页

核心收录：

学科分类：0907[农学-林学] 08[工学] 0829[工学-林业工程] 09[农学] 

基　　金：Fundacao de Amparo a Pesquisa e Inovacao de Santa Catarina (FAPESC) Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) 

主　　题：logistic regression model inference Santa Catarina Brazil 

摘      要：For a study area in the Brazilian state of Santa Catarina, the utilities of local and global forest maps in combination with poststratified and model-assisted estimators for increasing the precision of estimates of forest area were compared. Auxiliary information was in the form of local maps, the recent Global Forest Change map, and combinations of these maps. The poststratified estimators produced estimates of greater precision than the model-assisted regression estimators for maps of categorical variables, but the model assisted estimators produced estimates of greater precision for maps of continuous variables. The Global Forest Change map was the least accurate of all the maps, but it produced estimates of forest area that were similar to those for the other maps and that were more precise than if the map had not been used. Thus, the Global Forest Change map may be an attractive option if local maps are not available or cannot be constructed. The primary contributions of the study are two-fold. First, this is one of the first case studies that rigorously assess the utility of global maps for national estimation. After accumulation of a few more such studies, broader generalizations should be forthcoming. Second, a statistical basis is provided for the previously unexplained greater precision for poststratified estimators than for model-assisted estimators.