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

机译:评估局部和全局地图的效用以提高亚热带森林面积估计精度的方法

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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.
机译:对于巴西圣卡塔琳娜州的研究区域,比较了本地和全球森林地图与后分层和模型辅助估计器的结合,以提高森林面积估计的准确性。辅助信息包括本地地图,最近的全球森林变化地图以及这些地图的组合。对于分类变量图,后分层估计器的估计精度比模型辅助回归估计器的精度高,但是对于连续变量图,模型辅助估计器的精度更高。全球森林变化地图是所有地图中精度最低的地图,但它产生的森林面积估算值与其他地图相似,并且比未使用该地图时更为精确。因此,如果本地地图不可用或无法构建,全球森林变化地图可能是一个有吸引力的选择。该研究的主要贡献有两个方面。首先,这是第一个严格评估全球地图对国家估算的效用的案例研究之一。在积累了更多此类研究之后,应该会进行更广泛的概括。其次,为后分层估计量提供了比模型辅助估计量更精确的统计基础。

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