In the recent decades, growing demand for wood products, combined with efforts to conserve natural forests, has supported a steady increase in the global extent of planted forests. In this paper, a two-phase sampling strategy for large-scale assessment of hybrid poplar plantations in Northern Italy was implemented. The first phase was performed by means of tessellation stratified sampling on high-resolution remotely sensed imagery, covering the survey area by a grid of regular polygons of equal size and randomly and independently selecting one point per quadrat. All the plantations spotted by at least one sample point were selected. In the second phase, we randomly chosen a subset of plantations by stratified sampling that were visited on the ground to collect qualitative and quantitative attributes. The resulting estimates were reliable, and the survey demonstrated relatively easy to be implemented and replicated. These considerations support the use of the proposed sampling strategy to frequently update information on fast-growing forest plantations within agricultural farms, like hybrid poplar crops. Moreover, the results of the case study here presented highlight the relevance of hybrid poplar plantations in Italy, in the context of sustainable development strategies under a green economy perspective.

中文翻译：

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意大利北部杨树种植园大规模评估的概率抽样和估计

近几十年来，对木制品的需求不断增长，再加上保护天然林的努力，支持了全球人工林面积的稳步增长。在本文中，实施了意大利北部杂交杨树种植园大规模评估的两阶段抽样策略。第一阶段是通过对高分辨率遥感影像进行镶嵌分层采样，用大小相等的规则多边形网格覆盖调查区域，每个样方随机独立地选择一个点。选择至少一个采样点发现的所有种植园。在第二阶段，我们通过分层抽样随机选择了一个种植园子集，实地考察以收集定性和定量属性。结果估计是可靠的，并且调查显示相对容易实施和复制。这些考虑支持使用提议的抽样策略来频繁更新农业农场内快速生长的人工林的信息，如杂交杨树作物。此外，这里介绍的案例研究结果突出了意大利杂交杨树种植园在绿色经济视角下的可持续发展战略背景下的相关性。