Although trees growing outside forests are less perceived in relation to those inside forests, they are also valuable and serve various functions. The biophysical thresholds of Trees Outside Forests (TOF) were recently defined and standardised by the Global Forest Resources Assessments of the United Nations Food and Agricultural Organization (UNFAO-FRA). With these definitions, standardised mapping of TOF resources became feasible at the national and international level. Here, we aimed to fill the spatial information gap of TOF resources at the national scale with an automated mapping approach based on the UNFAO-FRA definition. The approach was carried out in ArcGIS using adapted UNFAO-FRA biophysical thresholds with routinely acquired countrywide remote sensing data for the whole of Switzerland: a Vegetation Height Model (VHM), a Topographic Landscape Model (TLM Regio) land cover map, and a Forest Mask. Results were validated using stereo-image interpretation data of the Swiss National Forest Inventory (NFI), which verified 95%, 55% and 75% of overall, producer’s and user’s accuracy, respectively. Of the five forest production regions in Switzerland, the highest accuracy was achieved in the Central Plateau and the lowest in the Alps, with accuracy generally decreasing with increasing elevation. Omission and commission errors were highly correlated with the vertical and horizontal accuracy of the VHM, and the applied biophysical thresholds caused both types of error. The final TOF map produced with our approach is at the countrywide scale, is superior to existing TOF information, meets UNFAO-FRA management and reporting needs, and enables the derivation of TOF’s biomass, carbon sequestration potential and species distribution for the whole country.

尽管与森林内部的树木相比，森林以外的树木被人们所感知的较少，但它们也很有价值并且具有多种功能。最近，联合国粮食及农业组织（UNFAO-FRA）的全球森林资源评估确定并标准化了森林外树木的生物物理阈值（TOF）。有了这些定义，就可以在国家和国际层面对TOF资源进行标准化的制图。在这里，我们旨在通过基于UNFAO-FRA定义的自动制图方法，在全国范围内填补TOF资源的空间信息空白。该方法是在ArcGIS中使用经过调整的UNFAO-FRA生物物理阈值和常规获取的整个瑞士的全国范围的遥感数据进行的：植被高度模型（VHM），地形景观模型（TLM Regio）土地覆盖图和森林面具。使用瑞士国家森林清单（NFI）的立体图像解释数据验证了结果，该数据分别验证了95％，55％和75％的总体准确性，生产者和用户的准确性。在瑞士的五个森林产区中，中部高原地区的精度最高，而阿尔卑斯山地区则最低，精度通常随着海拔的升高而降低。遗漏和委托误差与VHM的垂直和水平精度高度相关，并且所应用的生物物理阈值导致两种类型的误差。用我们的方法制作的最终TOF地图在全国范围内，优于现有的TOF信息，满足了UNFAO-FRA的管理和报告需求，并能够推导TOF的生物量，