Forest clear-cuts, as both a forestry technique and a direct spatial consequence of forestry, are currently being phased out in Europe (European Commission, 2020, 2021). However, clearings resulting from this long-standing landscape practice will remain across various forested regions of Europe for the foreseeable future. The physical traces derived from forest clear-cutting may hold potential landscape heritage value, as they are the remnants of an important cultural landscape undergoing drastic change due to its environmental impacts. Despite their ubiquitous presence, valuable clearings are hidden in plain sight. Sufficient attention is not given yet to their spatial qualities: they are not cataloged geographically and have yet to be incorporated into landscape surveys documenting the digital and physical heritage of European cultural landscapes. The techniques explored in this article are twofold: first is to develop a method for identifying the clearings, and second is to provide sufficient geometric information to value and categorize the shapes of selected clearings. Among various potential uses that such visualizations can illustrate, the most promising appears to be determining previously underrepresented landscape configurations based on perceived formal parameters applicable to landscape heritage and other cases wherein geometric information might be needed. The outcome is a novel model for the localization, identification, and geometric processing of forest clearings within the geographical scope of Europe. This model is executed through connecting the cloud computing capabilities and extensive data catalogs of Google Earth Engine with effective image segmentation based on the Meta Segment Anything Model and several open-source geospatial data analysis tools developed for geometric processing. Hansen Global Forest Change data is employed to detect disturbances in forest patterns on a global scale, serving as a preliminary filter to identify forest clearings in multiple national, high-resolution, color infrared (CIR), orthoimagery acquisitions across Finland, Latvia, and Germany. Expanding on the geographical scope of our previous study, the present methodology allows us to efficiently identify, filter, select, and process a rich set of sample clearings. For each clearing, a series of infrared image tiles, precise outlines, and geometric synthetizations are produced. Furthermore, outlines and abstract geometries in plan view are categorized in relation to their spatial location. While the collection of clearings could be expanded further, including other European countries, we offer a systematic, robust, and innovative approach that integrates different methods and data through a single accessible and centralized interface. Classification and segmentation models commonly used in the geosciences serve to determine landscape typologies and observe their transformations. However, they may be inherently limited in detecting geometrically fuzzy or temporarily unstable objects and surfaces. This research not only challenges the limitations of some of these tools and methods but also provides a clear workflow for identifying, collecting, categorizing, comparing, and ultimately valuing the complex shapes of forest clearings on a European scale.