The cessation of most human activities resulting from post‐World War II expulsions and forced displacements in Central Europe triggered massive land cover transformation in mountainous areas. However, many pre‐War traces of past landscapes have survived—imprinted in microtopography—in permanently abandoned villages. Currently, they constitute unique cultural heritage of communities no longer in existence. Our main goal was therefore to reconstruct a lost cultural landscape of mountain villages abandoned after World War II (WWII). The case study area comprised three such villages located in southern Poland, two in the Carpathians and one in the Sudetes. We used the national airborne light detection and ranging (LiDAR) dataset combined with archival cadastral maps and field survey to detect man‐made microtopographic features related to past boundaries, road network, agriculture and buildings and to interpret them in the landscape context. We demonstrated that the pre‐War human footprint left in relief was shaped largely by past landownership divisions, land use and environmental constraints (related to lithology, soils and topography). Our secondary goal was to assess the value and application opportunities of LiDAR in reconstructing past landscapes. We showed that 38–70% of non‐natural parcel boundaries and 65–79% of roads marked on mid‐19th‐century cadastral maps are still detectable using LiDAR. Therefore, we argue that the past landscape pattern, originating in late Middle Ages and subsequently transformed prior to WWII, remains well preserved in the relief and that LiDAR is an effective tool to reconstruct a past landscape of mountain villages abandoned after WWII. We also confirmed that customized LiDAR visualizations are more informative than ready‐to‐use shaded digital elevation models (DEMs), in particular when integrated with cadastral and field‐based data. We conclude that the greatest advantage of LiDAR is the capacity to provide a landscape context for isolated traces of past human activity, allowing for the reconstruction of entire spatial patterns and interrelationships developed by past societies.

Post-WWII displacements in the Polish Carpathians resulted in widespread land abandonment. Most of the pre-war agricultural areas are now covered with secondary forests, which will soon reach the felling age. Mapping their exact cover is crucial to investigate succession–regeneration processes and to determine their role in the landscape, before making management decisions. Our goal was to map post-agricultural forests in the Polish Eastern Carpathians using archival remote sensing data, and to assess their connectivity with pre-displacement forests. We used German Flown Aerial Photography from 1944 to map agricultural lands and forests from before displacements, and Corona satellite images to map agricultural lands which converted into the forest as a result of this event. We classified archival images using Object-Based Image Analysis (OBIA) and compared the output with the current forest cover derived from Sentinel-2. Our results showed that mature (60–70 years old) post-agricultural forests comprise 27.6% of the total forest area, while younger post-agricultural forests comprise 9%. We also demonstrated that the secondary forests fill forest gaps more often than form isolated patches: 77.5% of patches are connected with the old-woods (forests that most likely have never been cleared for agriculture). Orthorectification and OBIA classification of German Flown Aerial Photographs and Corona satellite images made it possible to accurately determine the spatial extent of post-agricultural forest. This, in turn, paves the way for the implementation of site-specific forest management practices to support the regeneration of secondary forests and their biodiversity.