the greenhouse effect and climate change [6; 7; 8]. Introduced tree stands in post-industrial areas play a significant role in the formation of specific microclimates and reforestation success. Appropriate control of vegetation growth, assessment of the productivity, including biomass, and the quality of the stands are indicators of the success of reclamation [6]. Thus, conducting research using remote sensing methods is very important for observing and conducting monitoring in reclaimed areas.  
Remote sensing data and geoinformation technologies can support studies on the dynamics of LULC changes and vegetation progression [9; 10; 11; 12; 13]. Geospatial technologies offer a significant opportunity to execute large-scale studies on biomass mapping. PlanetScope's satellites include more than 150 nanosatellites and provide a unique dataset of Earth-based observations. With a unique combination of resolution, coverage, and frequency, PlanetScope can take daily images anywhere on the Earth with a 3 m resolution. PlanetScope provides the data necessary to develop geospatial insights about the speed of LULC changes. By providing the best possible images, PlanetScope allows one to monitor areas of interest, validate information on the ground, and discover relevant trends [14].  
Light detection and ranging (LiDAR), especially airborne laser scanning (ALS), has great potential in studying vegetation formation [15; 16; 17; 18] based on the relative values of tree and bush heights according to the ground surface. These values are determined through ground topography models, such as the digital terrain model (DTM) and digital surface model (DSM). The normalized DSM (nDSM) is the difference between DSM and DTM (nDSM = DSM \(-\) DTM) [19]. Airborne laser scanning technology collects 2D and 3D information that helps establish the spatial characteristics of vegetation [20; 21; 22; 23; 24; 25; 26; 27]. It is highly important for the inventory and monitoring of afforestation and forest succession to provide information about biomass according to the EU Biodiversity Strategy [28], the National Program for Increasing Forest Cover [29], and actual information on forested grounds [30; 31; 32].  
This research aimed to investigate the possibility of integrating remote sensing data and geoinformation technologies for the automated monitoring of afforested and secondary forest succession areas in post-industrial grounds. The study intended to determine the ability to derive spatial information for precisely mapping the range and structure of forest succession vegetation according to biodiversity and biomass monitoring in a post-mining, reclaimed study area. The objective was to integrate land cover monitoring based on satellite imagery classification and the characteristics of vegetation based on LiDAR point clouds as 2D and 3D metrics to obtain information, e.g., about the height of the vegetation and the canopy cover. The fusion of satellite imageries with the ALS data provided an unprecedented dataset for observations, helping us better understand the land cover condition changes. The most important contributions of this study are its demonstration of the correctness of, and a possibility to integrate, various remote sensing materials, i.e., satellite images and airborne LIDAR point clouds, for the monitoring of forest phytocoenoses on degraded grounds.