## 5 Discussion
Increases in comparability, reliability, and efficiency are some benefits of using PlanetScope satellite imageries, LiDAR data, and automated procedures for detecting and monitoring afforestation. With a unique combination of high resolution and frequency, using PlanetScope and LiDAR data processing, we were able to provide the objective information necessary to produce geospatial insights into LULC classes in the reclaimed areas. In this study, we indicated the sequence of automated PlanetScope image processing and LiDAR point cloud metrics determination to obtain precise, objective, and validated information about the location, range, and spatial structures of the trees and shrubs formed or developed in post-industrial areas. Using PlanetScope imageries, we observe more precise characteristics of the transitional woodland shrub and broad-leaved or coniferous forest. PlanetScope satellite constellation utilization is expected to expand in the future, so this research is useful for readers who are considering the use of satellite data in the future. The authors investigated the possibility of applying the newest PlanetScope imageries for automated LULC classification in the reclaimed Jeziorko area, as forest succession mapping is an important issue in this post-mining terrain. Using ALS point clouds allowed us to analyze the vegetation canopy profiles and metrics and, in this case, study automation for monitoring the forest succession process [66; 67; 68]. We stated that image processing and LiDAR point clouds provide accurate information about forested areas. Alternatives for ALS data include point clouds derived using unmanned aerial vehicles (UAVs) [69; 70; 71; 72]. The stereo-matching method of UAVs and aerial photographs offer management, monitoring, and precise information about reclaimed areas [73; 74; 75]. In this case, the availability of a precise DTM derived from ALS that does not change for many years is important. Once obtained, e.g., from the ISOK project (ALS campaign in Poland), these data can be used for many studies. The automated ALS point cloud processing method presented in this study offers the possibility for vegetation growth assessment. Cyclic PlanetScope imageries and LiDAR data processing can provide the time-series mapping LULC changes taking place in reclaimed post-mining areas. Further, regular airborne scanning or UAV campaigns can derive the spatial characteristics of biomass. The study of individual environmental elements conducted at the former Jeziorko sulfur mine (for soil, surface water, plant reaction, and their nutritional conditions), supplemented with the use of modern geomatics technologies, enables a composite evaluation of the state of the restored ecosystem. Among other factors, land-cover categories were distinguished (with pine and birch woody vegetation in stands and areas without vegetation, the so-called degraded categories), which may allow for the precise positioning and establishment of permanent control areas in the field for detailed physicochemical tests. In addition, the use of modern technologies allowed monitoring of the conditions in areas of former sulfur mining at the Jeziorko mine (without having to explore the entire area), where excessive sulfur concentrations in the soil create the area a dynamic system. The present research on Jeziorko showed an increase in forested areas. Therefore, we conclude that automated remote sensing processing was useful for mapping the 3D characteristics of the analyzed affected post-industrial areas. A combination of satellite imageries and LiDAR data provided reliable results and may be used for the automated monitoring of forest succession in this degraded area in the future. Landscape and vegetation information and land cover mapping history can be used to assess the long-term restoration habitats according to the directions of reclamation, especially for woodland afforestation.