Key messageIntegrating airborne laser scanning and satellite time series data across the forest rotation enhances decision-making in precision forestry. This review supports forest managers by illustrating practical applications of these remote sensing technologies at different stages of intensive forest plantation management-such as site assessment, monitoring, and silviculture-helping improve productivity, sustainability, and operational efficiency.ContextIntensively managed forest plantations depend on high-resolution, timely data to guide silviculture and promote sustainability.AimsThis review explores how airborne laser scanning (ALS) and satellite time series data support precision forestry across key stages, including site assessment, establishment, monitoring, inventory updates, growth tracking, silvicultural interventions, and harvest planning.ResultsThe review highlights several key applications. ALS-derived digital elevation models and canopy metrics improve site productivity estimation by capturing micro-topographic variables and soil formation factors. Combining ALS with multispectral data enhances monitoring of seedling survival and health, although distinguishing seedlings from non-living components remains a challenge. ALS-based Enhanced Forest Inventories provide spatially detailed forest metrics, while satellite time series and vegetation indices support continuous monitoring of growth and early detection of drought, fire, and pest stress. ALS individual tree detection models offer insights into competition, stand structure, and spatial variability, informing thinning and fertilization decisions by identifying trees under stress or with high growth potential. These models also help mitigate drought and wind damage by guiding density and canopy structure management. ALS terrain data further support harvest planning by optimizing machinery routes and reducing environmental impacts.ConclusionDespite progresses, challenges remain in refining predictive models, expanding remote sensing applications, and developing tools that translate complex data into field operations. A major barrier is the technical expertise needed to interpret spatial data and integrate remote sensing into workflows. Continued research is needed to improve accessibility and operational relevance. High-resolution data still offer strong potential for adaptive management and sustainability.

Accurate knowledge of site conditions and their effects on regeneration establishment is important for selecting the most appropriate tree species and regeneration methods for a given regeneration site. This study examined the response of the first-year field performance of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.) and silver birch (Betula pendula Roth.) seedlings in boreal forests to variables available in open forest and natural resources datasets. Survival, height increment and damage of planted tree seedlings and the success of direct seeding of pine were analysed on a total of 284 plots (1000 m(2)) in 18 regeneration experiments established in 2020-2022 in southern and central Finland. The height increment of silver birch was higher than that of conifers, while the lowest mortality rate was found for spruce. In the generalised linear mixed models, topographic wetness index, soil texture, site type and growing stock at clearcut explained the species-specific survival and height increment of planted seedlings and the success of pine seeding. Low-cost, open geospatial data effectively provide useful details on the site conditions suitable for diversifying tree species composition in boreal forests instead of monocultures.

This study aimed to outline areas at risk of the occurrence of eucalypt defoliator caterpillars and their relationship with variations in the spectral behaviour of canopies and soil attributes. The study was conducted in three eucalypt plantation areas of the Bracell Bahia company, located in the state of Bahia, Brazil. Initially, the spatiotemporal distribution of climatic variables and water balance was evaluated. Subsequently, using geographic information systems and fuzzy logic, occurrence risk zoning was developed for defoliator caterpillars associated with different classes of eucalypt crop aptitude. After defining the areas at risk of pest occurrence, specific plots in different aptitude classes were selected to assess, intra-plot, characteristics that can increase or reduce the risk of defoliator caterpillar attack and damage intensity, as well as the plant's ability to recover after a controlled outbreak. Information on the spectral behaviour of the canopies and the availability of nutrients in the soil was used in this step. Zone modelling enabled the delineation of areas and periods at a higher risk of pest occurrence for the different aptitude conditions of the eucalypt crop. The intra-plot methodology proved that the class of eucalypt crop aptitude with the greatest potential for recovering vegetative vigour 60 days after caterpillar damage was the apt class. This result can be attributed to K limitation and the high spatial resolution of the PlanetScope orbital sensor.

Some soil behaviors change significantly as water content varies over time. The particle size distribution of soils has a direct impact on mechanical properties such as soil water content, resistance to dispersion, swelling-shrinkage, fluidity, plasticity, and stickiness. This study was conducted to investigate the usability of Atterberg limits, consistency index and coefficient of linear extensibility (COLE) in the temporal planning of ecosystem restoration activities such as silvicultural interventions, tillage, afforestation, and the construction of forest roads, etc. Surface soil samples were collected from the sections numbered 263, 264, 266, 268, 317, 318, 319, 323, 324,325 and 366 of the degraded forest of the And & imath;r & imath;n forestry operations department. The COLE, liquid limit (LL), plastic limit (PL), plasticity index and consistency index values of soil samples were determined. The LL values ranged from 17.5 to 62.4%, the PL values from 8.2 to 46.8% and the PI values from 6.4 to 15.5. The highest COLE value (0.13) was recorded in the 318, while the lowest COLE value (0.03) was in 325.The LL and PL values have a positive linear relationship with clay and organic matter content. All sections have karstic characteristics, but the mechanical characteristics of the soils differ significantly between the sections. Silvicultural interventions carried out especially in 318, which had the lowest consistency index (Ic = 0.70), and sections 263, 264, 317 and 319, where the consistency index is >2,should take mechanical properties into account, and the planting time intervals should be determined, accordingly for sustainable forestry.