Site productivity remains a fundamental concern in forestry as a significant driver of resource availability for tree growth. The site index (SI) reflects the overall impact of all environmental ...factors that determine tree height growth and is the most commonly used indirect proxy for forest site productivity estimated using stand age and height. The SI concept challenges are local variations in climate, soil, and genotype-environmental interactions that lead to variable height growth patterns among ecoregions and cause inappropriate estimation of site productivity. Developing regional models allow us to determine forest growth and SI more appropriately. This study aimed to develop height growth models for the Scots pine in Poland, considering the natural forest region effect. For height growth modelling, we used the growth trajectory data of 855 sample trees, representing the Scots pine entire range of geographic locations and site conditions in Poland. We compared the development of regional height growth models using nonlinear-fixed-effects (NFE) and nonlinear-mixed-effects (NME) modelling approaches. Our results indicate a slightly better fit to the data of the model built using NFE approach. The results showed significant differences between Scots pine growth in natural forest regions I, II, and III located in northern Poland and natural forest regions IV, V, and VI in southern Poland. We compared the development of regional height growth models using NFE and NME modelling approaches. Our results indicate a slightly better fit to the data of the model built using the NFE approach. The developed models show differences in height growth patterns of Scots pines in Poland and revealed that acknowledgement of region as the independent variable could improve the growth prediction and quality of the SI estimation. Differences in climate and soil conditions that distinguish natural forest regions affect Scots pine height growth patterns. Therefore, extending this research to models that directly describe height growth interactions with site variables, such as climate, soil properties, and topography, can provide valuable forest management information.
•Accurate detection of tree-cutting remains a significant scientific challenge.•A novel approach was proposed based on PlanetScope images and machine learning.•A high tree-cutting detection rate was ...achieved with a RF model.•The generalization testing confirmed the performance of the object-based RF model.
Despite utilizing various remote sensing datasets, precise tree-cutting detection remains challenging due to spatial and spectral resolution constraints in satellite imagery, complex landscapes, data integration issues, and the need for accurate multi-temporal reference datasets. This study investigates the utilization of PlanetScope (PS) satellite images, along with pixel-based (PBIA) and object-based (OBIA) image analysis, for accurate mapping of forest cover and detection of tree cuttings. Detailed multi-temporal reference datasets were collected based on airborne laser scanning (ALS)-derived canopy height models (CHM) and very high-resolution (VHR) aerial orthomosaics. Reference datasets were used to train three machine learning (ML) models: random forest (RF), support vector machine (SVM), and feed-forward neural network (Nnet) in two forest districts located in Western and Northern Poland. The study also assessed the generalization capabilities of the best model in both local and temporal contexts. Regarding forest cover mapping, the OBIA RF classifier outperformed all other models with an overall accuracy (OA) of 99.27 % and Kappa of 98.18 %, while the PBIA SVM model showed the lowest (OA = 97.18 %, Kappa = 94.35 %). The testing of the model's generalization confirmed the performance of the OBIA RF model, with the Dice Coefficient ranging from 95.86 % to 96.74 %. The methodology's effectiveness in tree-cutting detection was demonstrated, with the detection rate ranging from 96.20 % to 99.39 % for the total number of cuttings, and from 99.45 % to 99.86 % for the total volume. In conclusion, the integration of PS satellite images, spectral-textural features, and generalized ML models proves to be effective for tree-cutting detection.
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•100th percentile of point cloud and ITD approach gives a reliable stand height increment estimate.•The use of 99th and 95th percentile of point cloud result in underestimation of ...height increment.•Growth trajectories calculated using different grid cell size are nearly identical.•ALS data can be a good substitute for the inventory plot data in height growth modeling.
Site productivity and forest growth are critical inputs into projecting wood volume and biomass accumulation over time. Site productivity, which is determined most commonly using site index models is also the primary criterion to consider many forest management decisions. Most of the previous research utilizing the remote sensing data for assessment of site index with forest height are based on the existing site index models developed with traditional dendrometric methods. However, these traditional methods are both time-consuming and expensive. This study demonstrates how bi-temporal airborne laser scanning (ALS) data collected within the 8-year period can be used for the development of site index models for Scots pine. The accuracy of ALS-derived models was assessed by comparison to the reference site index model developed based on data from stem analysis of 174 felled Scots pine trees. We evaluated the effect of different height metrics and grid cell size on the trajectory of site index models developed from ALS-derived measurements. Four methods of estimating top height from ALS point clouds were evaluated: 95th, 99th and 100th percentiles of point clouds and an individual tree detection approach (ITD). The models were created for a range of grid cell sizes: 10 × 10 m, 30 × 30 m, and 50 × 50 m. The results indicate that bitemporal ALS data could substitute traditional methods that have been applied to date for stand growth modelling. It was found that top height increment can be estimated by using both ITD approach and the 100th percentile of point cloud giving an appropriate top height (TH) increment estimation. Observed growth curves of reference trees agreed best with the trajectories that were obtained based on TH calculated using ITD method (R2 = 0.892) and 100th percentile (R2 = 0.797). In case of TH obtained from 99th and 95th percentiles only weak correlation was found: R2 = 0.358 and R2 = 0.213, accordingly. The height growth models developed with 95th and 99th percentiles of point cloud were not compatible with the reference model. We also found that grid cell size did not affect the model height growth trajectories. Irrespective of the grid cell size, the obtained model trajectories for the given method of TH estimation are nearly identical for cells 10 × 10, 30 × 30 and 50 × 50 m.
Differing levels of humidity, sunlight exposure or temperature in different areas of mountain ranges are fundamental to the existence of particular vegetation types. A better understanding of even ...local variability of trees may bring significant benefits, not only economic, but most of all, nature-related. The main focus of this study was the analysis of relationships between increment in stand height, age and the natural topography in the examined area. Among others, the following were examined with regard to their influence on the growing process: age, altitude above sea level (m a.s.l.), aspect and slope, topographic wetness index (TWI), and topographic position index (TPI) generated from an airborne laser scanning (ALS)-derived elevation model. To precisely calculate forest growth dynamics in mountain conditions for different spruce stands, repeated airborne lidar measurements from 2007 and 2012 were used (with resolution respectively 4 and 6 pts./m2). Detailed information on every stand including species composition, share of individual species, as well as their age, were acquired from the State Forests IT System (SILP). It was proven in this study, that environmental and topographic variables may have an impact on forest growth dynamics on even closely located areas. Apart from the age, the greatest influence on tree growth has an altitude above sea level, aspect and slope. The highest height increment of spruce was observed in the stands of up to 30 years old, those that had grown at an altitude under 850 m a.s.l., on the slopes up to 15 degrees or on those which were on the northeastern exposure. The results obtained show that the physiology of species, even those that are well known, largely depends on local topographic conditions. The proven impact of different topography factors on the growth of spruce may be used while planning economic activities in precision forestry. Additional research with using multiple laser scanning in the context of other regions or other species may bring us better recognition of local growth conditions and in consequence, significantly better planning and higher revenues obtained from the sale of trees.
Purpose of Review
The increasing availability of three-dimensional point clouds, including both airborne laser scanning and digital aerial photogrammetry, allow for the derivation of forest inventory ...information with a high level of attribute accuracy and spatial detail. When available at two points in time, point cloud datasets offer a rich source of information for detailed analysis of change in forest structure.
Recent Findings
Existing research across a broad range of forest types has demonstrated that those analyses can be performed using different approaches, levels of detail, or source data. By reviewing the relevant findings, we highlight the potential that bi- and multi-temporal point clouds have for enhanced analysis of forest growth. We divide the existing approaches into two broad categories— – approaches that focus on estimating change based on predictions of two or more forest inventory attributes over time, and approaches for forecasting forest inventory attributes. We describe how point clouds acquired at two or more points in time can be used for both categories of analysis by comparing input airborne datasets, before discussing the methods that were used, and resulting accuracies.
Summary
To conclude, we outline outstanding research gaps that require further investigation, including the need for an improved understanding of which three-dimensional datasets can be applied using certain methods. We also discuss the likely implications of these datasets on the expected outcomes, improvements in tree-to-tree matching and analysis, integration with growth simulators, and ultimately, the development of growth models driven entirely with point cloud data.
Forest stand reflectance at the canopy level results from various factors, such as vegetation chemical properties, leaf morphology, canopy structure, and tree sizes. These factors are dependent on ...the species, age, and health statuses of trees, as well as the site conditions. Sentinel-2 imagery with the high spatial, spectral, and temporal resolution, has enabled analysis of the relationships between vegetation properties and their spectral responses at large spatial scales. A comprehensive study of these relationships is needed to understand the drivers of vegetation spectral patterns and is essential from the point of view of remote sensing data interpretation. Our study aimed to quantify the site and forest parameters affecting forest stands reflectance. The analysis was conducted for common beech-, silver fir- and Scots pine-dominated stands in a mountainous area of the Polish Carpathians. The effect of stands and site properties on reflectance in different parts of the growing season was captured using the dense time series provided by Sentinel-2 from 2018-2019. The results indicate that the reflectance of common beech stands is mainly influenced by elevation, particularly during spring and autumn. Other factors influencing beech stand reflectance include the share of the broadleaved understory, aspect, and, during summer, the age of stands. The reflectance of coniferous species, i.e., Scots pine and silver fir, is mainly influenced by the age and stand properties, namely the crown closure and stand density. The age is a primary driver for silver fir stands reflectance changes, while the stand properties have a large impact on Scots pine stands reflectance. Also, the understory influences Scots pine stands reflectance, while there appears to be no impact on silver fir stands. The influence of the abovementioned factors is highly diverse, depending on the used band and time of the season.
•Scots pine mortality is driven by climatic water balance.•The probability of drought-induced mortality is affected by stand age and site index.•The oldest stands show the highest susceptibility to ...drought-induced mortality.•Enhanced mortality probability is observed in most productive sites.
Warmer and drier conditions increase forest mortality worldwide. At the same time, nitrogen deposition, longer growing seasons and higher atmospheric CO2 concentrations may increase site productivity accelerating forest growth. However, tree physiological studies suggest that increased site productivity can also have adverse effects, reducing adaptation to drought. Understanding such intricate interactions that might foster tree mortality is essential for designing activities and policies aimed at preserving forests and the ecosystem services they provide. This study shows how site factors and stand features affect the susceptibility of Scots pine to drought-induced stand-level mortality. We use extensive forest data covering 750,000 ha, including 47,450 managed Scots pine stands, of which 2,547 were affected by mortality during the drought in 2015–2019. We found that the oldest and most dense stands growing on the most productive sites showed the highest susceptibility to enhanced mortality during drought. Our findings suggest that increasing site productivity may accelerate the intensity and prevalence of drought-induced forest mortality. Therefore, climate change may increase mortality, particularly in old and high-productive forests. Such exacerbated susceptibility to mortality should be considered in forest carbon sink projections, forest management, and policies designed to increase resilience and protect forest ecosystems.
The contribution of Douglas-fir (Df) to European forests is likely to increase as the species is a potential adaptation option to climate change. In this study, we investigated growth and survival of ...Df seed sources to fill a knowledge gap regarding recommendations for the future use of Df provenances in Poland. Our experimental test site represents the most continental climate among all Df trials installed in the IUFRO 1966–67 test series in Europe. At this unique single site, we evaluated the performance of 46 Df provenances from North America, and nine local landraces of unknown origin. Repeated measurements of tree diameter, height, and volume were analysed, to age 48, representing integrated responses to geographic and climatic conditions. Significant variation in survival and productivity-related traits were found, with the interior Df provenances performing best, in contrast to previous European reports. The higher survivability and volume of the interior provenances resulted from their superior frost resistance. The low precipitation seasonality at the location of seed origin provided an additional advantage to the trees at the test site. Geographic and climatic factors of seed origin explained most of the variation in productivity (77 and 64%, respectively). The tested landraces exhibited diverse performance, implying that naturalized local seed sources in Poland need improvement and perhaps enrichment with new genetic material from North America, while considering geography and climate. Assisted migration programs should consider the limitations imposed by both frost and drought events in guiding future Df selections for continental climates. Further field testing, early greenhouse screening and DNA testing are also recommended.
Site productivity provides critical information for forest management practices and is a fundamental measure in forestry. It is determined using site index (SI) models, which are developed using two ...primary groups of methods, namely, phytocentric (plant-based) or geocentric (earth-based). Geocentric methods allow for direct site growth modelling, in which the SI is predicted using multiple environmental indicators. However, changes in non-static site factors—particularly nitrogen deposition and rising CO2 concentration—lead to an increase in site productivity, which may be visible as an age trend in the SI. In this study, we developed a geocentric SI model for oak. For the development of the SI model, we used data from 150 sample plots, representing a wide range of local topographic and site conditions. A generalized additive model was used to model site productivity. We found that the oak SI depended predominantly on physicochemical soil properties—mainly nitrogen, carbon, sand, and clay content. Additionally, the oak SI value was found to be slightly shaped by the topography, especially by altitude above sea level, and topographic position. We also detected a significant relationship between the SI and the age of oak stands, indicating the long-term increasing site productivity for oak, most likely caused by nitrogen deposition and changes in climatic conditions. The developed geocentric site productivity model for oak explained 77.2% of the SI variation.
Over the past decade, the presence of mistletoe (Viscum album ssp. austriacum) in Scots pine stands has increased in many European countries. Understanding the factors that influence the occurrence ...of mistletoe in stands is key to making appropriate forest management decisions to limit damage and prevent the spread of mistletoe in the future. Therefore, the main objective of this study was to determine the probability of mistletoe occurrence in Scots pine stands in relation to stand-related endogenous factors such as age, top height, and stand density, as well as topographic and edaphic factors. We used unmanned aerial vehicle (UAV) imagery from 2,247 stands to detect mistletoe in Scots pine stands, while majority stand and site characteristics were calculated from airborne laser scanning (ALS) data. Information on stand age and site type from the State Forest database were also used. We found that mistletoe infestation in Scots pine stands is influenced by stand and site characteristics. We documented that the densest, tallest, and oldest stands were more susceptible to mistletoe infestation. Site type and specific microsite conditions associated with topography were also important factors driving mistletoe occurrence. In addition, climatic water balance was a significant factor in increasing the probability of mistletoe occurrence, which is important in the context of predicted temperature increases associated with climate change. Our results are important for better understanding patterns of mistletoe infestation and ecosystem functioning under climate change. In an era of climate change and technological development, the use of remote sensing methods to determine the risk of mistletoe infestation can be a very useful tool for managing forest ecosystems to maintain forest sustainability and prevent forest disturbance.
•ALS and UAV data allow for assessing the probability of mistletoe occurrence.•The densest, tallest, and oldest stands were more susceptible to mistletoe infestation.•Site type, topography, and CWB were also important factors driving mistletoe occurrence.
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