•Developed top height-age model using ALS data covering all aged stands.•Derived site-specific height growth trajectories from repeated ALS.•ALS height-age model described height-age data from stem ...analysis adequately well.•ALS data can be good substitute to the data from stem analysis and sample plots.
Forest site productivity, which is a quantitative estimate of the potential of a site to produce plant biomass, remains a fundamental variable in forestry. The most commonly used and widely accepted method of evaluating site productivity is the site index. Therefore, the construction of site index models describing top height (TH) growth with age remains a fundamental task for site productivity differentiation. Three main data sources have been used for site index model development to date: (1) repeated measurements on permanent sample plots (PSP); (2) temporary sample plot (TSP) data from periodic inventories; and (3) stem analysis (SA) data. Our study is practical application of change detection using airborne laser scanners for the development of top height growth models. We demonstrated how wall-to-wall airborne laser scanner (ALS) data obtained for large forest areas can be used in developing top height growth models for Norway spruce that appropriately reflect site-specific growth trajectories. Site specific growth trajectories were successfully captured by repeated height measurements using ALS data from notably short 5-year period, which indicates that such a period between subsequent ALS observations is sufficient and surmounts the noise and other uncertainties connected with ALS systems and interannual TH growth variations. Height increment obtained by change detection using repeated airborne laser scanning (ALS) may be recognized as a new, fully valuable data source for TH growth and site index modelling. Repeated ALS observations can be a substitute for height growth data used in site index modelling and collected to-date from SA, PSP or TSP. It could be expected that improving ALS technologies, decreasing costs of laser scanning acquisition and increasing data availability will result in improving the accuracy of forest height growth estimates. Therefore, in the near future, both utility and increasedpredictive validity will lead to substantial increases in the importance of change detection using airborne laser scanners in forest growth modelling using the data from repeated ALS measurements.
Background
Remote sensing techniques and data are becoming increasingly popular in forest management, e.g. for change detection and health condition analysis. Tree species recognition is a ...fundamental issue in taking forest inventories, especially in carbon budget modelling. Hyperspectral imagery provides an accurate classification results for large areas based on a relatively small amount of training data.
Results
A hyperspectral image of a forest stand in north-eastern Poland taken using an AISA (Airborne Imaging Spectrometer for Application) Eagle camera was transformed to extract the most valuable spectral differences and was classified into seven tree types (birch, European beech, oak, hornbeam, European larch, Scots pine, and Norway spruce) using nine classification algorithms. The highest overall accuracy and kappa coefficient were 90.3% and 0.9 respectively using three minimum noise fraction bands and maximum likelihood classifier.
Conclusions
Hyperspectral imaging of forests can be used to classify major forest tree species with a good degree of accuracy. It is time-efficient and user-friendly; however, the data and software required means that this approach is still expensive at present.
The increase in the deer population observed in recent decades has strongly impacted forest regeneration and the forest itself. The reduction in the quality of raw wood material, as a consequence of ...deer-mediated damage, constitutes a significant burden on forest owners. The basis for the commencement of preventive actions in this setting is the understanding of the populations and behaviors of deer in their natural environment. Although multiple studies have been carried out regarding this subject, only a few suggested topography as an important factor that may influence the distribution and intensity of deer-mediated damage. The detailed terrain models based on LiDAR data as well as the data on damage caused by deer from the State Forests database enabled thorough analyses of the distribution and intensity of damage in relation to land form in this study. These analyses were performed on three mountain regions in Poland: the Western Sudety Mountains, the Eastern Sudety Mountains, and the Beskidy Mountains. Even though these three regions are located several dozen to several hundred kilometers apart from each other, not all evaluated factors appeared common among them, and therefore, these regions have been analyzed separately. The obtained results indicated that the forest damage caused by deer increased with increasing altitude above 1000 m ASL. However, much larger areas of damage by deer were observed at elevations ranging from 401 to 1000 m ASL than at elevations below 400 m ASL. Moreover, the locations of damage (forest thickets and old stands) indicated that red deer is the species that exerts the strongest pressure on forest ecosystems. Our results show the importance of deer foraging behavior to the structure of the environment.
•Repeated ALS allows detecting short-term variation of the height increment.•Mean annual precipitation sum affects the height increment of Norway spruce.•Repeated ALS allows developing ...weather-sensitive height growth models.
Fluctuations in weather conditions, particularly precipitation and water availability, may strongly affect growth rate patterns and lead to interannual height growth variation. Consequently, height growth models developed using airborne laser scanning (ALS) data collected at short time intervals may over- or underestimate long-term height growth trends and finally result in different growth forecasts. The objective of this study was to develop height growth models for Norway spruce, including the effect of weather conditions. We used ALS-derived top height (TH) estimates and meteorological data from the research area collected for 2007-2012 and 2013-2018 to develop a weather-sensitive height growth model. The top height (TH) growth of Norway spruce was affected by the mean annual precipitation sum (APS) in the studied periods, and a higher APS resulted in faster TH growth. This study demonstrates the high potential of repeated ALS for detecting short-term variation in the tree height increment and the development of weather-sensitive height growth models.
The main aim of the work presented here has been to evaluate which combination of filtering and interpolation algorithms can offer the best DTM accuracy in conditions involving very dense forest in ...mountainous areas. The study area was in the Sudety Mountains of southwestern Poland, close to the Czech border. For each filtration, almost 100 DTMs were generated, with final analysis confined to just 6 most-accurate models. The results show that slope and particularly undergrowth vegetation are the most important factors influencing DTM accuracy in dense mountain forests. However, all methods of interpolation are capable of reaching very similar levels of error after proper calibration.
Spruce stands in the mountains of Central Europe are particularly valuable, not only because of their natural and scenic values but also because of their role in the protection of watersheds and ...soil. Over the past decades, these stands were frequently exposed to massive deforestation caused by various biotic, abiotic and anthropogenic factors. The current health condition of spruce stands in the Eastern Sudetes shows that the next phase of deterioration of these stands has begun. Bearing in mind past experiences and the current situation in these mountain areas, it is particularly important to understand the processes and factors that may short-term (2012–2016) spruce health analyses based on the normalized difference red-edge index and RapidEye satellite imagery, which is being delivered annually. Aided by remote sensing data and Boosted Regression Trees, it was possible to determine the topographic and tree stand features having the greatest impact on the vitality of spruce in all analyzed areas during 2012–2016. As the results show, the highest impact on the value of the normalized difference red-edge index indicator comes from a height above sea level, age of stands, terrain slopes, and exposure. In various areas, these factors may affect the vitality of spruce to varying degrees but not always in the same way. Our models accurately explained 74–81% of the randomly selected input data (predicted 72–80% of the excluded data) for site A, 50–58% for site B (48–57% for tested data) and 54–70% for site C (52–69% for excluded data).
Salvage logging is performed to remove the fallen and damaged trees after a natural disturbance, e.g., fire or windstorm. From an economic point of view, it is desirable to remove the most valuable ...merchantable timber, but usually, the process depends mainly on topography and distance to forest roads. The objective of this study was to evaluate the suitability of the Black-Bridge satellite imagery for the spatial distribution of salvage cutting in southern Poland after the severe windstorm in July 2015. In particular, this study aimed to determine which factors influence the spatial distribution of salvage cutting. The area of windthrow and the distribution of salvage cutting (July-August 2015 and August 2015-May 2016) were delineated using Black-Bridge satellite imagery. The distribution of the polygons (representing windthrow and salvage cutting) was verified with maps of aspect, elevation and slope, derived from the Digital Terrain Model and the distance to forest roads, obtained from the Digital Forest Map. The analysis included statistical modelling of the relationships between the process of salvage cutting and selected geographical and spatial features. It was found that the higher the elevation and the steeper the slope, the lower the probability of salvage cutting. Exposure was also found to be a relevant factor (however, it was difficult to interpret) as opposed to the distance to forest roads. Keywords: forest engineering, remote sensing, windthrow, sanitation harvest
In the 1980s, the Western Sudety Mountains were affected by a forest dieback process, resulting in large-scale deforestation covering an area of about 15,000 ha. A similar phenomenon is presently ...being observed in the Western Beskidy and Eastern Sudety Mountains, where the course of the process and the final effects are similar. The presented study analyzed the relationships between forest dieback processes today and in the past. Among others, the impact of the following factors was examined: exposure, slope, altitude, and topographic index, which was generated based on the airborne LIDAR (also airborne laser scanning abbreviated as ALS) data. The identification of forest dieback areas in the past was carried out based on the archived Landsat satellite imagery, as well as data obtained from the Polish State Forests. The identification of forest dieback areas at present was carried out based on the ALS data (single-tree detection approach) and color infrared aerial images. In the study, inter-dependencies between forest dieback today and in the past were compared. The performed analyses show significant differences between forests’ dieback specifics in all three areas. The process first occurred at 800–900 m a.s.l., and afterwards at over 900 m. Mortality was especially intensive on the western and southwestern slopes. Below 700 m a.s.l., forests survived quite well. In the 1980s, significantly higher concentrations of hazardous chemical compounds were noted, which resulted in respectively greater deforestations on aspects open to the operation of prevailing winds (mainly west). Nowadays, a proportionately higher number of trees die on the southern aspects, which is particularly visible in the Western Sudety Mountains.
Two change detection techniques (NDVI differencing and post-classification analysis) were compared, in order to detect canopy cover changes in forests on the area of twelve forest districts in the ...Sudety and West Beskidy Mountains in Poland, using 2012 and 2013 Black-Bridge satellite images. Although the classification accuracy of the respective images was high (about 95%), the accuracy of the difference in bi-temporal images was much worse because of the short time between the dates of images and the imperfection of the algorithm calculating the unclear boundary between the forest and no-forest areas. NDVI differencing method and thresholding brought much better overall results, although roads, clouds and fogs caused much problem performing pseudo-changes.
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