Mapping Forest Regeneration from Terrestrial Laser Scans

Az erdei újulati foltok helye, kiterjedése, borítottsága és törzsszáma kulcsfontosságú tényezők az erdődinamikai folyamatok feltárásában és a többkorú faállományok kezelésében. A fatermési modellek előállítása, az üzemi gyakorlatban végzett erdőművelés valamint erdőfeltárás pontos és objektív módszereket kíván az újulat helyének meghatározására. A földi lézeres letapogatás kiválóan alkalmas törzstérképek előállítására, ám az adatok feldolgozásához szükséges eljárásokat eddig csak szálerdőkre fejlesztettek ki. A tanulmány olyan automatikus eljárást mutat be, ami 3–6 méter magasságú faegyedek lézeres letapogatás adataiból történő azonosítását teszi lehetővé. Három, különböző jellegű újulati foltban létesített mintaterületen a ponthalmaz vizuális interpretációjával azonosított törzsek 79–90%-át sikerült automatikus úton felismerni. Az eljárás teljesítményét a vizsgált állományjellemzők közül elsősorban a törzsszám befolyásolta, míg az ágak mennyiségének hatása elenyésző. Az elért eredmények rámutatnak, hogy a földi lézeres letapogatás alkalmas az újulat mennyiségének felmérésére, így a folyamatos borítású erdők leírásának ígéretes eszköze lehet

Hydrological impacts of various land cover types in the context of climate change for Zala County

The water balance of Zala County was analyzed using remote-sensing based actual evapotranspiration (ETA) and runoff (R) in the context of land cover types. The highest mean ETA rates were determined for water bodies (658 mm/year) and wetlands (622 mm/year). Forests have higher values than agricultural areas, and the lowest rates belong to artificial surfaces. Mean annual runoff is the largest on artificial surfaces (89 mm/year). For climate change impact analysis a Budykomodel was used in spatially distributed mode. The parameter of the Budyko model (α) was calculated for pixels without surplus water. For the extra water affected pixels a linear model with β parameter (actual evapotranspiration / pan evapotranspiration) was used. These parameters (α and β) can be used for evaluating future ETA and R in spatially distributed mode. According to the predictions, the mean annual evapotranspiration may increase about 27 mm while the runoff may decrease to one third of the present amount by end of the century

International benchmarking of terrestrial laser scanning approaches for forest inventories

The last two decades have witnessed increasing awareness of the potential of terrestrial laser scanning (TLS) in forest applications in both public and commercial sectors, along with tremendous research efforts and progress. It is time to inspect the achievements of and the remaining barriers to TLS-based forest investigations, so further research and application are clearly orientated in operational uses of TLS. In such context, the international TLS benchmarking project was launched in 2014 by the European Spatial Data Research Organization and coordinated by the Finnish Geospatial Research Institute. The main objectives of this benchmarking study are to evaluate the potential of applying TLS in characterizing forests, to clarify the strengths and the weaknesses of TLS as a measure of forest digitization, and to reveal the capability of recent algorithms for tree-attribute extraction. The project is designed to benchmark the TLS algorithms by processing identical TLS datasets for a standardized set of forest attribute criteria and by evaluating the results through a common procedure respecting reliable references. Benchmarking results reflect large variances in estimating accuracies, which were unveiled through the 18 compared algorithms and through the evaluation framework, i.e., forest complexity categories, TLS data acquisition approaches, tree attributes and evaluation procedures. The evaluation framework includes three new criteria proposed in this benchmarking and the algorithm performances are investigated through combining two or more criteria (e.g., the accuracy of the individual tree attributes are inspected in conjunction with plot-level completeness) in order to reveal algorithms’ overall performance. The results also reveal some best available forest attribute estimates at this time, which clarify the status quo of TLS-based forest investigations. Some results are well expected, while some are new, e.g., the variances of estimating accuracies between single-/multi-scan, the principle of the algorithm designs and the possibility of a computer outperforming human operation. With single-scan data, i.e., one hemispherical scan per plot, most of the recent algorithms are capable of achieving stem detection with approximately 75% completeness and 90% correctness in the easy forest stands (easy plots: 600 stems/ha, 20 cm mean DBH). The detection rate decreases when the stem density increases and the average DBH decreases, i.e., 60% completeness with 90% correctness (medium plots: 1000 stem/ha, 15 cm mean DBH) and 30% completeness with 90% correctness (difficult plots: 2000 stems/ha, 10 cm mean DBH). The application of the multi-scan approach, i.e., five scans per plot at the center and four quadrant angles, is more effective in complex stands, increasing the completeness to approximately 90% for medium plots and to approximately 70% for difficult plots, with almost 100% correctness. The results of this benchmarking also show that the TLS-based approaches can provide the estimates of the DBH and the stem curve at a 1–2 cm accuracy that are close to what is required in practical applications, e.g., national forest inventories (NFIs). In terms of algorithm development, a high level of automation is a commonly shared standard, but a bottleneck occurs at stem detection and tree height estimation, especially in multilayer and dense forest stands. The greatest challenge is that even with the multi-scan approach, it is still hard to completely and accurately record stems of all trees in a plot due to the occlusion effects of the trees and bushes in forests. Future development must address the redundant yet incomplete point clouds of forest sample plots and recognize trees more accurately and efficiently. It is worth noting that TLS currently provides the best quality terrestrial point clouds in comparison with all other technologies, meaning that all the benchmarks labeled in this paper can also serve as a reference for other terrestrial point clouds sources.</p

Algorithms for stem mapping by means of terrestrial laser scanning

Terrestrial laser scanning is an active remote-sensing technique, which has the potential toprovide detailed spatial data for various applications in the fields of forestry and nature conservation.This study introduces algorithms and methods to extract individual tree parameters – such as treelocation, stem diameter at breast height (DBH), and tree height – in automatic manner from terrestriallaser scanning data. The efficiency of the algorithms was tested on laser scanning data collected in apermanent sampling plot in the Hidegvíz-völgy forest reserve. The accuracy of the derived individualtree parameters was validated against tree metrics yielded by traditional field methods

Algorithms for Stem Mapping by Means of Terrestrial Laser Scanning = Automatizált eljárások törzstérképek előállítására földi lézeres letapogatás alapján

Terrestrial laser scanning is an active remote-sensing technique, which has the potential to provide detailed spatial data for various applications in the fields of forestry and nature conservation. This study introduces algorithms and methods to extract individual tree parameters – such as tree location, stem diameter at breast height (DBH), and tree height – in automatic manner from terrestrial laser scanning data. The efficiency of the algorithms was tested on laser scanning data collected in a permanent sampling plot in the Hidegvíz-völgy forest reserve. The accuracy of the derived individual tree parameters was validated against tree metrics yielded by traditional field methods. | A földi lézeres letapogatás egy új, aktív távérzékelési technika, mely részletes térbeli adatok szolgáltatásával az erdészeti és természetvédelmi célú térképezések és faállomány-felvételek hatékony eszköze lehet. Jelen tanulmány olyan módszereket és algoritmusokat mutat be, melyekkel egyesfák térképi pozíciója, mellmagassági átmérője, és magassága határozható meg automatizált úton, a földi lézeres letapogatás adataiból. Az algoritmusok hatékonyságát a Hidegvíz-völgy erdőrezervátum egyik állandósított mintapontján készített felmérés adataival teszteltük. A faegyedek helyének és méreteinek pontossági vizsgálatához az algoritmusok eredményeit hagyományos eszközökkel végzett térképezés és törzsenkénti felvétel adataival hasonlítottuk össze