Géza Király

Bio: Géza Király is an academic researcher from University of West Hungary. The author has contributed to research in topics: Land use & Tree (data structure). The author has an hindex of 8, co-authored 13 publications receiving 498 citations.

Legacies of 19th century land use shape contemporary forest cover

Abstract: Historic land use can exert strong land-use legacies, i.e., long-lasting effects on ecosystems, but the importance of land-use legacies, alongside other factors, for subsequent forest-cover change is unclear. If past land use affects rates of forest disturbance and afforestation then this may constrain land use planning and land management options, and legacies of current land management may constrain future land use. Our goal was to assess if and how much land-use legacies affect contemporary forest disturbance, and the abundance of different forest types in the Carpathian region in Eastern Europe (265,000 km2, encompassing parts of Poland, Slovakia, Ukraine, Romania, Hungary, and Czech Republic). We modeled contemporary forest disturbance (based on satellite image analysis from 1985 to 2010) as a function of historic land use (based on digitized topographic maps from 1860 and 1960). Contemporary forest disturbance was strongly related to historic land use even when controlling for environmental, accessibility and socio-political variation. Across the Carpathian region, the odds of forest disturbance were about 50% higher in areas that were not forested in 1860 (new forests) compared to areas that were forested then (old forests). The forest disturbance in new forests was particularly high in Poland (88% higher odds), Slovakia (69%) and Romania (67%) and persisted across the entire range of environmental, accessibility and socio-political variation. Reasons for the observed legacy effects may include extensive plantations outside forest ranges, predominantly spruce, poplar, and black locust, which are prone to natural disturbances. Furthermore, as plantations reach harvestable age of about 70 years for pulp and 120 year for saw-timber production, these are likely to be clear-cut, producing the observed legacy effects. Across the Carpathians, forest types shifted towards less coniferous cover in 2010 compared to the 1860s and 1960s likely due to extensive historic conifer harvest, and to recent natural disturbance events and clear-cuts of forest plantations. Our results underscore the importance of land-use legacies, and show that past land uses can greatly affect subsequent forest disturbance for centuries. Given rapid land use changes worldwide, it is important to understand how past legacies affect current management and what the impact of current land management decisions may be for future land use.

Algorithms for stem mapping by means of terrestrial laser scanning

Abstract: Terrestrial laser scanning is an active remote-sens ing technique, which has the potential to provide detailed spatial data for various applicati ons in the fields of forestry and nature conservati on. This study introduces algorithms and methods to ext ract 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 algorith ms was tested on laser scanning data collected in a permanent sampling plot in the Hidegviz-volgy fores t reserve. The accuracy of the derived individual tree parameters was validated against tree metrics yielded by traditional field methods. Remote Sensing / TLS / Modelling / Algorithms / Tree parameter estimation

Tree height estimation methods for terrestrial laser scanning in a forest reserve

Abstract: A terrestrial laser scanning survey has been performed on a forest reserve site. This paper represents the processing of the dataset. Two new methods have been developed for tree positioning, which is necessary for height calculation. One of them is the clustering method, the other is the so-called crescent moon method. The stems were modelled, as high as possible, by both methods. Two methods were tested for height estimation. One was a direct method based upon the Digital Surface Model; however a new method was developed to predict the tree-top based upon the modelled trunk and then the nearest local maximum was selected to that predicted point in the DSM. The other was an indirect method, where the modelled stems were described as paraboloids, and the heights were extrapolated. The accuracies of the methods were investigated by means of photogrammetric measurements based on very high-resolution aerial images. Both the clustering and crescent moon methods were appropriate in tree positioning and stem modelling. The height estimation based upon the DSM yielded good results. The extrapolation method was tested for European Larch only. The height in one-third of the cases was estimated by this method within tolerance. This method can be taken into consideration in the case of leaves on scanning in very dense, multi-storey forests.

Historical land use dataset of the Carpathian region (1819–1980)

Abstract: We produced the first spatially explicit, cross-border, digital map of long-term (160 years) land use in the Carpathian Ecoregion, the Hungarian part of the Pannonian plains and the historical regi...

Terrestrial laser scanning in forest inventories

Abstract: Decision making on forest resources relies on the precise information that is collected using inventory. There are many different kinds of forest inventory techniques that can be applied depending on the goal, scale, resources and the required accuracy. Most of the forest inventories are based on field sample. Therefore, the accuracy of the forest inventories depends on the quality and quantity of the field sample. Conventionally, field sample has been measured using simple tools. When map is required, remote sensing materials are needed. Terrestrial laser scanning (TLS) provides a measurement technique that can acquire millimeter-level of detail from the surrounding area, which allows rapid, automatic and periodical estimates of many important forest inventory attributes. It is expected that TLS will be operationally used in forest inventories as soon as the appropriate software becomes available, best practices become known and general knowledge of these findings becomes more wide spread. Meanwhile, mobile laser scanning, personal laser scanning, and image-based point clouds became capable of capturing similar terrestrial point cloud data as TLS. This paper reviews the advances of applying TLS in forest inventories, discusses its properties with reference to other related techniques and discusses the future prospects of this technique.

Retrieval of forest structural parameters using LiDAR remote sensing

Abstract: In this paper, a literature overview is presented on the use of laser rangefinder techniques for the retrieval of forest inventory parameters and structural characteristics. The existing techniques are ordered with respect to their scale of application (i.e. spaceborne, airborne, and terrestrial laser scanning) and a discussion is provided on the efficiency, precision, and accuracy with which the retrieval of structural parameters at the respective scales has been attained. The paper further elaborates on the potential of LiDAR (Light Detection and Ranging) data to be fused with other types of remote sensing data and it concludes with recommendations for future research and potential gains in the application of LiDAR for the characterization of forests.

Automatic Stem Mapping Using Single-Scan Terrestrial Laser Scanning

Abstract: The demand for detailed ground reference data in quantitative forest inventories is growing rapidly, eg, to improve the calibration of the developed models of airborne-laser-scanning-based inventories The application of terrestrial laser scanning (TLS) in the forest has shown great potential for improving the accuracy and efficiency of field data collection This paper presents a fully automatic stem-mapping algorithm using single-scan TLS data for collecting individual tree information from forest plots In this method, the stem points are identified by the spatial distribution properties of the laser points, the stem model is built up of a series of cylinders, and the location of the stem is estimated by the model The experiment was performed on nine plots with 10-m radius The stem-location maps measured in the field by traditional methods were used as the ground truth The overall stem-mapping accuracy was 73% The result shows that, in a relatively dense managed forest, the majority of stems can be located by the automatic algorithm The proposed method is a general solution for stem locating where particular plot knowledge and data format are not required

Detection of Vertical Pole-Like Objects in a Road Environment Using Vehicle-Based Laser Scanning Data

Abstract: Accurate road environment information is needed in applications such as road maintenance and virtual 3D city modelling. Vehicle-based laser scanning (VLS) can produce dense point clouds from large areas efficiently from which the road and its environment can be modelled in detail. Pole-like objects such as traffic signs, lamp posts and tree trunks are an important part of road environments. An automatic method was developed for the extraction of pole-like objects from VLS data. The method was able to find 77.7% of the poles which were found by a manual investigation of the data. Correctness of the detection was 81.0%.

International benchmarking of terrestrial laser scanning approaches for forest inventories

Abstract: 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.