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Airborne Laser Scanning

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Norbert Pfeifer – One of the best experts on this subject based on the ideXlab platform.

  • Categorizing Grassland Vegetation with Full-Waveform Airborne Laser Scanning: A Feasibility Study for Detecting Natura 2000 Habitat Types
    Remote Sensing, 2014
    Co-Authors: András Zlinszky, Anke Schroiff, Adam Kania, Balázs Deák, Werner Mücke, Ágnes Vári, Balázs Székely, Norbert Pfeifer

    Abstract:

    There is increasing demand for reliable, high-resolution vegetation maps covering large areas. Airborne Laser Scanning data is available for large areas with high resolution and supports automatic processing, therefore, it is well suited for habitat mapping. Lowland hay meadows are widespread habitat types in European grasslands, and also have one of the highest species richness. The objective of this study was to test the applicability of Airborne Laser Scanning for vegetation mapping of different grasslands, including the Natura 2000 habitat type lowland hay meadows. Full waveform leaf-on and leaf-off point clouds were collected from a Natura 2000 site in Sopron, Hungary, covering several grasslands. The LIDAR data were processed to a set of rasters representing point attributes including reflectance, echo width, vegetation height, canopy openness, and surface roughness measures, and these were fused to a multi-band pseudo-image. Random forest machine learning was used for classifying this dataset. Habitat type, dominant plant species and other features of interest were noted in a set of 140 field plots. Two sets of categories were used: five classes focusing on meadow identification and the location of lowland hay meadows, and 10 classes, including eight different grassland vegetation categories. For five classes, an overall accuracy of 75% was reached, for 10 classes, this was 68%. The method delivers unprecedented fine resolution vegetation maps for management and ecological research. We conclude that high-resolution full-waveform LIDAR data can be used to detect grassland vegetation classes relevant for Natura 2000.

  • opals a framework for Airborne Laser Scanning data analysis
    Computers Environment and Urban Systems, 2014
    Co-Authors: Norbert Pfeifer, Gottfried Mandlburger, Johannes Otepka, Wilfried Karel

    Abstract:

    Abstract A framework for Orientation and Processing of Airborne Laser Scanning point clouds, OPALS, is presented. It is designed to provide tools for all steps starting from full waveform decomposition, sensor calibration, quality control, and terrain model derivation, to vegetation and building modeling. The design rationales are discussed. The structure of the software framework enables the automatic and simultaneous building of command line executables, Python modules, and C++ classes from a single algorithm-centric repository. It makes extensive use of (industry-) standards as well as cross-platform libraries. The framework provides data handling, logging, and error handling. Random, high-performance run-time access to the originally acquired point cloud is provided by the OPALS data manager, allowing storage of billions of 3D-points and their additional attributes. As an example geo-referencing of Laser Scanning strips is presented.

  • radiometric calibration of multi wavelength Airborne Laser Scanning data
    ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences, 2012
    Co-Authors: Christian Briese, Wolfgang Wagner, Martin Pfennigbauer, Andreas Ullrich, Hubert Lehner, Norbert Pfeifer

    Abstract:

    Abstract. Airborne Laser Scanning (ALS) is a widely used technique for the sampling of the earth’s surface. Nowadays a wide range of ALS sensor systems with different technical specifications can be found. One parameter is the Laser wavelength which leads to a sensitivity for the wavelength dependent backscatter characteristic of sensed surfaces. Current ALS sensors usually record next to the geometric information additional information on the recorded signal strength of each echo. In order to utilize this information for the study of the backscatter characteristic of the sensed surface, radiometric calibration is essential. This paper focuses on the radiometric calibration of multi-wavelength ALS data and is based on previous work on the topic of radiometric calibration of monochromatic (single-wavelength) ALS data. After a short introduction the theory and whole workflow for calibrating ALS data radiometrically based on in-situ reference surfaces is presented. Furthermore, it is demonstrated that this approach for the monochromatic calibration can be used for each channel of multi-wavelength ALS data. The resulting active multi-channel radiometric image does not have any shadows and from a geometric viewpoint the position of the objects on top of the terrain surface is not altered (the result is a multi-channel true orthophoto). Within this paper the approach is demonstrated by three different single-wavelength ALS data acquisition campaigns (532nm, 1064nm and 1550nm) covering the area of the city Horn (Austria). The results and practical issues are discussed.

Matti Maltamo – One of the best experts on this subject based on the ideXlab platform.

  • bayesian approach to tree detection based on Airborne Laser Scanning data
    IEEE Transactions on Geoscience and Remote Sensing, 2014
    Co-Authors: Timo Lahivaara, Timo Tokola, Jari Vauhkonen, Aku Seppanen, J P Kaipio, Lauri Korhonen, Matti Maltamo

    Abstract:

    In this paper, we consider a computational method for detecting trees on the basis of Airborne Laser Scanning (ALS) data. In the approach, locations, heights, and crown shapes of trees are tracked automatically by fitting multiple 3-D crown height models to ALS data of a field plot. The estimates are computed with an iterative reconstruction method based on Bayesian inversion paradigm. The formulation allows for utilizing prior information on tree shapes in the estimation. Here, the prior models are written based on field measurement data and allometric models for tree shapes. The feasibility of the approach is tested with ALS and field data from a managed boreal forest. The algorithm found 70.2% of the trees in the area, which is a clear improvement compared to a usual 2.5D crown delineation approach (53.1% of the trees detected).

  • canonical correlation analysis for interpreting Airborne Laser Scanning metrics along the lorenz curve of tree size inequality
    Baltic Forestry, 2014
    Co-Authors: Ruben Valbuena, Petteri Packalen, Timo Tokola, Matti Maltamo

    Abstract:

    Canonical Correlation Analysis for Interpreting Airborne Laser Scanning Metrics along the Lorenz Curve of Tree Size Inequality

  • forestry applications of Airborne Laser Scanning concepts and case studies
    , 2014
    Co-Authors: Matti Maltamo, Erik Næsset, Jari Vauhkonen

    Abstract:

    1. Introduction to forest applications of Airborne Laser Scanning Jari Vauhkonen et al.- PART I – Methodological issues.- 2. Laser pulse interaction with forest canopy – geometric and radiometric issues Andreas Roncat et al.- 3. Full-waveform Airborne Laser Scanning systems and their possibilities in forest applications Markus Hollaus et al.- 4. Integrating Airborne Laser Scanning with data from global navigation satellite systems and optical sensors Ruben Valbuena.- 5. Segmentation of forest to tree objects Barbara Koch et al.- 6. The semi-individual tree crown approach Johannes Breidenbach, Rasmus Astrup.- 7. Tree species recognition based on Airborne Laser Scanning and complementary data sources Jari Vauhkonen et al.- 8. Estimation of biomass components by Airborne Laser Scanning Sorin C. Popescu, Marius Hauglin.- 9. Predicting tree diameter distributions Matti Maltamo, Terje Gobakken.- 10. A model-based approach for the recovery of forest attributes using Airborne Laser Scanning data Lauri Mehtatalo et al.- PART II – Forest inventory applications.- 11. Area-based inventory in Norway – from innovation to an operational reality Erik Naesset.- 12. Species specific management inventory in Finland Matti Maltamo, Petteri Packalen.- 13. Inventory of forest plantations Jari Vauhkonen et al.- 14. Using Airborne Laser Scanning data to support forest sample surveys Ronald E. McRoberts et al.- 15. Modeling and estimating change Ronald E. McRoberts et al.- 16. Valuation of Airborne Laser Scanning based forest information Annika Kangas et al.- PART III – Ecological applications.- 17. Assessing habitats and organism-habitat relationships by Airborne Laser Scanning Ross A. Hill et al.- 18. Assessing biodiversity by Airborne Laser Scanning Jorg Muller, Kerri Vierling.- 19. Assessing dead wood by Airborne Laser Scanning Matti Maltamo et al.- 20. Estimation of canopy cover, gap fraction and leaf area index with Airborne Laser Scanning Lauri Korhonen, Felix Morsdorf.- 21. Canopy gap detection and analysis with Airborne Laser Scanning Benoit St-Onge et al.- 22. Applications of Airborne Laser Scanning in forest fuel assessment and fire prevention John Gajardo et al.- Index.

Juha Hyyppä – One of the best experts on this subject based on the ideXlab platform.

  • single sensor solution to tree species classification using multispectral Airborne Laser Scanning
    Remote Sensing, 2017
    Co-Authors: Juha Hyyppä, Mikko Vastaranta, Harri Kaartinen, Paula Litkey, Markus Holopainen

    Abstract:

    This paper investigated the potential of multispectral Airborne Laser Scanning (ALS) data for individual tree detection and tree species classification. The aim was to develop a single-sensorsolution for forest mapping that is capable of providing species-specific information, required for forest management and planning purposes. Experiments were conducted using 1903 ground measured trees from 22 sample plots and multispectral ALS data, acquired with an Optech Titan scanner over a boreal forest, mainly consisting of Scots pine (Pinus Sylvestris), Norway spruce (Picea Abies), and birch (Betula sp.), in southern Finland. ALS-features used as predictors for tree species were extracted from segmented tree objects and used in random forest classification. Different combinations of features, including point cloud features, and intensity features of single and multiple channels, were tested. Among the field-measured trees, 61.3% were correctly detected. The best overall accuracy (OA) of tree species classification achieved for correctly-detected trees was 85.9% (Kappa = 0.75), using a point cloud and single-channel intensity features combination, which was not significantly different from the ones that were obtained either using all features (OA = 85.6%, Kappa = 0.75), or single-channel intensity features alone (OA = 85.4%, Kappa = 0.75). Point cloud features alone achieved the lowest accuracy, with an OA of 76.0%. Field-measured trees were also divided into four categories. An examination of the classification accuracy for four categories of trees showed that isolated and dominant trees can be detected with a detection rate of 91.9%, and classified with a high overall accuracy of 90.5%. The corresponding detection rate and accuracy were 81.5% and 89.8% for a group of trees, 26.4% and 79.1% for trees next to a larger tree, and 7.2% and 53.9% for trees situated under a larger tree, respectively. The results suggest that Channel 2 (1064 nm) contains more information for separating pine, spruce, and birch, followed by channel 1 (1550 nm) and channel 3 (532 nm) with an overall accuracy of 81.9%, 78.3%, and 69.1%, respectively. Our results indicate that the use of multispectral ALS data has great potential to lead to a single-sensor solution for forest mapping.

  • fully automated power line extraction from Airborne Laser Scanning point clouds in forest areas
    Remote Sensing, 2014
    Co-Authors: Lingli Zhu, Juha Hyyppä

    Abstract:

    High-voltage power lines can be quite easily mapped using Laser Scanning data, because vegetation close to high-voltage lines is typically removed and also because the power lines are located higher off the ground in contrast to regional networks and lower voltage networks. On the contrary, lower voltage power lines are located in the middle of dense forests, and it is difficult to classify power lines in such an environment. This paper proposes an automated power line detection method for forest environments. Our method was developed based on statistical analysis and 2D image-based processing technology. During the process of statistical analysis, a set of criteria (e.g., height criteria, density criteria and histogram thresholds) is applied for selecting the candidates for power lines. After transforming the candidates to a binary image, image-based processing technology is employed. Object geometric properties are considered as criteria for power line detection. This method was conducted in six sets of Airborne Laser Scanning (ALS) data from different forest environments. By comparison with reference data, 93.26% of power line points were correctly classified. The advantages and disadvantages of the methods were analyzed and discussed.

  • Airborne Laser Scanning and digital stereo imagery measures of forest structure comparative results and implications to forest mapping and inventory update
    Canadian Journal of Remote Sensing, 2013
    Co-Authors: Mikko Vastaranta, Juha Hyyppä, Joanne C White, Michael A Wulder, Markus Holopainen, C. Ginzler, Sakari Tuominen, Anssi Pekkarinen, Ville Kankare, Hannu Hyyppa

    Abstract:

    Airborne Laser Scanning (ALS) has demonstrated utility for forestry applications and has renewed interest in other forms of remotely sensed data, especially those that capture three-dimensional (3-D) forest characteristics. One such data source results from the advanced processing of high spatial resolution digital stereo imagery (DSI) to generate 3-D point clouds. From the derived point cloud, a digital surface model and forest vertical information with similarities to ALS can be generated. A key consideration is that when developing forestry related products such as a canopy height model (CHM), a high spatial resolution digital terrain model (DTM), typically from ALS, is required to normalize DSI elevations to heights above ground. In this paper we report on our investigations into the use of DSI-derived vertical information for capturing variations in forest structure and compare these results to those acquired using ALS. An ALS-derived DTM was used to provide the spatially detailed ground surface elev…