Christian Briese

3D vegetation mapping using small-footprint full-waveform airborne laser scanners

Small‐footprint full‐waveform airborne laser scanning (ALS) is a remote sensing technique capable of mapping vegetation in three dimensions with a spatial sampling of about 0.5–2 m in all directions. This is achieved by scanning the laser beam across the Earths surface and by emitting nanosecond‐long infrared pulses with a high frequency of typically 50–150 kHz. The echo signals are digitized during data acquisition for subsequent off‐line waveform analysis. In addition to delivering the three‐dimensional (3D) coordinates of scattering objects such as leaves or branches, full‐waveform laser scanners can be calibrated for measuring the scattering properties of vegetation and terrain surfaces in a quantitative way. As a result, a number of physical observables are obtained, such as the width of the echo pulse and the backscatter cross‐section, which is a measure of the electromagnetic energy intercepted and re‐radiated by objects. The main aim of this study was to build up an understanding of the scattering characteristics of vegetation and the underlying terrain. It was found that vegetation typically causes a broadening of the backscattered pulse, while the backscatter cross‐section is usually smaller for canopy echoes than for terrain echoes. These scattering properties allowed classification of the 3D point cloud into vegetation and non‐vegetation echoes with an overall accuracy of 89.9% for a dense natural forest and 93.7% for a baroque garden area. In addition, by removing the vegetation echoes before the filtering process, the quality of the digital terrain model could be improved.

Calibration of full-waveform airborne laser scanning data for object classification

Small-footprint airborne laser scanners with waveform-digitizing capabilities are becoming increasingly available. Waveform-digitizing laser scanners seize the physical measurement process in its entire complexity. This leads the way to the possibility of deriving the backscatter cross section which is a measure of the electromagnetic energy intercepted and reradiated by objects. The cross section can be obtained by firstly decomposing the echo waveform in several distinct echoes, whereas for each echo its range, amplitude and width are known. Then the radar equation can be used for calibrating the waveform measurements using external reference targets with known backscatter cross sections. The final outcome is a 3D point cloud where each point represents one scatterer with a given cross section and echo width. Using these physical attributes and various geometric criteria the point cloud can be segmented or classified. In this paper this procedure is demonstrated based on waveform measurements acquired by the RIEGL LMS-Q560 sensor. The cross section of the homogenous reference targets is estimated with a RIEGL reflectometer and Spectralon® targets.

Laser scanning – principles and applications

In this overview paper the principles of laser scanning systems are presented. This includes a survey of different range measurement principles as well as different mechanisms for the deflection of the emitted laser beam. Furthermore, the usage of the laser scanning (LS) principle at different platforms (airborne (ALS), terrestrial (TLS), satellite) is discussed. Additionally, typical sensor parameters of currently commercially available sensor systems are presented. Furthermore, the technique of full-waveform LS is introduced and georeferencing of ALS data for improved precision is presented. The usage of LS data in different applications will be presented in an overview.

Categorizing Wetland Vegetation by Airborne Laser Scanning on Lake Balaton and Kis-Balaton, Hungary

Outlining patches dominated by different plants in wetland vegetation provides information on species succession, microhabitat patterns, wetland health and ecosystem services. Aerial photogrammetry and hyperspectral imaging are the usual data acquisition methods but the application of airborne laser scanning (ALS) as a standalone tool also holds promises for this field since it can be used to quantify 3-dimensional vegetation structure. Lake Balaton is a large shallow lake in western Hungary with shore wetlands that have been in decline since the 1970s. In August 2010, an ALS survey of the shores of Lake Balaton was completed with 1 pt/m2 discrete echo recording. The resulting ALS dataset was processed to several output rasters describing vegetation and terrain properties, creating a sufficient number of independent variables for each raster cell to allow for basic multivariate classification. An expert-generated decision tree algorithm was applied to outline wetland areas, and within these, patches dominated by Typha sp. Carex sp., and Phragmites australis. Reed health was mapped into four categories: healthy, stressed, ruderal and die-back. The output map was tested against a set of 775 geo-tagged ground photographs and had a user’s accuracy of > 97% for detecting non-wetland features (trees, artificial surfaces and low density Scirpus stands), > 72% for dominant genus detection and > 80% for most reed health categories (with 62% for one category). Overall classification accuracy was 82.5%, Cohen’s Kappa 0.80, which is similar to some hyperspectral or multispectral-ALS fusion studies. Compared to hyperspectral imaging, the processing chain of ALS can be automated in a similar way but relies directly on differences in vegetation structure and actively sensed reflectance and is thus probably more robust. The data acquisition parameters are similar to the national surveys of several European countries, suggesting that these existing datasets could be used for vegetation mapping and monitoring.

Digital terrain modelling for archaeological interpretation within forested areas using full-waveform laserscanning

The identification of sites within forested areas is one of the remaining unresolved issues for archaeological prospection. Airborne laser scanning can be a solution to this problem: due to the capability of penetrating forest to a certain degree (depending on the vegetation density) the determination of the terrain surface is even possible in wooded areas. To be able to identify archaeological structures, archaeologists have to interpret the resulting topographical data of a filtered ALS scan. This does not pose major problems with large structures. Smaller features, however, are much more difficult to identify, because their appearance in an ALS point cloud is very similar to natural and recent features, as for example dense brushwood, or piles of twigs or wood. Therefore, to eliminate potential sources of error, a high quality separation of terrain and off-terrain points is essential for archaeological interpretation while maintaining a high point density of the ALS data. Using conventional ALS systems, the possibilities to classify terrain and off-terrain points are limited and the results - especially in forested areas with dense understorey - are far from ideal for archaeological purposes. This paper will demonstrate how the new generation of full-waveform ALS systems can be used to get a much better classification of solid ground and vegetation cover and consequently DTMs, which can be interpreted archaeologically with much more confidence.

Radiometrically Calibrated Features of Full-Waveform Lidar Point Clouds Based on Statistical Moments

Full-waveform lidar has gained increasing attention in 3-D remote sensing and related disciplines during the last decade due to its capability of delivering both geometric and radiometric information in the same spatial resolution. Radiometric information may either be related to the echo, e.g., echo amplitude and width, or to the target itself, e.g., the backscatter cross section (BCS). Echo parameters, often obtained by Gaussian decomposition, as well as target properties, which are (geo)physical properties and therefore independent of data acquisition mission parameters, are considered as additional features of the point cloud generated by laser scanning. The BCS commonly is derived by performing a deconvolution which results in its temporal derivative, the differential backscatter cross-section (dBCS), and subsequent integration. The temporal shape of the dBCS has gained little attention in the literature so far. In this letter, we discuss the derivation of additional target parameters, namely the statistical moments of the respective target dBCS. Besides discussing the applicability of established deconvolution approaches for the extraction of statistical moments in the dBCS, special emphasis is laid on their derivation in B-spline-based deconvolution. Uniform B-splines allow for linear deconvolution and subsequent radiometric calibration. We illustrate the potential of the proposed method by a sample data set stemming from an airborne lidar campaign in complex mountainous terrain.

Undistorting the Past: New Techniques for Orthorectification of Archaeological Aerial Frame Imagery

Archaeologists using airborne data can encounter a large variety of frame images in the course of their work. These range from vertical aerial photographs acquired with very expensive calibrated optics to oblique images from hand-held, uncalibrated cameras and even photographs shot with compact cameras from an array of unmanned airborne solutions. Additionally, imagery can be recorded in one or more spectral bands of the complete optical electromagnetic spectrum. However, these aerial images are rather useless from an archaeological standpoint as long as they are not interpreted in detail. Furthermore, the relevant archaeological information interpreted from these images has to be mapped and compared with information from other sources. To this end, the imagery must be accurately georeferenced, and the many geometrical distortions induced by the optics, the terrain and the camera tilt should be corrected. This chapter focuses on several types of archaeological airborne frame imagery, the distortion factors that are influencing these two-dimensional still images and the necessary steps to compute orthophotographs from them. Rather than detailing the conventional photogrammetric orthorectification workflows, this chapter mainly centres on the use of computer vision-based solutions such as structure from motion (SfM) and dense multi-view stereo (MVS). In addition to a theoretical underpinning of the working principles and algorithmic steps included in both SfM and MVS, real-world imagery originating from traditional and more advanced airborne imaging platforms will be used to illustrate the possibilities of such a computer vision-based approach: the variety of imagery that can be dealt with, how (accurately) these images can be transformed into map-like orthophotographs and how these results can aid in the documentation of archaeological resources at a variety of spatial scales. Moreover, the case studies detailed in this chapter will also prove that this approach might move beyond current restrictions of conventional photogrammetry due to its applicability to datasets that were previously thought to be unsuitable for convenient georeferencing.

Quantification of Overnight Movement of Birch (Betula pendula) Branches and Foliage with Short Interval Terrestrial Laser Scanning

The goal of the study was to determine circadian movements of silver birch (Petula Bendula) branches and foliage detected with terrestrial laser scanning (TLS). The study consisted of two geographically separate experiments conducted in Finland and in Austria. Both experiments were carried out at the same time of the year and under similar outdoor conditions. Experiments consisted of 14 (Finland) and 77 (Austria) individual laser scans taken between sunset and sunrise. The resulting point clouds were used in creating a time series of branch movements. In the Finnish data, the vertical movement of the whole tree crown was monitored due to low volumetric point density. In the Austrian data, movements of manually selected representative points on branches were monitored. The movements were monitored from dusk until morning hours in order to avoid daytime wind effects. The results indicated that height deciles of the Finnish birch crown had vertical movements between -10.0 and 5.0 cm compared to the situation at sunset. In the Austrian data, the maximum detected representative point movement was 10.0 cm. The temporal development of the movements followed a highly similar pattern in both experiments, with the maximum movements occurring about an hour and a half before (Austria) or around (Finland) sunrise. The results demonstrate the potential of terrestrial laser scanning measurements in support of chronobiology.

Full-Waveform Airborne Laser Scanning Systems and Their Possibilities in Forest Applications

Full-waveform (FWF) airborne laser scanning (ALS) systems became available for operational data acquisition around the year 2004. These systems typically digitize the analogue backscattered echo of the emitted laser pulse with a high frequency. FWF digitization has the advantage of not limiting the number of echoes that are recorded for each individual emitted laser pulse. Studies utilizing FWF data have shown that more echoes are provided from reflections in the vegetation in comparison to discrete echo systems. To obtain geophysical metrics based on ALS data that are independent of a mission’s flying height, acquisition time or sensor characteristics, the FWF amplitude values can be calibrated, which is an important requirement before using them in further classification tasks. Beyond that, waveform digitization provides an additional observable which can be exploited in forestry, namely the width of the backscattered pulse (i.e. echo width). An early application of FWF ALS was to improve ground and shrub echo identification below the forest canopy for the improvement of terrain modelling, which can be achieved using the discriminative capability of the amplitude and echo width in classification algorithms. Further studies indicate that accuracies can be increased for classification (e.g. species) and biophysical parameter extraction (e.g. diameter at breast height) for single-tree- and area-based methods by exploiting the FWF observables amplitude and echo width.

Distinguishing features from outliers in automatic Kriging-based filtering of MBES data: a comparative study

Multi beam echo sounding is the state of the art way for surveying sea bottoms. The sea floor elevation is obtained strip wise by measuring the time it takes for sound signals, emitted simultaneously in different directions, to travel to the sea bottom and back. We compare various ways of filtering erroneous soundings from MBES data sets, all based on Kriging. This research was initiated because of the problems a classic 1D cross validation method had with distinguishing blunders from features, like pipelines. We show that part of the problems can be solved by extending the 1D method to 2D and that most problems are solved by a robust, iterative filter method.