Martin Hämmerle

Effects of Reduced Terrestrial LiDAR Point Density on High-Resolution Grain Crop Surface Models in Precision Agriculture

3D geodata play an increasingly important role in precision agriculture, e.g., for modeling in-field variations of grain crop features such as height or biomass. A common data capturing method is LiDAR, which often requires expensive equipment and produces large datasets. This study contributes to the improvement of 3D geodata capturing efficiency by assessing the effect of reduced scanning resolution on crop surface models (CSMs). The analysis is based on high-end LiDAR point clouds of grain crop fields of different varieties (rye and wheat) and nitrogen fertilization stages (100%, 50%, 10%). Lower scanning resolutions are simulated by keeping every n-th laser beam with increasing step widths n. For each iteration step, high-resolution CSMs (0.01 m2 cells) are derived and assessed regarding their coverage relative to a seamless CSM derived from the original point cloud, standard deviation of elevation and mean elevation. Reducing the resolution to, e.g., 25% still leads to a coverage of >90% and a mean CSM elevation of >96% of measured crop height. CSM types (maximum elevation or 90th-percentile elevation) react differently to reduced scanning resolutions in different crops (variety, density). The results can help to assess the trade-off between CSM quality and minimum requirements regarding equipment and capturing set-up.

Comparison of Kinect and Terrestrial LiDAR Capturing Natural Karst Cave 3-D Objects

Modeling natural phenomena from 3-D information enhances our understanding of the environment. Dense 3-D point clouds are increasingly used as highly detailed input datasets. In addition to the capturing techniques of point clouds with LiDAR, low-cost sensors have been released in the last few years providing access to new research fields and facilitating 3-D data acquisition for a broader range of applications. This letter presents an analysis of different speleothem features using 3-D point clouds acquired with the gaming device Microsoft Kinect. We compare the Kinect sensor with terrestrial LiDAR reference measurements using the KinFu pipeline for capturing complete 3-D objects (<; 4 m3). The results demonstrate the suitability of the Kinect to capture flowstone walls and to derive morphometric parameters of cave features. Although the chosen capturing strategy (KinFu) reveals a high correlation (R2 = 0.92) of stalagmite morphometry along the vertical object axis, a systematic overestimation (22% for radii and 44% for volume) is found. The comparison of flowstone wall datasets predominantly shows low differences (mean of 1 mm with 7 mm standard deviation) of the order of the Kinect depth precision. For both objects the major differences occur at strongly varying and curved surface structures (e.g., with fine concave parts).

The climate tourism potential of Alpine destinations using the example of Sonnblick, Rauris and Salzburg

The climate tourism potential of a region can be described by methods used in human biometeorology and applied climatology. Frequency analyses based on complex thermal bioclimatic indices (e.g. physiologically equivalent temperature) and diagrams of precipitation patterns based on thresholds offer new approaches of visualisation. An integral approach for tourism climatologic analyses is provided by the climate–tourism/transfer–information–scheme that also bases on frequency distributions of relevant factors and parameters which are important for a destination. The knowledge about the vertical variability of tourism climatologic factors is of high importance because of the several kinds of tourism activities affected by weather. The same holds for a quantification of extreme events like heat waves because of their possible effects on health and recreation over a years course. The results show that the vertical gradient of bioclimatic and tourism-related parameters can be of value when developing strategies of adaption to climate change.

Assessment of tourism and recreation destinations under climate change conditions in Austria

To urism and recreation are important economic factors which are directly connected to weather and climate of a specific destination. Based on the observation network of the Central Institute of Meteorology and Geodynamics of Austria (ZAMG), data of 37 stations has been collected and analysed for tourism and recreation purposes. The analysis was based on long term data sets which were processed in relevant ways for tourism and recreation, resulting in frequency diagrams of Physiologically Equivalent Temperature (PET) and precipitation. Additionally, we prepared the results according to the demands of tourism and recreation authorities and industry using the Climate-Tourism/Transfer-Information-Scheme (CTIS). Applying data from the regional climate models REMO and CLM we can provide information on future climate conditions in Austria’s recreation areas. We chose two different time slices (2021–2050, 2071–2100) and IPCC emission scenarios (A1B, B1). The data was processed based on the threshold factors which are included in the CTIS (e.g. thermal comfort, heat stress, cold stress, sunshine, etc.). For the time slice 2021–2050 only moderate changes can be expected. But for 2071–2100 one can observe a distinct decrease of cold stress and the skiing potential. On the other hand, moderate increases of thermal comfort, heat stress, sultriness and sunshine are expected. No tendencies can be seen in precipitation and wind conditions.

3D Participatory Sensing with Low-Cost Mobile Devices for Crop Height Assessment--A Comparison with Terrestrial Laser Scanning Data.

The integration of local agricultural knowledge deepens the understanding of complex phenomena such as the association between climate variability, crop yields and undernutrition. Participatory Sensing (PS) is a concept which enables laymen to easily gather geodata with standard low-cost mobile devices, offering new and efficient opportunities for agricultural monitoring. This study presents a methodological approach for crop height assessment based on PS. In-field crop height variations of a maize field in Heidelberg, Germany, are gathered with smartphones and handheld GPS devices by 19 participants. The comparison of crop height values measured by the participants to reference data based on terrestrial laser scanning (TLS) results in R2 = 0.63 for the handheld GPS devices and R2 = 0.24 for the smartphone-based approach. RMSE for the comparison between crop height models (CHM) derived from PS and TLS data is 10.45 cm (GPS devices) and 14.69 cm (smartphones). Furthermore, the results indicate that incorporating participants’ cognitive abilities in the data collection process potentially improves the quality data captured with the PS approach. The proposed PS methods serve as a fundament to collect agricultural parameters on field-level by incorporating local people. Combined with other methods such as remote sensing, PS opens new perspectives to support agricultural development.

Assessing the Potential of a Low-Cost 3-D Sensor in Shallow-Water Bathymetry

Highly detailed 3-D geoinformation about bathymetry is crucial to understand a wide range of processes and conditions in the geosciences. Recently, low-cost sensors such as Microsoft’s structured-light 3-D camera Kinect for Xbox 360 have been deployed to complement established sources of 3-D bathymetric data like light detection and ranging or sound navigation and ranging. In this letter, we assess the Kinect’s applicability to capture the bathymetry of shallow waters. Therefore, the maximum capturing range through water, accuracy, and precision of Kinect measurements are examined. Additionally, we test a recording setup which allows for the mitigation of waves and which features advantages in terms of refraction correction on a scene containing submerged gravels. As a result, water depths of 30 cm (outdoors) and 40 cm (indoors) can be penetrated. The accomplished accuracy [mean standard deviation (SD) 7 mm] and precision values (mean SD 3.1 mm) are similar to the ones achieved by terrestrial laser scanning bathymetry. Derived gravel sizes highly correspond to the manual reference measurements. Overall, the findings show the Kinect’s applicability in researching shallow natural water bodies.

Towards an Electrochemical Immunosensor System with Temperature Control for Cytokine Detection

The cytokine interleukin-13 (IL-13) plays a major role in airway inflammation and is a target of new anti-asthmatic drugs. Hence, IL-13 determination could be interesting in assessing therapy success. Thus, in this work an electrochemical immunosensor for IL-13 was developed and integrated into a fluidic system with temperature control for read-out. Therefore, two sets of results are presented. First, the sensor was set up in sandwich format on single-walled carbon nanotube electrodes and was read out by applying the hydrogen peroxide–hydroquinone–horseradish peroxidase (HRP) system. Second, a fluidic system was built up with an integrated heating function realized by Peltier elements that allowed a temperature-controlled read-out of the immunosensor in order to study the influence of temperature on the amperometric read-out. The sensor was characterized at the temperature optimum of HRP at 30 °C and at 12 °C as a reference for lower performance. These results were compared to a measurement without temperature control. At the optimum operation temperature of 30 °C, the highest sensitivity (slope) was obtained compared to lower temperatures and a limit of detection of 5.4 ng/mL of IL-13 was calculated. Taken together, this approach is a first step towards an automated electrochemical immunosensor platform and shows the potential of a temperature-controlled read-out.

HELIOS full-waveform laser scanning simulation framework. Source code, precompiled version, example files for study of understory tree height scanning and respective output.

This data collection enables any user to reproduce the study Hammerle et al. (2017). It provides the source code to compile the applied simulation framework. Furthermore, a precompiled version of the software including the necessary files are provided so that a direct start of the simulation without compilation is possible. The output of the simulation (ASCII point clouds) is also provided. For details see the provided README.txt file. The main aim of the study was to examine different laser scanning campaing setups with respect to understory tree height representation which is important, for example, for forestry or climate research.

Introduction to LiDAR in Geoarchaeology from a Technological Perspective

LiDAR is a remote sensing method established in the geosciences for capturing highly accurate three-dimensional geodata. It is increasingly used to support geoarchaeological research due to a range of advantages, including survey-grade data quality, real 3D geodata, nonselective coverage of scenes with high measurement density, on-demand data capturing, and comprehensive filtering options based on geometric and radiometric information.

Terrestrial and unmanned aerial system imagery for deriving photogrammetric three-dimensional point clouds and volume models of mass wasting sites

Abstract. Three-dimensional (3-D) geodata of mass wasting sites are important to model surfaces, volumes, and their changes over time. With a photogrammetric approach commonly known as structure from motion, 3-D point clouds can be derived from image collections in a straightforward way. The quality of point clouds covering a quarry dump derived from terrestrial and aerial imagery is compared and assessed. A comprehensive set of quality indicators is calculated and compared to surveyed reference data and to a terrestrial LiDAR point cloud. The examined indicators are completeness of coverage, point density, vertical accuracy, multiscale point cloud distance, scaling accuracy, and dump volume. It is found that the photogrammetric datasets generally represent the examined dump well with, for example, an area coverage of up to 90% and 100% in case of terrestrial and aerial imagery, respectively, a maximum scaling difference of 0.62%, and volume estimations reaching up to 100% of the LiDAR reference. Combining the advantages of 3-D geodata derived from terrestrial (high detail, accurate volume calculation even with a small number of input images) and aerial images (high coverage) can be a promising method to further improve the quality of 3-D geodata derived with low-cost approaches.