3 documents found in 148ms
# 1
Richter, Nicole • Nikkhoo, Mehdi • de Zeeuw-van Dalfsen, Elske • Walter, Thomas. R.
Abstract: The datasets included in this data publication are: (1) the TLS combined point cloud (consisting of ∼15 million data points), (2) a Digital Elevation Model (DEM) with 1 m pixel spacing which was generated from (1), and (3) a shaded relief of (2) in kmz format. These datasets are supplement to de Zeeuw-van Dalfsen et al. (2017), who used them to study structural and geomorphological features at the nested summit craters of Láscar Volcano, Chile. However, in the paper the data were used in a local reference frame while we here provide both the TLS point cloud and the DEM product in global coordinates (WGS 1984 UTM Zone 19 South). Light detection and ranging (LiDAR) is a technique where a laser pulse is actively emitted from a LiDAR instrument and the echo that returns from a target object is recorded. The distances between the instrument and the target points are calculated from the round-trip travel time of the laser pulse (Fornaciai et al., 2010). A terrestrial laser scanner (TLS) uses this technique in a scanning mode where the laser beam is deflected into different directions by an oscillating mirror while at the same time the scanner’s head is rotating. We used a long-range RIEGL LMS-Z620 instrument with a field of view of up to 80° by 360° in the vertical and horizontal plane, respectively. The maximum repeatability of this instrument is 5 mm, but this value increases with increasing distance between the scanner and the target, when viewing geometries or the target reflectivity are not optimal or when atmospheric conditions vary and are not ideal. From the acquired 3D point cloud topographic details can be retrieved over a maximum distance of 2 km. However, newer instruments can reach distances of 6 km or more.
Georeferencing (local coordinate system) In total, four TLS scans were acquired on two days in November 2013 (two at each day to overcome shadowing effects). The two point clouds from each view point were combined using tie points, i.e. reflectors that were placed in the field, and the RiSCAN Pro Software (http://www.riegl.com). For the two point clouds from day 1, we achieved a standard deviation of 0.0023 m using 6 tie points, while for the two point clouds acquired on day 2 we reached a standard deviation of 0.0052 m using 3 tie points. In addition to the TLS measurement, the reflectors’ positions were also measured using a total station. This additional data allowed us to 1) orientate each of the two point clouds to a local geodetic reference frame in the XY plane using a 3D affine transformation with a remaining RMSE of ∼1 cm and 2) estimate the orientation about Z and the full translation parameters using hand-held GPS coordinates of a common point and the individual tie points. Following this procedure we produced a combined point cloud of all four TLS scans in a local geodetic reference frame. Georeferencing (global coordinate system) In order to derive the coordinates of the TLS point cloud in a global coordinate system, we used the open-source software Minuit2 5.18/00 which was developed at CERN (James and Winkler, 2004 and references therein). This tool finds the minimum value of multi-parameter functions and was in our case employed to find the minimum root mean square residuals (in elevation) between the TLS point clouds and a reference DEM featuring a 1 m pixel spacing that was calculated from tri-stereo optical Pléiades-1 satellite imagery. When applying this minimization technique, the data are transferred to the same coordinate system as the reference data (WGS 1984 UTM Zone 19 South). In a first step, we minimized the two TLS point clouds from the two different acquisition dates separately. We masked out areas from the Pléiades reference DEM that we know are very different when compared to the TLS point data. For instance, areas along the steep crater walls are interpolated to a high degree in the Pléiades DEM, while the scanner-facing crater walls are expected to have comparably precise point values in the TLS dataset. Thereafter, we combined the TLS point clouds and ran another Minuit RMSE minimization onto the masked Pléiades DEM.
# 2
Schmidt, Marius
Abstract: TERENO Eifel-Rur Observatory. TERENO (TERrestrial ENvironmental Observatories) spans an Earth observation network across Germany that extends from the North German lowlands to the Bavarian Alps. This unique large-scale project aims to catalogue the longterm ecological, social and economic impact of global change at regional level.The central monitoring site of the TERENO Eifel/Lower Rhine Valley Observatory is the catchment area of the River Rur. It covers a total area of 2354 km² and exhibits a distinct land use gradient: The lowland region in the northern part is characterised by urbanisation and intensive agriculture whereas the low mountain range in the southern part is sparsely populated and includes several drinking water reservoirs. Furthermore, the Eifel National Park is situated in the southern part of the Rur catchment serving as a reference site. Intensive test sites are placed along a transect across the Rur catchments in representative land cover, soil, and geologic settings.The Rollesbroich site is located in the low mountain range “Eifel” near the German-Belgium border and covers the area of the small Kieselbach catchment (40 ha) with altitudes ranging from 474 to 518 m.a.s.l.. The climate is temperate maritime with a mean annual air temperature and precipitation of 7.7 °C and 1033 mm, respectively, for the period from 1981 to 2001. Soils are dominated by (stagnic) Cambisols and Stagnosols on Devonian shales with occasional sandstone inclusions that are covered by a periglacial solifluction clay–silt layer. The mountainous grassland vegetation is dominated by perennial ryegrass (Lolium perenne) and smooth meadow grass (Poa pratensis).The study site is highly instrumented. All components of the water balance (e.g. precipitation, evapotranspiration, runoff, soil water content) are continuously monitored using state-of-the-art instrumentation, including weighable lysimeters, runoff gauges, cosmic-ray soil moisture sensors, a wireless sensor network that monitors soil temperature, and soil moisture at 189 locations in different depths (5, 20 and 50 cm) throughout the study site. Periodically also different chamber measurements were made to access soil or plant gas exchange.This data set contains weekly updated flux-, meteorological and soil measurements of the permanent operating EC/Climate station Rollesbroich 1 (50.621° N, 6.304° E, 515 m a.s.l.), which was installed in spring 2011 at the border of two fields of grassland (5.8 and 7.8 ha) within the study site. Management of both fields is typical for the low mountain range of the Eifel region with one fertilizer application and three cuts per year. The area within the fetch of the eddy covariance tower is relatively flat with slopes ranging between 0.35° and 3.12°. The station is equipped with a CSAT3 sonic anemometer and LI7500 gas analyser. Besides flux measurements and typical climate parameters (radiation, air temperature, air humidity, soil moisture, soil temperature etc.) also the plant height and farming activities are recorded.Meteorological and soil data was at least controlled by visual inspection by using common plausibility ranges and cross checks with nearby stations. Afterwards the data was flagged according to it's quality (O.K., suspect, moderate, bad etc.). Flux data was processed and checked according to the TERENO QC scheme (Mauder,et al., 2013, doi:10.1016/j.agrformet.2012.09.006).
# 3
Hank, Tobias Benedikt • Locherer, Matthias • Richter, Katja • Mauser, Wolfram
Abstract: This data collection contains a multitemporal series of six airborne hyperspectral image mosaics acquired during the growing season of 2012 over the Neusling test area near Landau a.d. Isar in Southern Germany. The airborne hyperspectral data is complemented by accompanying in-situ data acquired parallel to the overflights. The dataset is composed of a) four airborne hyperspectral image mosaics acquired during overflights on April 28th 2012, May 25th 2012, June 16th 2012 and September 8th 2012 with the AVIS-3 imaging spectrometer. The AVIS data consists of 197 spectral bands, ranging from VIS to SWIR (477 - 1704 nm); b) two airborne hyperspectral image mosaics acquired during overflights, which were conducted by the DLR user service OpAiRS (www.dlr.de/opairs) on May 8th 2012 and August 14th 2012 with a HySpex imaging spectrometer. The HySpex data consists of 332 spectral bands, ranging from VIS to SWIR (417 - 2496 nm); c) spatially comprehensive land use/land cover maps generated from in-situ observations for two time-windows during the growing season of 2012 (May and August); d) Flight-parallel in-situ point-measurements consisting of: i) non-destructively measured leaf area index of winter wheat, winter barley, sugar beet, maize and rapeseed (561 measurements incl. standard deviations), ii) SPAD chlorophyll measurements (522 measurements incl. standard deviations), iii) 557 soil moisture measurements incl. standard deviations iv) 539 phenological observations v) 499 measurements of canopy height incl. standard deviations and vi) 38 measurements of plant density. The dataset was collected in order to cover the seasonal dynamics in the development of agricultural crops in Southern Germany.Version History: Correct Acquisition date of the second HySpex flight was August 14th 2012, not August 12th 2012.
The Environmental Mapping and Analysis Program (EnMAP) is a German hyperspectral satellite mission that aims at monitoring and characterizing the Earth’s environment on a global scale. EnMAP serves to measure and model key dynamic processes of the Earth’s ecosystems by extracting geochemical, biochemical and biophysical parameters, which provide information on the status and evolution of various terrestrial and aquatic ecosystems. In the frame of the EnMAP preparatory phase, pre-flight campaigns including airborne and in-situ measurements in different environments and for several application fields are being conducted. The main purpose of these campaigns is to support the development of scientific applications for EnMAP. In addition, the acquired data are input in the EnMAP end-to-end simulation tool (EeteS) and are employed to test data pre-processing and calibration-validation methods. The campaign data are made freely available to the scientific community under a Creative Commons Attribution-ShareAlike 4.0 International License. An overview of all available data is provided in in the EnMAP Flight Campaigns Metadata Portal http://www.enmap.org/?q=flights.
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