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Supplementary data to publication GPS Solutions 24:64 (2020) Wanninger, L., Heßelbarth, A. (2020): GNSS code and carrier phase observations of a Huawei P30 smartphone: quality assessment and centimeter-accurate positioning; GPS Solutions 24:64, https://doi.org/10.1007/s10291-020-00978-z (open access). The data set consists of GNSS observations of a smartphone Huawei P30. They were collected in 8 static observation sessions with an overall duration of 77 h. Each session data set includes raw data gathered by GNSSLogger and RINEX files for Huawei P30 and a local reference station. The data sets are stored in two separate zip-archives. This archive contains the RINEX observations of Huawei P30, RINEX observations of the local reference station "BZW1" equipped with SEPT POLARX5 / JAVRINGANT_DM JVDM, broadcast ephemerides in RINEX format, and antenna corrections in ANTEX format. All RINEX files containing Huawei P30 observations use station name "HUAW". The five rooftop sessions with different Huawei P30 orientations were used to calibrate the phase center of the smartphone. This was repeated with the DRB2 rotational device, which enables observations in four azimuthal orientations per minute. Our results of the HUAWEI P30 phase center calibration, valid for the setup as shown in the paper (Fig. 1), are found in the ANTEX directory. The two field sessions are complemented with additional observations by LEICA GRX1200+ GNSS / NAX3G+C NONE at the same stations as used by the Huawei P30. In field session 1 the station is named "1000". In the second session it is called "2000".
Supplementary data to publication GPS Solutions 24:64 (2020) Wanninger, L., Heßelbarth, A. (2020): GNSS code and carrier phase observations of a Huawei P30 smartphone: quality assessment and centimeter-accurate positioning; GPS Solutions 24:64, https://doi.org/10.1007/s10291-020-00978-z (open access). The data set consists of GNSS observations of a smartphone Huawei P30. They were collected in 8 static observation sessions with an overall duration of 77 h. Each session data set includes raw data gathered by GNSSLogger and RINEX files for Huawei P30 and a local reference station. The data sets are stored in two separate zip-archives. This archive contains the GNSSLogger raw data of the Huawei P30 GNSS measurements for all 8 sessions.
Supplementary image dataset of the ISPRS International Journal of Geoinformation publication "Fully Automated Pose Estimation of Historical Images in the Context of 4D Geographic Information Systems Utilizing Machine Learning Methods". Historical image benchmark dataset including feature matches and four scene reconstructions. The dataset can be used for testing and evaluating feature matching methods on exclusively historical images. Additionally, the dataset can easily be extended as all tie point information is provided.
A workflow is introduced to automatically measure water stages based on image measurements using deep learning. So far, most camera gauges do not provide the needed robustness to achieve accurate water stage measurements because of changing environmental conditions. The novel, suggested approach is based on two CNNs (i.e. FCN and SegNet) to identify water in imagery. The image information is transformed into metric water level values intersecting the extracted water contour with a 3D model. The workflow allows for the densification of river monitoring networks based on low-cost camera gauges in various scenarios.
For detailed data description, please refer to: Zeh, L., Igel, T. M., Schellekens, J., Limpens, J., Bragazza, L., & Kalbitz, K. (2020). Vascular plants affect properties and decomposition of moss-dominated peat, particularly at elevated temperatures. Biogeosciences Discussions, 1-29.
This data collection includes the Python script used for image processing and analysis as described in the article "Quantification of uncertainties from image processing and analysis in laboratory-scale DNAPL migration experiments evaluated by reflective optical imaging" by Engelmann et al. submitted to Journal "Water" in 2019. Exemplary raw images generated from laboratory-scale tank experiments for DNAPL migration are included as well.
The final article can be found via https://doi.org/10.3389/fenvs.2020.00051
The MatLab Code can be used to simulate a underwater laser triangulation system. Editing the Input Parameter in the script suimulation.m will generate plots of the system including the resulting measurement image.
This data collection includes the Python script used for model data preparation, processing and assessment as described in the article "Evaluation of Decentralized, Closely-Spaced Precipitation Water and Treated Wastewater Infiltration" by Händel et al. submitted to Journal "Water" in 2018. Python script input data as generated from Hydrus 2D/3D models as well as resulting plots as used in the previously mentioned article are included.
This collection includes Supplementary Materials from the IfK results for meinGrün, made available on mCloud: 1. Metadata Dresden dataset 2. Metadata Heidelberg dataset 3. Use Case Web Portal Heatmap "Großer Garten"