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  • Forschungsdaten  (7)
  • Forschungsdaten (GFZ)  (7)
  • Biota  (6)
  • 551 Geology, hydrology, meteorology  (1)
  • CRC1211 Database (CRC1211DB)  (7)
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  • Forschungsdaten (GFZ)  (7)
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  • 1
    Publikationsdatum: 2024-02-21
    Beschreibung: Abstract
    Beschreibung: A high-resolution Digital Terrain Model (DTM) has been processed for the Tillandsia landbeckii study sites at Arica. The original source data have been obtained from drone flight images. The final resolution of the DTM is of about 14 cm. We acknowledge support in the field and during data processing from Alexander Siegmund (PH Heidelberg). RE Stein and D Jäger contributed equally to the work.
    Beschreibung: TableOfContents
    Beschreibung: The zip.file contains the following 5 files: 1) Arica.blend 2) Arica_Ortho_clipped_0-5res.tif 3) DEM_Arica_final_clipped_rescale2.tif 4) DEM_Arica_final_clipped_rescale2_0-5res_raw.tif 5) DEM_Arica_final_clipped_rescale2_0-5res_rendered.tif Please do not change file names nor file extensions when loading files for viewing in BLENDER version 4.0 (https://www.blender.org/download/releases/4-0/). The "0-5res" file-versions refer to a 0.5m/px resolution (EPSG:32719 - WGS 84 / UTM Zone 19S). File DEM_Arica_final_clipped_rescale2.tif was processed to a final resolution of 1.35e-06 °degrees (c. 0.143 m) [EPSG:4326 - WGS 84].
    Beschreibung: Other
    Beschreibung: Short introduction into the methods: Very-high resolution images were captured using an unmanned aerial vehicle (UAVs) [drone: DJI Matrice 200; DJI Zenmuse X5S RGB camera]. With processing of the UAV data images are merged according to their geographical position by means of the Structure-from-Motion (SfM) algorithm and a digital elevation model was created (Micheletti et al. 2015; Westoby et al. 2012). High-resolution topographic surveying using the Structure-from-Motion (SfM) algorithm is a low-cost and user-friendly photogrammetric technique to obtain high-resolution datasets. The SfM method solves the camera pose and scene geometry simultaneously and automatically, using highly redundant bundle adjustment based on matching features in multiple overlapping, offset images (Westoby et al. 2012). SfM-Processing was performed using Agisoft Metashape Professional (Version 1.6.1 64 bit). Agisoft Metashape Professional performs well to reconstruct landscape 3D point clouds and the different steps of the process are configurable and can be controlled (Laporte-Fauret et al. 2019). Images were fed into the software and the quality (tool “estimate image quality”) and position was determined respectives images were chosen to cover the study area. Using the “Aling Photos” tool images were aligned creating tie points (2D) and a Depth Maps (high quality, mild filtering) was created (3D). With the help of the Build Dense Cloud tool, set to high quality, the data points were created that represent the study area in 3D. Consecutively an orthomosaic of the study area was created using the Build Orthomosaic tool. An orthomosaic is a photogrammetrically orthorectified image product that has been mosaicked from a collection of images and corrected for geometric distortion to create a seamless mosaic dataset. Due to the high-resolution input data and the processing without compression a high-resolution orthomosaic was achieved with a pixel size of 2.1 cm/pix covering the study area. This detailed, high-resolution geolocated photo representation of the study site is the basis for the following analytical steps. A digital elevation model (DEM) was computed using the “Build DEM” tool. Its dimensions resulted herein in a 14 cm/pix size to cover the entire study site. Final adjustment of elevation has been done using the Copernicus Digital Elevation Model (https://spacedata.copernicus.eu/de/collections/copernicus-digital-elevation-model) using Q-GIS (https://www.qgis.org/de/site/). Laporte-Fauret, Q., et al. (2019). "Low-Cost UAV for high-resolution and large-scale coastal dune change monitoring using photogrammetry." Journal of Marine Science and Engineering 7(3): 63. Micheletti, N., Chandler, J. H., & Lane, S. N. (2015). Structure from motion (SFM) photogrammetry. In L. E. Clarke, & J. M. Nield (Eds.), Geomorphological techniques (Online Edition) (pp. 1–12, Chapter 2.2.2). British Society for Geomorphology Westoby, M. J., et al. (2012). "‘Structure-from-Motion’photogrammetry: A low-cost, effective tool for geoscience applications." Geomorphology 179: 300-314.
    Schlagwort(e): Biota ; Landscape Evolution ; Biodiversity
    Materialart: Dataset , Sub data for DTM configuration
    Standort Signatur Erwartet Verfügbarkeit
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  • 2
    Publikationsdatum: 2024-02-21
    Beschreibung: Abstract
    Beschreibung: A high-resolution Digital Terrain Model (DTM) has been processed for the Tillandsia landbeckii study sites at Arica. The original source data have been obtained from drone flight images. The final resolution of the DTM is of about 16 cm/px. We acknowledge support in the field and during data processing from Alexander Siegmund (PH Heidelberg).
    Beschreibung: TableOfContents
    Beschreibung: The zip.file contains the following 5 files: 1) Caldera.blend 2) Caldera_Ortho_0-5res_clipped.tif 3) Caldera_DEM_clipped_rescale.tif 4) Caldera_DEM_clipped_rescale_0-5res.tif 5) Caldera_DEM_clipped_rescale_0-5res_rendered.tif Please do not change file names nor file extensions when loading files for viewing in BLENDER version 4.0 (https://www.blender.org/download/releases/4-0/). The "0-5res" file-versions refer to a 0.5m/px resolution (EPSG:32719 - WGS 84 / UTM Zone 19S). File Caldera_DEM_clipped_rescale.tif was processed to a final resolution of 1.67e-06 °degrees (c. 0.165 m) [EPSG:4326 - WGS 84].
    Beschreibung: Other
    Beschreibung: Short introduction into the methods: Very-high resolution images were captured using an unmanned aerial vehicle (UAVs) [drone: DJI Matrice 200; DJI Zenmuse X5S RGB camera]. With processing of the UAV data images are merged according to their geographical position by means of the Structure-from-Motion (SfM) algorithm and a digital elevation model was created (Micheletti et al. 2015; Westoby et al. 2012). High-resolution topographic surveying using the Structure-from-Motion (SfM) algorithm is a low-cost and user-friendly photogrammetric technique to obtain high-resolution datasets. The SfM method solves the camera pose and scene geometry simultaneously and automatically, using highly redundant bundle adjustment based on matching features in multiple overlapping, offset images (Westoby et al. 2012). SfM-Processing was performed using Agisoft Metashape Professional (Version 1.6.1 64 bit). Agisoft Metashape Professional performs well to reconstruct landscape 3D point clouds and the different steps of the process are configurable and can be controlled (Laporte-Fauret et al. 2019). Images were fed into the software and the quality (tool “estimate image quality”) and position was determined respectives images were chosen to cover the study area. Using the “Aling Photos” tool images were aligned creating tie points (2D) and a Depth Maps (high quality, mild filtering) was created (3D). With the help of the Build Dense Cloud tool, set to high quality, the data points were created that represent the study area in 3D. Consecutively an orthomosaic of the study area was created using the Build Orthomosaic tool. An orthomosaic is a photogrammetrically orthorectified image product that has been mosaicked from a collection of images and corrected for geometric distortion to create a seamless mosaic dataset. Due to the high-resolution input data and the processing without compression a high-resolution orthomosaic was achieved with a pixel size of 2.1 cm/pix covering the study area. This detailed, high-resolution geolocated photo representation of the study site is the basis for the following analytical steps. A digital elevation model (DEM) was computed using the “Build DEM” tool. Its dimensions resulted herein in a 16.5 cm/pix size to cover the entire study site. Final adjustment of elevation has been done using the Copernicus Digital Elevation Model (https://spacedata.copernicus.eu/de/collections/copernicus-digital-elevation-model) using QGIS (https://www.qgis.org/de/site/). Laporte-Fauret, Q., et al. (2019). "Low-Cost UAV for high-resolution and large-scale coastal dune change monitoring using photogrammetry." Journal of Marine Science and Engineering 7(3): 63. Micheletti, N., Chandler, J. H., & Lane, S. N. (2015). Structure from motion (SFM) photogrammetry. In L. E. Clarke, & J. M. Nield (Eds.), Geomorphological techniques (Online Edition) (pp. 1–12, Chapter 2.2.2). British Society for Geomorphology Westoby, M. J., et al. (2012). "‘Structure-from-Motion’photogrammetry: A low-cost, effective tool for geoscience applications." Geomorphology 179: 300-314.
    Schlagwort(e): Biota ; Landscape Evolution
    Materialart: Dataset , Sub data for DTM configuration
    Format: ZIP
    Standort Signatur Erwartet Verfügbarkeit
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  • 3
    Publikationsdatum: 2024-01-19
    Beschreibung: Abstract
    Beschreibung: The present dataset correspond to georeferenced high-resolution DEMs (0.1-0.32 m) and orthophotos (0.035-0.08 m) of crustal faults&039; scarps and outcrops, derived from UAV imagery data obtained during a field campaign in December 2021. The imagery data was processed with Agisoft PhotoScan 1.4.0 (e.g., Uysal et al., 2015) for 4 key sites (~2.8 km²) between Quebrada de Tana and Quebrada Aroma, Northernmost Chile, and used as part of the input data for a fault database of the study area.
    Schlagwort(e): Imagery/Base Maps/Earth Cover ; Terrestrial Observation ; Quaternary Geology ; Geomorphology ; Structural Geology ; Tectonics ; Neotectonics ; 551 Geology, hydrology, meteorology
    Materialart: Dataset , DEMs and Orthophotos
    Format: 1590842661 Bytes
    Format: GeoTIFF
    Standort Signatur Erwartet Verfügbarkeit
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  • 4
    Publikationsdatum: 2024-01-19
    Beschreibung: Other
    Beschreibung: Statistics generated by Stacks pipeline and detailed cluster evaluation done by STRUCTURE Harvester tool Supplementary data of the manuscript (Tables&Figures).
    Schlagwort(e): Biota ; Population Genetics
    Materialart: DataPaper , Text files and other formats
    Format: ZIP
    Standort Signatur Erwartet Verfügbarkeit
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  • 5
    Publikationsdatum: 2023-12-15
    Beschreibung: Other
    Beschreibung: SNPs Data for Huidobria chilensis generated by the stacks pipeline and filtered for further processing
    Schlagwort(e): Biota ; Population Genetics
    Materialart: Dataset , Input File
    Format: ZIP
    Standort Signatur Erwartet Verfügbarkeit
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  • 6
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    Unbekannt
    CRC1211 Database (CRC1211DB)
    Publikationsdatum: 2023-10-26
    Beschreibung: Abstract
    Beschreibung: The database contains 90 taxa (3 outgroups and 87 ingroups) and a combined matrix of COI, 16S, and Wg genes (COI=1-1516; 16S=1517-1973; Wg=1974-2460) of Psectrascelis which was used for the phylogenetic analyses in the paper "The colonization of the Puna and Atacama Biogeographic Province by sister clades of Psectrascelis (Coleoptera: Tenebrionidae): Synchronous expansion without spatial overlap" published in the Journal of Biogeography.
    Schlagwort(e): Biota ; Biodiversity ; Evolution ; Biogeography
    Materialart: Dataset , Dataset
    Format: ASCII
    Standort Signatur Erwartet Verfügbarkeit
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  • 7
    Publikationsdatum: 2023-01-23
    Beschreibung: TableOfContents
    Beschreibung: The file contains the transcriptome dataset used in the study Phylogenomics of darkling beetles (Coleoptera: Tenebrionidae) from the Atacama Desert. Directory including: Supplemental Data S1 (Data_S1). Dataset used for ML and BI analyses comprising 34 peptide precursors from 83 genera of Tenebrionidae (47 tribes, seven subfamilies), including the 30 genera from the Atacama Desert. Files: - Neuropeptide precursors matrix for ML analysis (DataS1_NP_Matrix_for_ML: amino acids in PHYLIP format). - Neuropeptide precursors matrix for BI analysis, including partitions and evolutionary models for each partition from ModelFinder (DataS1_NP_Matrix_for_BI: amino acids in NEXUS format). - Partition schemes of Neuropeptide precursors matrix for ML analysis /DataS1_ML_NP_Partition_schemes). Supplemental Data S2 (Data_S1). Dataset used for ML analysis comprising 1742 orthogroups from 83 genera of Tenebrionidae (47 tribes, seven subfamilies), including the 30 genera from the Atacama Desert. - 1742 orthogroups matrix for ML analysis (DataS2_1742_OG_ML: amino acids in PHYLIP format). - Partition schemes of 1742 orthogroups matrix for ML analysis (DataS2_1742_OG_ML_partitions_scheme)
    Schlagwort(e): Biota ; Phylogeny ; Evolution ; Insects ; Biodiversity
    Materialart: Dataset , Dataset
    Format: ZIP
    Standort Signatur Erwartet Verfügbarkeit
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