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  2. Aerial Peruvian Andes Campaign (ALPACA) Dataset 2019
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    Datenpaket: Aerial Peruvian Andes Campaign (ALPACA) Dataset 2019

    Alternativer Identifier:
    (KITopen-DOI) 10.5445/IR/1000118082
    Verwandter Identifier:
    -
    Ersteller/in:
    Riese, Felix M. [Riese, Felix M.]

    Schroers, Samuel [Schroers, Samuel]

    Wienhöfer, Jan https://orcid.org/0000-0003-4970-508X [Wienhöfer, Jan]

    Keller, Sina [Keller, Sina]
    Beitragende:
    (Other)
    Wagner, Philipp [Wagner, Philipp]

    (Other)
    Bocanegra, Julian [Bocanegra, Julian]
    Titel:
    Aerial Peruvian Andes Campaign (ALPACA) Dataset 2019
    Weitere Titel:
    -
    Beschreibung:
    (Abstract) The Aerial Peruvian Andes Campaign (ALPACA) dataset was acquired during a measurement campaign of the Institute of Photogrammetry and Remote Sensing (IPF) and the Institute of Water and River Basin Management - Hydrology (IWG) of the Karlsruhe Institute of Technology (KIT). The measurement campaign was conducted in Peru, in the catchment area of the river Lurín near Lima, in April 2019. Areas in five different locations between 2700 m and 3700 m above mean sea level are included. The ALPACA dataset consists of hyperspectral data in the range of 900 nm to 2500 nm and soil moisture point data in the range of 4 % to 89 %. The hyperspectral data was acquired with a Headwall Hyperspec SWIR sensor, which was mounted on DJI Matrice 600 Pro an Unmanned Aerial Vehicle. About 27 600 square meters of hyperspectral data were acquired with a pixel edge length of about 3 cm. A detailed description of the data acquisition can be found in [1]. The soil moisture data was measured with a handheld ThetaProbe sensor. As a result, 236 soil moisture values are provided. The point measurements were performed in a grid of various distances between 5 m and 15 m. The processing of the dataset is described in [1] and published in [2]. Acknowledgment: The ALPACA dataset is published as part of the Trust project, which is funded by the German Federal Ministry of Education and Research (BMBF). We thank Philipp Wagner and Julian Bocanegra for their help during the measurement campaign. Further, we thank Stefan Hinz and Erwin Zehe. **References:** [1] Felix M. Riese. "Development and Applications of Machine Learning Methods for Hyperspectral Data." Ph.D. Thesis. Karlsruhe Institute of Technology, Karlsruhe, Germany. 2020. [2] Felix M. Riese. "Processing Scripts for the ALPACA Dataset." Zenodo. 2020.
    (Technical Remarks) **Folder "hy_data/":** Hyperspectral data for the five measurement areas area1, area2_1, area2_2, area3, area4, area5, as GeoTiff (.tif) files with header (.hdr) files. - Coordinate system: WGS 84 (EPSG 4326) - 170 spectral bands, included in the header files - Information about the calibration and corrections are included in the header files **Folder "sm_data/":** Soil moisture data of the five measurement areas 1, 2, 3, 4, and 5. The measurements are provided in `peru_soilmoisture.csv`. The columns are defined as follows: - area: Measurement areas 1-5 (integer) - long: Longitude coordinate, WGS 84, in degrees (float) - lat: Latitude coordinate, WGS 84, in degrees (float) - soilmoisture_perc: Volumetric soil moisture content, in percent (float) - weather: Notes about weather conditions (string) - datetime: Date of the soil moisture measurement and start date of a measurement, in Peru Time (PET) (string in the iso 8601 format "YYYY-MM-DD hh:mm:ss")
    Schlagworte:
    hyperspectral
    short-wave infrared
    soil moisture
    multi-sensor experiment
    UAV
    Zugehörige Informationen:
    -
    Sprache:
    -
    Herausgeber/in:
    Karlsruhe Institute of Technology
    Erstellungsjahr:
    Fachgebiet:
    Geological Science
    Objekttyp:
    Dataset
    Datenquelle:
    -
    Verwendete Software:
    -
    Datenverarbeitung:
    -
    Erscheinungsjahr:
    Rechteinhaber/in:
    Riese, Felix M.

    Schroers, Samuel

    Keller, Sina
    Förderung:
    -
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    Status:
    Publiziert
    Eingestellt von:
    kitopen
    Erstellt am:
    Archivierungsdatum:
    2023-06-21
    Archivgröße:
    39,7 GB
    Archiversteller:
    kitopen
    Archiv-Prüfsumme:
    e382122e234f67a2305dc2f7d2b8bab0 (MD5)
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