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Hyperspectral benchmark dataset on soil moisture

Riese, Felix M.; Keller, Sina

Abstract (englisch):
Hyperspectral and soil-moisture data from a field campaign based on a soil sample. Karlsruhe (Germany), 2017.

This dataset was measured in a five-day field campaign in May 2017 in Karlsruhe, Germany. An undisturbed soil sample is the centerpiece of the measurement setup. The soil sample consists of bare soil without any vegetation and was taken in the area near Waldbronn, Germany.

Introducing paper: Felix M. Riese and Sina Keller, “Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data,” in 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, 2018, accepted.

The following sensors were deployed:

- Cubert UHD 285 hyperspectral snapshot camera recording 50 by 50 images with 125 spectral bands ranging from 450 nm to 950 nm and a spectral resolution of 4 nm.
- TRIME-PICO time-domain reflectometry (TDR) sensor in a depth of 2 cm measuring the soil moisture in percent.

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Originalveröffentlichung
DOI: 10.5281/zenodo.1227837
Zugehörige Institution(en) am KIT Fakultät für Bauingenieur-, Geo- und Umweltwissenschaften (BGU)
Institut für Photogrammetrie und Fernerkundung (IPF)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Forschungsdaten
Publikationsdatum 24.04.2018
Erstellungsdatum 16.05.2017 - 26.05.2017
Sprache Englisch
Identifikator KITopen-ID: 1000084164
Projektinformation FOR 1598 CAOS; TP B (DFG, DFG KOORD, HI 1289/6-2)
Schlagwörter hyperspectral dataset
Liesmich

Hyperspectral and soil-moisture data from a field campaign based on a soil sample. Karlsruhe (Germany), 2017.

This dataset was measured in a five-day field campaign in May 2017 in Karlsruhe, Germany. An undisturbed soil sample is the centerpiece of the measurement setup. The soil sample consists of bare soil without any vegetation and was taken in the area near Waldbronn, Germany.

Introducing paper: Felix M. Riese and Sina Keller, “Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data,” in 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, 2018, accepted.

The following sensors were deployed:

  • Cubert UHD 285 hyperspectral snapshot camera recording 50 by 50 images with 125 spectral bands ranging from 450 nm to 950 nm and a spectral resolution of 4 nm.
  • TRIME-PICO time-domain reflectometry (TDR) sensor in a depth of 2 cm measuring the soil moisture in percent.
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