Next Article in Journal
Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture
Next Article in Special Issue
Improved Mapping of Potentially Toxic Elements in Soil via Integration of Multiple Data Sources and Various Geostatistical Methods
Previous Article in Journal
Susceptibility Analysis of the Mt. Umyeon Landslide Area Using a Physical Slope Model and Probabilistic Method
Previous Article in Special Issue
Mapping of Peat Thickness Using a Multi-Receiver Electromagnetic Induction Instrument
Article

Utilization of Multi-Temporal Microwave Remote Sensing Data within a Geostatistical Regionalization Approach for the Derivation of Soil Texture

by 1,*,† and 2,†
1
Department of Geography, Ludwig-Maximilians-Universität München, Luisenstrasse 37, 80333 Munich, Germany
2
Leibniz-Institute of Vegetable and Ornamental Crops (IGZ), Theodor-Echtermeyer-Weg 1, 14947 Grossbeeren, Germany
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Remote Sens. 2020, 12(16), 2660; https://doi.org/10.3390/rs12162660
Received: 8 July 2020 / Revised: 14 August 2020 / Accepted: 15 August 2020 / Published: 18 August 2020
Land Surface Models (LSM) have become indispensable tools to quantify water and nutrient fluxes in support of land management strategies or the prediction of climate change impacts. However, the utilization of LSM requires soil and vegetation parameters, which are seldom available in high spatial distribution or in an appropriate temporal frequency. As shown in recent studies, the quality of these model input parameters, especially the spatial heterogeneity and temporal variability of soil parameters, has a strong effect on LSM simulations. This paper assesses the potential of microwave remote sensing data for retrieving soil physical properties such as soil texture. Microwave remote sensing is able to penetrate in an imaged media (soil, vegetation), thus being capable of retrieving information beneath such a surface. In this study, airborne remote sensing data acquired at 1.3 GHz and in different polarization is utilized in conjunction with geostatistics to retrieve information about soil texture. The developed approach is validated with in-situ data from different field campaigns carried out over the TERENO test-site “North-Eastern German Lowland Observatorium”. With the proposed approach a high accuracy of the retrieved soil texture with a mean RMSE of 2.42 (Mass-%) could be achieved outperforming classical deterministic and geostatistical approaches. View Full-Text
Keywords: remote sensing; SAR; geostatistics; regression kriging; soil texture remote sensing; SAR; geostatistics; regression kriging; soil texture
Show Figures

Graphical abstract

MDPI and ACS Style

Marzahn, P.; Meyer, S. Utilization of Multi-Temporal Microwave Remote Sensing Data within a Geostatistical Regionalization Approach for the Derivation of Soil Texture. Remote Sens. 2020, 12, 2660. https://doi.org/10.3390/rs12162660

AMA Style

Marzahn P, Meyer S. Utilization of Multi-Temporal Microwave Remote Sensing Data within a Geostatistical Regionalization Approach for the Derivation of Soil Texture. Remote Sensing. 2020; 12(16):2660. https://doi.org/10.3390/rs12162660

Chicago/Turabian Style

Marzahn, Philip, and Swen Meyer. 2020. "Utilization of Multi-Temporal Microwave Remote Sensing Data within a Geostatistical Regionalization Approach for the Derivation of Soil Texture" Remote Sensing 12, no. 16: 2660. https://doi.org/10.3390/rs12162660

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop