Estimation of water-infiltration rate in Mediterranean sandy soils using airborne hyperspectral sensors

Nicolas Francos*, Sabine Chabrillat, Nikolaos Tziolas, Robert Milewski, Maximilian Brell, Nikiforos Samarinas, Theodora Angelopoulou, Nikolaos Tsakiridis, Vasillis Liakopoulos, Thomas Ruhtz, Eyal Ben-Dor

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The efficiency of spectral-based assessments of soil attributes using soil spectral libraries (SSLs) covering the visible–near-infrared–shortwave-infrared (VNIR–SWIR: 400–2500 nm) region has been proven in many studies. Nevertheless, as traditional SSLs are commonly developed under laboratory conditions, their application is limited for the assessment of soil surface-dependent properties such as water-infiltration rate (WIR) into the soil profile due to the sampling procedure. Currently, few studies are based on field SSLs for the prediction of physical soil properties. This study used a field-based protocol to measure soil reflectance data and WIR simultaneously in the field, and generate spectral-based decision tree models to predict WIR solely from field spectral measurements using the SoilPRO® assembly. The obtained models were applied to both airborne hyperspectral (HySpex) and satellite multispectral (Sentinel 2) data on a pixel-by-pixel basis to generate raster maps of WIR. The study areas were located in Macedonia (Greece), and were optimal for mapping WIR because the soil crust was well developed, and sites were characterized by bare soils (no vegetation coverage) with a sandy structure. Whereas the WIR map generated with the satellite data was poor due to the low spatial and spectral resolution of Sentinel 2 (20 m, 9 bands), the results obtained with the airborne hyperspectral HySpex sensor (5 m, 408 bands) were satisfactorily validated in the ground-truth stage with good prediction accuracy due to high spatial and spectral resolution. Validation accuracy of the HySpex observations using all field samples gave R2 = 0.68, whereas the predictions of the ground-truth samples that were not part of the calibration stage (field validation group) of the model gave R2 = 0.59. We concluded that these results are favourable for rapid estimation of soil surface conditions and pave the way for a wider spatial view from orbital hyperspectral remote-sensing sensors.

Original languageEnglish
Article number107476
JournalCatena
Volume233
DOIs
StatePublished - Dec 2023

Funding

FundersFunder number
European Cooperation in Science and TechnologyCA16219
Bundesministerium für Wirtschaft und EnergieDLR/BMWi 50 EE 1529
Ministry of National Infrastructure, Energy and Water Resources218-17-007, JPI2018
Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ
Universidad Autónoma de Sinaloa
Ministry of Energy, Israel

    Keywords

    • Decision tree
    • HySpex
    • Hyperspectral remote sensing
    • Mediterranean soil
    • Sandy soil
    • Sentinel 2
    • Soil spectroscopy
    • Water-infiltration rate

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