Mapping and dating of arid and semi-arid alluvial fans are of great importance in many Quaternary studies. Yet the most common mapping method of these features is based on visual, qualitative interpretation of air-photos. In this study we examine the feasibility of mapping arid alluvial surfaces by using airborne hyperspectral reflective remote sensing methodology. This technique was tested on Late Pleistocene to Holocene alluvial fan surfaces located in the hyperarid southern Arava valley, Israel. Results of spectral field measurements showed that the surface reflectance is controlled by two main surficial processes, which are used as relative age criteria: the degree of desert pavement development (gravel coverage %) controls the absorption feature depths, while the rock coating development influences significantly the overall reflectance of the surface, but its effect on the absorption feature depths is limited. We show that as the percent of the surface covered by gravels increases, the absorption feature depth of the common gravels, in this case carbonate at 2.33 μm, increases as well; whereas the absorption features depth of the fine particle in-between the gravels, decrease (hydroxyl and ferric absorption features at 2.21 μm, and 0.87 μm, respectively), as the fines are removed from the surface. Using these correlations we were able to map the surface gravel coverage (%) on the entire alluvial fan, by calculating the gravel coverage (%) in each pixel of the hyperspectral image. The prediction of gravel coverage (%) is with accuracy of ± 15% (e.g. gravel coverage of 50% can be predicted to be 35% to 65%). Using extensive accuracy assessment data, we show that the spectral based mapping maintained high accuracy degree (R2 = 0.57 to 0.83). The quantitative methodology developed in this study for mapping alluvial surfaces can be adapted for other surfaces and piedmonts throughout the arid regions of the world.
Bibliographical noteFunding Information:
This project was carried out in collaboration with the Remote Sensing section 1.5 in the GFZ, Potsdam, the DLR-Oberpfaffenhofen, and the AGF-Munich, Germany. We thank Prof. Dr. H. Kaufmann and Dr. M. Schudlock from the GFZ, Dr. M. Frie from the AGF-Munich, and Dr. R. Richter from the DLR for their help and cooperation in almost every stage of this study. We thank M. Dvorachek (GSI) for the SEM analysis. We thank A. Mushkin, A. Trakhtenbrot, N. Levin, Dr. B. Begin, Prof. Y. Enzel, Prof. A. Gillespie, A. Tzurieli, and S. Ashkenazi for fruitful discussions and field assistance. B. Katz helped in editing the text. This project was supported by the GIF research grant I-547-177.02/97. The senior author wishes to thank the US Army Research Office (DAAD19-03-1-0159) for enabling him to summarize this paper.
- Alluvial fan surfaces
- Desert pavement
- Quantitative hyperspectral remote sensing mapping
- Reflectance spectra
- Rock coating