Journal
EUROPEAN JOURNAL OF SOIL SCIENCE
Volume 60, Issue 3, Pages 431-442Publisher
WILEY
DOI: 10.1111/j.1365-2389.2009.01129.x
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Funding
- The UK Natural Environment Research Council [CROFT14137]
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The ability to quantitatively and spatially assess soil surface roughness is important in geomorphology and land degradation studies. This paper describes the results of an experiment designed to investigate whether hyperspectral directional reflectance factors can describe fine-scale variations in soil surface roughness. A Canadian silt loam soil was sieved to an aggregate size range of 1-4.75 mm and exposed to five different artificial rainfall durations to produce soils displaying progressively decreasing levels of surface roughness. Each soil state was measured using a point laser profiling instrument at 2 mm spatial resolution, in order to provide information on the structure and spatial arrangement of soil particles. Hyperspectral directional reflectance factors were measured using an Analytical Spectral Devices FieldSpec Pro Spectroradiometer (range 350-2500 nm), at a range of measurement angles (theta(r) = -60 degrees to +60 degrees) and illumination angle conditions (theta(i) = 28 degrees-74 degrees). Directional reflectance factors varied with illumination and view angles, and with soil structure. Geostatistically-derived indicators of soil surface roughness (sill variance) were regressed with directional reflectance factors. The results showed a strong relationship between directional reflectance and surface roughness (R-2 = 0.94 where theta(r) = -60 degrees, theta(i) = 67 degrees-74 degrees). This fine-scale quasi-natural experiment allowed the control of slope, initial aggregate size and rainfall exposure, permitting an investigation into factors affecting a soil's bidirectional reflectance response. This has highlighted the relationship between fine-scale variations in surface roughness, illumination angle and reflectance response. The results show how the technique could provide a quantitative measure of surface roughness at fine spatial scales.
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