Jay C. Bell

Digital elevation model resolution: effects on terrain attribute calculation and quantitative soil-landscape modeling

The accuracy of digital elevation models (DEM) and DEM-derived products depends on several factors, including the horizontal resolution and vertical precision at which the elevation data are represented, and the source of the elevation data. This accuracy becomes increasingly important as we extend the use of DEM data for spatial prediction of soil attributes. Our objective was to compare terrain attributes and quantitative soil-landscape models derived from grid-based DEM represented at different horizontal resolutions (10 and 30 m), represented at different vertical precisions (0.1 and 1 m), and acquired from different sources. Decreasing the horizontal resolution of the field survey DEM produced lower slope gradients on steeper slopes, steeper slope gradients on flatter slopes, narrower ranges in curvatures, larger specific catchment areas in upper landscape positions, and lower specific catchment areas values in lower landscape positions. Overall, certain landscape features were less discernible on the 30-m DEM than on the 10-m DEM. Decreased vertical precision produced a large proportion of points with zero slope gradient and zero slope curvature, and a large number of steeply sloping and more highly curved areas. Differences among DEM from different sources were more significant, with less accurate representation of depressions and drainage pathways with the USGS DEM as compared to the field survey DEM. Empirical models developed from different DEM included similar predictive terrain attributes, and were equally successful in predicting A-horizon depth (AHD) in the validation data set.

Delineating patterns of soil drainage class on bare soils using remote sensing analyses

Abstract The high spectral resolution of much satellite imagery has great potential for detailed soil mapping. However, satellite imagery often has low spatial resolution (i.e. 30 m), reducing its utility except for regional inventories. Digital aerial photographs that have been orthorectified (digital orthophoto quads (DOQ)) often have spatial resolution in the range of 1–5 m and can be inexpensive to acquire. DOQs are generally used for qualitative visual interpretation of photo tone and have had limited applications in digital image analysis due to their low spectral variability (usually panchromatic black and white). Our research examines the merging of multiple remote sensing imageries (Landsat TM, DOQ and IKONOS) and digital elevation model (DEM) data to determine optimal combinations for mapping soil drainage classes on bare soil surfaces. Spatial resolutions of these data are 30 m for Landsat TM, 4 m for IKONOS, 0.6 m for the DOQ, and 10 m for the DEM. Overall classification accuracy compared to field-verified samples was 73% using a combination of the DOQ and Landsat TM. The addition of IKONOS imagery did not provide any significant accuracy improvement. Our results demonstrate that DOQ data merged with Landsat TM and a DEM significantly improve our ability to predict spatial patterns of soil drainage classes using image classification techniques when compared to the original soil survey of the study site. For reference, the published soil survey (1:15,840 scale) had an accuracy of 55% for soil drainage class when compared to our field-verified samples. While bare soil surfaces may be limited in many areas, they do provide opportunities where rapid, automated classification techniques are possible and provide useful information for understanding and documenting soil–landscape relationships and spatial variability.

Laboratory comparison of soil redox conditions between red soils and brown soils in Minnesota, USA

Certain soil morphological characteristics create significant problems for hydric soil identification due to lack of commonly observable Fe-based redoximorphic features that indicate seasonally saturated and reduced conditions. Examples include soils with high levels of organic C and red soils (7.5YR or redder) containing high amounts of hematite iron. The objectives of this research were to examine the effects of organic C content and Fe mineralogy on (i) soil redox response and (ii) the development of Fe-based redoximorphic features. Redox reactions related to the fundamental biochemical processes that occur in saturated soils were studied in a controlled laboratory experiment. The experimental design included six columns of red soils (5YR) from northeastern Minnesota and six columns of brown soils (10YR), possessing varying organic carbon contents, from southeastern Minnesota. Redox measurements taken throughout the experiment suggest different soil redox environments between the brown and red soils. The brown soils had redox potentials that decreased gradually and then remained at a constant decreased state around 0.0 mV. Redox potentials for the red soils decreased rapidly and equilibrated in the range of 100 to 300 mV. Variations between these soil responses may be due to different Fe-oxide mineralogies and/or the amount of bioavailable organic carbon.