A. Introduction B. Digital soil mapping: current state and perspectives C. Conception and handling of soil databases D. Sampling methods for creating digital soil maps E. New environmental covariates for digital soil mapping F. Quantitative modelling for digital soil mapping F.i : Examples of predicting soil classes F.ii : Examples of predicting soil attributes G. Quality assessment and representation of digital soil maps

Digital soil mapping : an introductory perspective

Soil (regolith) depth is a crucial input for modeling earth surface phenomena. However, most studies ignore its spatial variability. Techniques that map the spatial variability of soil depth are of three types: (1) physically-based; (2) empirico-statistical from environmental correlates; and (3) interpolation from point observations. In an anthropogenic landscape, soil depth does not depend primarily on natural processes, making it difficult to apply a physically-based approach. The present study compares empirico-statistical methods with geostatistical methods for predicting soil depth in such a landscape: Aruvikkal catchment (9.5 km 2 ) in the Western Ghats of Kerala, India. Regression kriging applied on blocks of 20 m by 20 m using the environmental covariates elevation, slope, aspect, curvature, wetness index, land use and distance from streams, proved to be the best predictor of soil depth. This model explains 52% of the variability of soil depth in the catchment; with a prediction variance of 0.05 to 0.19. A Gaussian simulation was attempted for a more realistic visualization of the depth, as opposed to the smooth kriging prediction. The most important explanatory variable of soil depth in this landscape is land use, as expected from the strong human intervention.

Prediction of soil depth using environmental variables in an anthropogenic landscape, a case study in the Western Ghats of Kerala, India.

Riparian forests are assumed to play a crucial role in the global carbon cycle. However, little data are available on C stocks of floodplains in comparison to other terrestrial ecosystems. In this study, we quantified the C stocks of aboveground biomass and soils of riparian vegetation types at 76 sampling sites in the Donau-Auen National Park in Austria. Based on our results and a remotely sensed vegetation map, we estimated total C stocks. Carbon stocks in soils (up to 354 t ha ―1 within 1 m below surface) were huge compared to other terrestrial ecosystems. As expected, soils of different vegetation types showed different texture with a higher percentage of sandy soils at the softwood sites, while loamy soils prevailed at hardwood sites. Total C stocks of vegetation types were significantly different, but reflect differences in woody plant biomass rather than in soil C stocks. Mature hardwood and cottonwood forests proved to have significantly higher total C stocks (474 and 403 t ha ―1 , respectively) than young reforestations (217 t ha ―1 ) and meadows (212 t ha ―1 ). The C pools of softwood forests (356 t ha ―1 ) ranged between those of hardwood/cottonwood forests and of reforestations/meadows. Our study proves the relevance of floodplains as possible C sinks, which should be increasingly taken into account for river management. Furthermore, we conclude that plant-species distribution does not indicate the conditions of sedimentation and soil C sequestration over the time span of interest for the development of soil C stocks.

Carbon stocks of soil and vegetation on Danubian floodplains

What Do We Really Know about the Space–Time Continuum of Soil-Landscapes?

Geomorphologists have to make choices and compromises, as acquisition techniques of geometrical information are numerous, depending on the specific complexity of the targeted three-dimensional objects and the requirements of the end user. This article presents the methodology and the results over a well known and documented site. This ready-to-use, low-altitude, aerial photo methodology reveals itself to be a satisfying compromise between cost, accuracy and difficulty of implementation. The selected equipment package is light enough to enable a quick reaction to unexpected events and the tools and methods are competitive with field acquisition techniques. An evaluation has demonstrated a sub-metric accuracy for the final result.

/pdf/the-use-of-small-format-and-low-altitude-aerial-photos-for-5apkbcbkwj.pdf

The use of small‐format and low‐altitude aerial photos for the realization of high‐resolution DEMs in mountainous areas: application to the Super‐Sauze earthflow (Alpes‐de‐Haute‐Provence, France)

Three-dimensional GIS cartography applied to the study of the spatial variation of soil horizons in a Swiss floodplain

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Three-dimensional GIS cartography applied to the study of the spatial variation of soil horizons in a Swiss floodplain