Automatic landform stratification and environmental correlation for modelling loess landscapes in North Otago, South Island, New Zealand

Hughes, Matthew W.; Schmidt, Jochen; Almond, Peter C.

doi:10.1016/j.geoderma.2008.11.024

Cited by 12 publications

(3 citation statements)

References 31 publications

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“…In the north of the study area, loess deposition occurred during the Quaternary, resulting in more or less thick and scattered current patches of silty materials (Haase et al, 2007). The distribution and the thickness of these Quaternary loess (aeolian silt) deposits strongly influence soil properties (Hughes et al, 2009), but their spatial distribution is highly complex; thus, they are of major interest for the prediction of soil spatial distribution. Other superficial formations of interest are alluvial (terraces and modern deposits) and colluvial deposits.…”

Section: Study Areamentioning

confidence: 99%

Extrapolation at regional scale of local soil knowledge using boosted classification trees: A two-step approach

et al. 2012

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Section: Study Areamentioning

confidence: 99%

Extrapolation at regional scale of local soil knowledge using boosted classification trees: A two-step approach

et al. 2012

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“…Aeolian-derived soils are widespread throughout the world, e.g., the Huangtu Plateau in central China and the West European Loess Belt. However, unlike bedrock-weathering-dominated landscapes, which have been extensively studied in the literature [e.g., Gilbert, 1877;Carson and Kirkby, 1972;Heimsath et al, 1997;Vanwalleghem et al, 2013], our understanding of aeolian-derived soil evolution is still somewhat conceptual and qualitative in nature [Hughes et al, 2009[Hughes et al, , 2010.…”

Section: Introductionmentioning

confidence: 99%

The effects of sediment transport, weathering, and aeolian mechanisms on soil evolution

et al. 2015

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Aeolian-derived soils are found throughout the world. Soil evolution processes in aeolian-dominated landscapes differ from processes in bedrock-weathering landscapes by a number of key aspects including the lack of (1) soil production depth dependency, (2) surface armoring, and (3) grain size self-organization in the soil profile. We use here a soil evolution model (mARM5D) to study the differences between aeolian and bedrock-weathering-dominated landscapes by analyzing soil evolution on a hillslope under various aeolian and bedrock-soil supply settings subject to fluvial and diffusive sediment transport. The model simulates spatial and temporal variation in soil particle size distribution (PSD) and profile depth for each grid cell on the landscape, as a function of physical weathering, aeolian deposition, and diffusive and fluvial sediment transport. Our results indicate that surface armoring plays a major role in soil evolution. Under bedrock-weathering-dominated conditions, armoring reduces soil erosion and in conjunction with depth-dependent soil production, leads to steady state soil grading and depth and a relatively uniform soil distribution. In contrast, aeolian-dominated landscapes tend to have considerable spatial variability in soil depth and PSD. Our results also indicate that in contrast with diffusive transport, which is assumed to be PSD independent, fluvial sediment transport is strongly influenced by the soil production mechanism (aeolian or bedrock weathering). Based on the results presented here, we propose that aeolian-dominated landscapes are more responsive to environmental changes (e.g., climatic and anthropogenic) compared with bedrock-weathering landscapes. We further propose that this sensitivity may help explain the patchy soil distribution that is often observed in aeolian-dominated regions.

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“…With the rapid development of photogrammetry, remote sensing technology and geographic information science, the acquisition of high-precision loess topographic data became more convenient, promoting the extraction of loess features [21,22]. On the one hand, a series of terrain parameters are derived based on DEM by calculating the elevation change in a certain analysis window (i.e., 3 × 3 or 5 × 5), such as the average slope gradient, topographic relief, coefficient of elevation variation and surface cutting depth [23][24][25][26]. These terrain parameters present significant differences in different landform zones, which are also applied to explore landform development.…”

Section: Introductionmentioning

confidence: 99%

An Exploration of Loess Landform Development Based on Population Ecology Method

Yang

2022

IJGI

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The study of gully characteristics is one of the most effective ways to explore the loess landform development in the Loess Plateau of China. However, current studies mostly focus on gullies’ overall characteristics and ignore the different composition of the whole gully system. Therefore, a new perspective is provided in this paper for exploring loess landform development from the population characteristics of the gully system. Firstly, different types of gullies were extracted based on DEM and high-resolution images in three sample watersheds, including hillslope ephemeral gully, bank gully and different-level valley gully. Secondly, population characteristics from the amount, length, age structure and convergent relationship were calculated and analyzed by referring to the biological population in ecology. Finally, the development stages of loess landform in three watersheds were explored based on their population characteristics. The results showed that: (1) The population characteristics, including number density, length density, age structure and convergence, were obviously different in three sample watersheds. (2) The development differences of three watersheds were obtained by synthesizing all population characteristics: Linjiajian was the most developed and oldest watershed, followed by Yangjiaju and then Wangjiagou. (3) The comparison based on the existing soil erosion intensity map and predisposing factors proved that the findings of this paper were more reasonable than that of the traditional hypsometric integral. This research provides a new quantitative-based approach to explore the development degree of loess landform from the gully population, and is a beneficial attempt to combine geomorphology and ecology, further supplementing and improving the study of loess landform development.

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Automatic landform stratification and environmental correlation for modelling loess landscapes in North Otago, South Island, New Zealand

Cited by 12 publications

References 31 publications

Extrapolation at regional scale of local soil knowledge using boosted classification trees: A two-step approach

Extrapolation at regional scale of local soil knowledge using boosted classification trees: A two-step approach

The effects of sediment transport, weathering, and aeolian mechanisms on soil evolution

An Exploration of Loess Landform Development Based on Population Ecology Method

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