The influence of pre-quaternary underlying terrain on the formation of loess landforms, i.e., the geomorphological inheritance issue, is a focus in studies of loess landforms. On the basis of multi-source information, we used GIS spatial analysis methods to construct a simulated digital elevation model of a pre-quaternary paleotopographic surface in a severe soil erosion area of the Loess Plateau. To reveal the spatial relationship between underlying paleotopography and modern terrain, an XY scatter diagram, hypsometric curve, gradient and concavity of terrain profiles are used in the experiments. The experiments show that the altitude, gradient and concavity results have significant linear positive correlation between both terrains, which shows a relatively strong landform inheritance relationship, particularly in the intact and complete loess deposit areas. Despite the current surface appearing somewhat changed from the original shape of the underlying terrain under different erosion forces, we reveal that the modern terrain generally smoothes the topographic relief of underlying terrain in the loess deposition process. Our results deepen understanding of the characteristics of geomorphological inheritance in the formation and evolution of loess landforms.
XIONG LiYangTANG GuoAnYUAN BaoYinLU ZhongChenLI FaYuanZHANG Lei
The spatial structure characteristics of landform are the foundation of geomorphologic classification and recognition.This paper proposed a new method on quantifying spatial structure characteristics of terrain surface based on improved 3D Lacunarity model.Lacunarity curve and its numerical integration are used in this model to improve traditional classification result that different morphological types may share the close value of indexes based on global statistical analysis.Experiments at four test areas with different landform types show that improved 3D Lacunarity model can effectively distinguish different morphological types per texture analysis.Higher sensitivity in distinguishing the tiny differences of texture characteristics of terrain surface shows that the quantification method by 3D Lacu-narity model and its numerical integration presented in this paper could contribute to improving the accuracy of land-form classifications and relative studies.
This paper presents a new method for simulating the evolution of a gully head in a loess catchment with cellular automata(CA) based on the Fisher discriminant. The experimental site is an indoor loess catchment that was constructed in a fixed-intensity rainfall erosion test facility. Nine high-resolution digital elevation model(DEM) data sets were gathered by close range photogrammetry during different phases of the experiment. To simulate the evolution of the catchment gully head, we assumed the following. First, the 5th and 6th DEM data sets were used as a data source for acquiring the location of the catchment gully head and for obtaining spatial variables with GIS spatial analysis tools. Second, the Fisher discriminant was used to calculate the weight of the spatial variables to determine the transition probabilities. Third, CA model was structured to simulate the evolution of the gully head by iterative looping. The status of the cell in the CA models was dynamically updated at the end of each loop to obtain realistic results. Finally, the nearest neighbor, G-function, K-function, Moran′s I and fractal indexes were used to evaluate the model results. Overall, the CA model can be used to simulate the evolution of a loess gully head. The experiment demonstrated the advantages of the CA model which can simulate the dynamic evolution of gully head evolution in a catchment.
LIU XiaojingTANG Guo'anYANG JianyiSHEN ZhouPAN Ting
