As one of most active gully types in the Chinese Loess Plateau,bank gullies generally indicate soil loss and land degradation.This study addressed the lack of detailed,large scale monitoring of bank gullies and proposed a semi-automatic method for extracting bank gullies,given typical topographic features based on 5 m resolution DEMs.First,channel networks,including bank gullies,are extracted through an iterative channel bum-in algorithm.Second,gully heads are correctly positioned based on the spatial relationship between gully heads and their corresponding gully shoulder lines.Third,bank gullies are distinguished from other gullies using the newly proposed topographic measurement of "relative gully depth (RGD)."The experimental results from the loess hilly area of the Linjiajian watershed in the Chinese Loess Plateau show that the producer accuracy reaches 87.5%. The accuracy is affected by the DEM resolution and RGD parameters,as well as the accuracy of the gully shoulder line.The application in the Madigou watershed with a high DEM resolution validated the duplicability of this method in other areas.The overall performance shows that bank gullies can be extracted with acceptable accuracy over a large area,which provides essential information for research on soil erosion,geomorphology,and environmental ecology.
A simulated loess watershed, where the loess material and relief properly represent the true loess surface, is adopted to investigate the variation in slope spectrum with loess watershed evolution. The evolution of the simulated loess watershed was driven by the exogenetic force of artificial rainfall. For a period of three months, twenty artificial rainfall events with different intensities and durations were carried out. In the process, nine DEM data sets, each with 10mm grid resolution, were established by the method of close-range photogrammetry. The slope spectra were then extracted from these DEMs. Subsequent series of carefully designed quantitative analyses indicated a strong relationship between the slope spectrum and the evolution of the simulated loess watershed. Quantitative indices of the slope spectrum varied regularly following the evolution of the simulated loess watershed. Mean slope, slope spectrum information entropy （H）, terrain driving force （Td）, Mean patch area （AREA_MN）, Contagion Index （CONTAG）, and Patch Cohesion Index （COHESION） kept increasing following the evolution of the simulated watershed, while skewness （S）, Perimeter-Area Fractal Dimension （PAFRAC）, and Interspersion and Juxtaposition Index （IJl） represented an opposite trend. All the indices changed actively in the early and active development periods, but slowly in the stable development periods. These experimental results indicate that the time series of slope spectra was able to effectively depict the slope distribution of the simulated loess watershed, thus presenting a potential method for model- ing loess landforms.
Gully feature mapping is an indispensable prerequisite for the motioning and control of gully erosion which is a widespread natural hazard. The increasing availability of high-resolution Digital Elevation Model(DEM) and remote sensing imagery, combined with developed object-based methods enables automatic gully feature mapping. But still few studies have specifically focused on gully feature mapping on different scales. In this study, an object-based approach to two-level gully feature mapping, including gully-affected areas and bank gullies, was developed and tested on 1-m DEM and Worldview-3 imagery of a catchment in the Chinese Loess Plateau. The methodology includes a sequence of data preparation, image segmentation, metric calculation, and random forest based classification. The results of the two-level mapping were based on a random forest model after investigating the effects of feature selection and class-imbalance problem. Results show that the segmentation strategy adopted in this paper which considers the topographic information and optimal parameter combination can improve the segmentation results. The distribution of the gully-affected area is closely related to topographic information, however, the spectral features are more dominant for bank gully mapping. The highest overall accuracy of the gully-affected area mapping was 93.06% with four topographic features. The highest overall accuracy of bank gully mapping is 78.5% when all features are adopted. The proposed approach is a creditable option for hierarchical mapping of gully feature information, which is suitable for the application in hily Loess Plateau region.
LIU KaiDING HuTANG GuoanZHU A-XingYANG XinJIANG ShengCAO Jianjun
