A new concept dealing with digital analysis of loess terrain,slope spectrum,is presented and discussed in this paper,by introducing its characteristic,represen-tation and extracting method from DEMs. Using 48 geomorph...A new concept dealing with digital analysis of loess terrain,slope spectrum,is presented and discussed in this paper,by introducing its characteristic,represen-tation and extracting method from DEMs. Using 48 geomorphological units in dif-ferent parts of the loess as test areas and 5 m-resolution DEMs as original test data,the quantitative depiction and spatial distribution of slope spectrum in China's Loess Plateau have been studied on the basis of a series of carefully-designed experiments. In addition,initial experiment indicates a strong relationship between the slope spectrum and the loess landform types,displaying a potential importance of the slope spectrum in geomorphological studies. Based on the slope spectrums derived from the 25 m-resolution DEM data in whole loess terrain in northern part of Shaanxi,13 slope spectrum indices were extracted and integrated into a compre-hensive layer with image integration method. Based on that,a series of unsuper-vised classifications was applied in order to make a landform classification in northern Shaanxi Loess Plateau. Experimental results show that the slope spec-trum analysis is an effective method in revealing the macro landform features. A continuous change of slope spectrum from south to north in northern Shaanxi Loess Plateau shows an obvious spatial distribution of different loess landforms. This also proves the great significance of the slope spectrum method in describing the terrain roughness and landform evolution as well as a further understanding on landform genesis and spatial distribution rule of different landforms in the Loess Plateau.展开更多
Slope spectrum has been proved to be a significant methodology in revealing geomorphological features in the study of Chinese loess terrain. The determination of critical areas in deriving slope spectra is an indispen...Slope spectrum has been proved to be a significant methodology in revealing geomorphological features in the study of Chinese loess terrain. The determination of critical areas in deriving slope spectra is an indispensable task. Along with the increase in the size of the study area, the derived spectra are becoming more and more alike, such that their dif- ferences can be ignored in favor of a standard. Subsequently, the test size is defined as the Slope Spectrum Critical Area （SSCA）. SSCA is not only the foundation of the slope spectrum calculation but also, to some extent, a reflection of geomorphological development of loess relief. High resolution DEMs are important in extracting the slope spectrum. A set of 48 DEMs with different landform areas of the Loess Plateau in northern Shaanxi province was selected for the experiment. The spatial distribution of SSCA is investigated with a geo-statistical analysis method, resulting in values ranging from 6.18 km^2 to 35.1 km^2. Primary experimental results show that the spatial distribution of SSCA is correlated with the spatial distribution of the soil erosion intensity, to a certain extent reflecting the terrain complexity. The critical area of the slope spectrum presents a spatial variation trend of weak-strong-weak from north to south. Four terrain parameters, gully density, slope skewness, terrain driving force （Td） and slope of slope （SOS）, were chosen as indicators. There exists a good exponential function relationship between SSCA and gully density, terrain driving force （Td） and SOS and a loga- rithmic function relationship between SSCA and slope skewness. Slope skewness increases, and gully density, terrain driving force and SOS decrease with increasing SSCA. SSCA can be utilized as a discriminating factor to identify loess landforms, in that spatial distributions of SSCA and the evolution of loess landforms are correlative. Following the evolution of a loess landform from tableland to gully-hilly region, this also proves that SSCA can repre展开更多
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 th...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.展开更多
基金the National Natural Science Foundation of China (Grant Nos. 40671148 and 40571120)
文摘A new concept dealing with digital analysis of loess terrain,slope spectrum,is presented and discussed in this paper,by introducing its characteristic,represen-tation and extracting method from DEMs. Using 48 geomorphological units in dif-ferent parts of the loess as test areas and 5 m-resolution DEMs as original test data,the quantitative depiction and spatial distribution of slope spectrum in China's Loess Plateau have been studied on the basis of a series of carefully-designed experiments. In addition,initial experiment indicates a strong relationship between the slope spectrum and the loess landform types,displaying a potential importance of the slope spectrum in geomorphological studies. Based on the slope spectrums derived from the 25 m-resolution DEM data in whole loess terrain in northern part of Shaanxi,13 slope spectrum indices were extracted and integrated into a compre-hensive layer with image integration method. Based on that,a series of unsuper-vised classifications was applied in order to make a landform classification in northern Shaanxi Loess Plateau. Experimental results show that the slope spec-trum analysis is an effective method in revealing the macro landform features. A continuous change of slope spectrum from south to north in northern Shaanxi Loess Plateau shows an obvious spatial distribution of different loess landforms. This also proves the great significance of the slope spectrum method in describing the terrain roughness and landform evolution as well as a further understanding on landform genesis and spatial distribution rule of different landforms in the Loess Plateau.
基金Foundation： National Natural Science Foundation of China, No.41171299, No.41171320, No.41401237
文摘Slope spectrum has been proved to be a significant methodology in revealing geomorphological features in the study of Chinese loess terrain. The determination of critical areas in deriving slope spectra is an indispensable task. Along with the increase in the size of the study area, the derived spectra are becoming more and more alike, such that their dif- ferences can be ignored in favor of a standard. Subsequently, the test size is defined as the Slope Spectrum Critical Area （SSCA）. SSCA is not only the foundation of the slope spectrum calculation but also, to some extent, a reflection of geomorphological development of loess relief. High resolution DEMs are important in extracting the slope spectrum. A set of 48 DEMs with different landform areas of the Loess Plateau in northern Shaanxi province was selected for the experiment. The spatial distribution of SSCA is investigated with a geo-statistical analysis method, resulting in values ranging from 6.18 km^2 to 35.1 km^2. Primary experimental results show that the spatial distribution of SSCA is correlated with the spatial distribution of the soil erosion intensity, to a certain extent reflecting the terrain complexity. The critical area of the slope spectrum presents a spatial variation trend of weak-strong-weak from north to south. Four terrain parameters, gully density, slope skewness, terrain driving force （Td） and slope of slope （SOS）, were chosen as indicators. There exists a good exponential function relationship between SSCA and gully density, terrain driving force （Td） and SOS and a loga- rithmic function relationship between SSCA and slope skewness. Slope skewness increases, and gully density, terrain driving force and SOS decrease with increasing SSCA. SSCA can be utilized as a discriminating factor to identify loess landforms, in that spatial distributions of SSCA and the evolution of loess landforms are correlative. Following the evolution of a loess landform from tableland to gully-hilly region, this also proves that SSCA can repre
基金We are grateful for the financial support from the National Natural Science Foundation of China （Grant Nos. 41171299 and 41271438）, the Priority Academic Program Development of Jiangsu Higher Education Institutions （164320H116） and the foundation of State Key Laboratory of Soil Erosion and Dryland Fanning on the Loess Plateau （10501-1217, K318009902-13）. We are also grateful to Dr. Josef Strobl for his constructive critique of the manuscript. The constructive criticisms and suggestions from anonymous reviewers are also gratefully acknowledged.
文摘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.
