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1.
针对当前单一地貌划分单元造成的分类结果破碎或漏分问题,该文引入双尺度流域单元划分方法,即采用两种不同大小流域单元的组合作为地貌划分基本单元,以提高地貌划分的细分性和完整性。以30 m ASTER GDEM数据为数据源,基于最佳地形因子组合(高程、地势起伏度、坡度、坡度变率、光照模拟值)、双尺度流域单元、CART决策树算法,实现了北回归线(云南段)地区平原(2类)和山地(7类)共9类地貌的划分,双尺度流域单元划分的最佳流量阈值分别为500、2000。通过平均值、标准差、Moran′s I和人工判读结果对分类结果进行检验,发现基于CART决策树的双尺度流域单元地貌分类方法在北回归线(云南段)地区总体精度可达82.1%,Kappa系数为0.793,总体能够准确识别出研究区的地貌类型空间分布特征,是地貌类型划分的一种可行方法。  相似文献   

2.
基于DEM的地貌实体单元自动提取方法   总被引：17，自引：4，他引：13  
我国传统地貌基本形态类型分类强调地貌单元的完整性,界线划分沿地貌实体边界而非规则统计单元,目前尚缺乏地貌实体单元的有效自动提取方法。针对这一难点,本文提出一种基于DEM的地貌实体单元数字提取方法。利用坡度分级,并搜索相邻栅格单元、计算坡度级别内相互连通栅格的面积,建立坡度、面积阈值综合判别规则进行山地平原的自动划分;利用地形倒置、水文淹没分析,将山体划分的二维判别规则扩展到实际三维地形中,并结合地形结构线提取算法进行山体界线自动提取、确定山地地貌实体单元。结果表明,该方法符合我国传统地貌分类体系,能够较好实现山地/平原的自动划分和山体界线的数字提取。  相似文献   

3.
An iterative procedure that implements the classification of continuous topography as a problem in digital image-processing automatically divides an area into categories of surface form; three taxonomic criteria–slope gradient, local convexity, and surface texture–are calculated from a square-grid digital elevation model (DEM). The sequence of programmed operations combines twofold-partitioned maps of the three variables converted to greyscale images, using the mean of each variable as the dividing threshold. To subdivide increasingly subtle topography, grid cells sloping at less than mean gradient of the input DEM are classified by designating mean values of successively lower-sloping subsets of the study area (nested means) as taxonomic thresholds, thereby increasing the number of output categories from the minimum 8 to 12 or 16. Program output is exemplified by 16 topographic types for the world at 1-km spatial resolution (SRTM30 data), the Japanese Islands at 270 m, and part of Hokkaido at 55 m. Because the procedure is unsupervised and reflects frequency distributions of the input variables rather than pre-set criteria, the resulting classes are undefined and must be calibrated empirically by subsequent analysis. Maps of the example classifications reflect physiographic regions, geological structure, and landform as well as slope materials and processes; fine-textured terrain categories tend to correlate with erosional topography or older surfaces, coarse-textured classes with areas of little dissection. In Japan the resulting classes approximate landform types mapped from airphoto analysis, while in the Americas they create map patterns resembling Hammond's terrain types or surface-form classes; SRTM30 output for the United States compares favorably with Fenneman's physical divisions. Experiments are suggested for further developing the method; the Arc/Info AML and the map of terrain classes for the world are available as online downloads.  相似文献   

4.
Landform classification is one of the most important procedures in recognizing and dividing earth surface landforms. However, topographical homogeneity and differences in regional-scale landforms are often ignored by traditional pixel- and object-based landform classification methods based on digital elevation models (DEMs). In this work, a drainage basin object-based method for classifying regional-scale landforms is proposed. Drainage basins with least critical areas are first delineated from DEMs. Then, terrain derivatives of mean elevation, mean slope, drainage density, drainage depth, and terrain texture are employed to characterize the morphology of the drainage basins. Finally, a decision tree based on the topographical characteristics of the drainage basins is constructed and employed to determine the landform classification law. The experiment is validated in the landform classification of regional-scale loess areas in China. Results show that clear boundaries exist in different landforms at the regional scale. Landform type in a specific region shows significant topographical homogeneity under its specific regional geomorphological process. Classification accuracies are 87.3 and 86.3% for the field investigation and model validation, respectively. Spatial patterns of classified landforms and their proximity to sediment sources and other factors can be regarded as indicators of the evolutionary process of loess landform formation.  相似文献   

5.
地形元素（如山脊、沟谷等）是地表形态类型基本单元,通过地形元素的不同空间组合可形成更高级别的地貌类型。现有的地形元素提取方法大多依靠地形属性计算,难以克服地形元素的空间相关性表达与局部地形属性计算存在不对应的矛盾,Jasiewicz和Stepinski提出的Geomorphons方法——基于高程相对差异信息进行地形元素分类,可避免这一问题,但Geomorphons方法本质上是在单一分析尺度上选择地形特征点用于判别,易受局部地形起伏的影响而造成误分类。针对这一问题,设计出一种多分析尺度下综合判别的地形元素分类方法。应用结果表明：相比Geomorphons方法,利用该方法得到的地形元素的分类结果更为合理。  相似文献   

6.
月球地貌是月球表面发生的地质和地貌过程的结果,月球地貌单元的划分和等级分类体系的构建是月球地貌学研究的基础,也是月球地貌图制图的基础和关键科学问题。地貌学是研究形态和成因的科学,高程和起伏度是最基本的地貌指标。本文基于LOLA（Lunar Orbiter Laser Altimeter） DEM数据以及LOLA和SELENE TC（Terrain Camera）融合的DEM数据（SLDEM2015,文中简称SLDEM）,利用均值变点法确定月表起伏度计算的最佳窗口,并以起伏度100 m、200 m、300 m、700 m、1500 m及2500 m为阈值将月球表面分为微起伏平原（< 100 m）、微起伏台地[100 m, 200 m）、微小起伏丘陵[200 m, 300 m）、小起伏山地[300 m, 700 m）、中起伏山地[700 m, 1500 m）、大起伏山地[1500 m, 2500 m）及极大起伏山地（≥ 2500 m）地貌7个类型。划分结果显示：微起伏平原主要分布在月海平原区域、部分有玄武岩充填的撞击盆地的盆底区域以及撞击坑坑底区域;微起伏台地主要分布在月海和月陆区域的交界区域;微小起伏丘陵主要分布在月溪和皱脊等构造单元区域;小起伏山地主要分布在撞击坑中央峰及坑底断裂区域;中起伏山地主要分布在撞击坑坑底和坑壁过渡区域、撞击坑坑壁和坑缘过渡区域、撞击盆地盆底与盆壁过渡区域以及盆壁与盆缘过渡区域;大起伏和极大起伏山地主要分布在撞击坑坑壁区域及撞击盆地盆壁区域。本文确定的月表起伏度分级标准可以对月表数字地貌分类体系的构建和月球地貌图集的编研提供定量标准和重要参考。  相似文献   

7.
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8.
An efficient and accurate method of generating landslide susceptibility maps is very important to mitigate the loss of properties and lives caused by this type of geological hazard. This study focuses on the development of an accurate and efficient method of data integration, processing and generation of a landslide susceptibility map using an ANN and data from ASTER images. The method contains two major phases. The first phase is the data integration and analysis, and the second is the Artificial Neural Network training and mapping. The data integration and analysis phase involve GIS based statistical analysis relating landslide occurrence to geological and DEM (digital elevation model) derived geomorphological parameters. The parameters include slope, aspect, elevation, geology, density of geological boundaries and distance to the boundaries. This phase determines the geological and geomorphological factors that are significantly correlated with landslide occurrence. The second phase further relates the landslide susceptibility index to the important geological and geomorphological parameters identified in the first phase through ANN training. The trained ANN is then used to generate a landslide susceptibility map. Landslide data from the 2004 Niigata earthquake and a DEM derived from ASTER images were used. The area provided enough landslide data to check the efficiency and accuracy of the developed method. Based on the initial results of the experiment, the developed method is more than 90% accurate in determining the probability of landslide occurrence in a particular area.  相似文献   

9.
本文分别利用光学立体和In SAR技术生成了东南极Grove山地区15 m分辨率的ASTER DEM和20 m分辨率的In SAR DEM。在利用ASTER立体像对生成DEM的过程中引入ICESat测高数据作为高程控制以减少错误匹配,提高DEM垂直精度;而在利用ERS tandem数据生成DEM后,选取ICESat测高数据对In SAR DEM进行倾斜面纠正,以消除基线不精确估计等带来的影响。通过与未作控制的ICESat测高数据进行比较,评价了两种DEM的精度并对误差进行了分析。同时,比较了两种DEM的差异,并分析了造成这些差异的原因,探讨了两种技术生成南极冰盖DEM的优势和不足。最后结合两DEM的优势,融合生成了Grove山地区高精度的DEM。  相似文献   

10.
Lunar landforms are the results of geological and geomorphic processes on the lunar surface. It is very important to identify the types of lunar landforms. Geomorphology is the scientific study of the origin and evolution of morphological landforms on planetary surfaces. Elevation and relief amplitude are the most commonly used geomorphic indices in geomorphological classification studies. Previous studies have determined the elevation classification criteria of the lunar surface. In this paper, we focus on the classification criteria of the topographic relief amplitude of the lunar surface. To estimate the optimal window for calculating the relief amplitude of the lunar surface, we use the mean change-point method based on LOLA (Lunar Orbiter Laser Altimeter) Digital Elevation Model (DEM) data and SLDEM2015 DEM data combining observations from LOLA and SELenological and Engineering Explorer Terrain Camera (SELENE TC). The classification criterion of the lunar surface relief amplitude is then determined according to the statistical analysis of basic lunar landforms. Taking the topographic relief amplitudes of 100 m, 200 m, 300 m, 700 m, 1500 m and 2500 m as thresholds, the lunar surface is divided into seven geomorphic types, including minor microrelief plains (< 100 m), minor microrelief platforms [100 m, 200 m), microrelief landforms [200 m, 300 m), small relief landforms [300 m, 700 m), medium relief landforms [700 m, 1500 m), large relief landforms [1500 m, 2500 m) and extremely large relief landforms (≥ 2500 m). The minor microrelief plains are mainly distributed in the maria and the basalt filled floors of craters and basins, while the minor microrelief platforms are mainly in the transition regions between the maria and highlands. The microrelief landforms are mainly located in regions with relatively high topography, such as wrinkle ridges and sinuous rilles in the mare. The small relief landforms are mainly scattered in the central peak and floor fractures of craters. The medium relief landforms are mainly distributed in the transition regions between crater floors and crater walls, between crater walls and crater rims, between basin floors and basin walls, and between basin walls and basin rims. Large and extremely large relief landforms are mainly found along crater walls and basin walls. The classification criteria determination for assessing lunar surface relief amplitude described in this paper can provide important references for the construction of digital lunar surface geomorphology classification schemes.  相似文献   

11.
This paper proposes a quantitative method to classify landforms using four morphometric parameters from DEM-derived thematic raster maps of slope and topographic openness. Because the different surficial processes and stages in the evolution of slopes create landscapes with different shapes, these parameters may lead to a genetic interpretation of topography. The raster maps of slope and topographic openness were constructed for Northeast Honshu, Japan, from 50-m DEMs. The mean and standard deviation of morphometric parameters within a 3050 m by 3050 m moving window on the raster maps were calculated. The results for some training areas show that constructional/depositional and erosional landforms with different relief have different morphometric characteristics. A supervised landform classification for Northeast Honshu using the knowledge from the training areas revealed a ladder geomorphological structure composed of high mountains, ranges and volcanoes. The close relationship between the ladder geomorphological structure and volcano distribution indicates that the structure reflects the magmatic plumbing system from the upper mantle to the crust of the Northeast Honshu arc.  相似文献   

12.
Using geomorphological knowledge, spatial data and GIS methods, one can obtain phytogeomorphological site variables describing interactions between landforms and vegetation. We used 15 site variables derived from maps to explain forest site productivity in southern and central Finland expressed as dominant height of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies [L.] Karst.) with ages of 30–110 years. These site variables were grouped into two: Group 1 with seven variables describing geographical conditions of sites including climate, and Group 2 with eight variables describing local morphometric and soil properties. We calculated slope and aspect from a 25 × 25 m DEM. The catchment area, calcium content in soil, length of the growing season, radiation index, sea index, lake index, past highest shoreline and total annual temperature sum with threshold + 5 °C were also obtained. Then we classified the landforms of 688 sample plots into four major types and 15 sub-types. We applied regression analysis to explain the tree height as a function of the tree age and the phytogeomorphological site variables. When the tree height was explained with the tree age and the Group 1 variables, the remaining standard error of the model was 16.6–17.9%. When the Group 2 variables were added to the analysis, the standard error decreased slightly. The most significant variables were the temperature sum, latitude coordinate and length of the growing season. Other significant variables were elevation, slope and aspect. The major landform types, sub-types and watershed area did not explain the tree height. Furthermore, if the forest site types determined in the field were included, the remaining standard error decreased by ca. 2%, showing the importance of field information.  相似文献   

13.
Sanjit K. Deb  Aly I. El-Kadi   《Geomorphology》2009,108(3-4):219-233
The deterministic Stability INdex MAPping (SINMAP) model, which integrates a mechanistic infinite-slope stability model and a hydrological model, was applied to assess susceptibility of slopes in 32 shallow-landslide-prone watersheds of the eastern to southern areas of Oahu, Hawaii, USA. Input to the model includes a 10-m Digital Elevation Model (DEM), an inventory of storm-induced landslides that occurred from 1949 to 2006, and listings of soil-strength and hydrological parameters including transmissivity and steady-state recharge. The study area of ca. 384 km2 was divided into four calibration regions with different geotechnical and hydrological characteristics. All parameter values were separately calibrated using observed landslides as references. The study used a quasi-dynamic scenario of soil wetness resulting from extreme daily rainfall events with a return period of 50 years. The return period was based on almost-90-year-long (1919–2007) daily rainfall records from 26 raingauge stations in the study area. Output of the SINMAP model includes slope-stability-index-distribution maps, slope-versus-specific-catchment-area charts, and statistical summaries for each region.The SINMAP model assessed susceptibility at the locations of all 226 observed shallow landslides and classified these susceptible areas as unstable. About 55% of the study area was predicted as highly unstable, highlighting a critical island problem. The SINMAP predictions were compared to an existing debris-flow-hazard map. Areas classified as unstable in the current study were classified as low-to-moderate and moderate-to-high debris-flow hazard risks by the prior mapping. The slope-stability maps provided by this study will aid in explaining the causes of known landslides, making emergency decisions, and, ultimately mitigating future landslide risks. The maps may be further improved by incorporating heterogeneous and anisotropic soil properties and spatial and temporal variation of rainfalls as well as by improving the accuracy of the DEM and the locations of shallow landslide initiation.  相似文献   

14.
Marshes are ubiquitous landforms in estuaries and lagoons, where important hydrological, morphological and ecological processes take place. These areas attenuate sea action on the coast and act as sediment trapping zones. Due to their ecosystem functions and effects on coastal stabilization, marshes are crucial structures in tidal environments, both biologically and geomorphologically, and are fundamental elements in wetland restoration and coastal realignment schemes. The spatially-distributed study of the geomorphology of intertidal areas using remotely-sensed digital terrain models remains problematic, owing to their small relief, often of the order of a few tens of centimetres, and to the presence of short and dense vegetation, which strongly reduces the number of resolvable ground returns. Here, we use high-resolution Terrestrial Laser Scanning ( 200 returns/m2) to retrieve a high-resolution and high-accuracy Digital Terrain Model within a tidal marsh in the Venice lagoon. To this aim we apply a new filtering scheme to Terrestrial Laser Scanner data which selects the lowest values within moving windows, whose optimal size is determined with the aid of a limited number of ancillary Differential GPS data in order to maximize resolution while ensuring the identification of true ground returns. The accuracy of the filtered data is further refined using classifications of the intensity of the returns to extract additional information on the surface (ground or canopy) originating the returning laser beam. Validations against about 200 reference Differential GPS ground elevation observations indicates that the best separation of canopy and ground signals is obtained using a low-pass filter with window size of the order of 1 m and the maximum likelihood classifier to further refine the detection of ground returns. In this case the average estimation error is about 1 cm (slight overestimation of ground elevation), while its standard deviation is about 3 cm. Our approach allows the separation of laser returns coming from the low marsh vegetation from those coming from the marsh surface. The overall result is a new observation technique producing Digital Terrain and Digital Surface Models in areas with very small relief, which is shown to provide unprecedented high-resolution and high-accuracy characterizations of marsh morphology.  相似文献   

15.
This paper presents a semi-automatic method using an unsupervised neural network to analyze geomorphometric features as landform elements. The Shuttle Radar Topography Mission (SRTM) provided detailed digital elevation models (DEMs) for all land masses between 60°N and 57°S. Exploiting these data for recognition and extraction of geomorphometric features is a challenging task. Results obtained with two methods, Wood's morphometric parameterization and the Self Organizing Map (SOM), are presented in this paper.Four morphometric parameters (slope, minimum curvature, maximum curvature and cross-sectional curvature) were derived by fitting a bivariate quadratic surface with a window size of 5 by 5 to the SRTM DEM. These parameters were then used as input to the two methods. Wood's morphometric parameterization provides point-based features (peak, pit and pass), line-based features (channel and ridge) and area-based features (planar). Since point-based features are defined as having a very small slope when their neighbors are considered, two tolerance values (slope tolerance and curvature tolerance) are introduced. Selection of suitable values for the tolerance parameters is crucial for obtaining useful results.The SOM as an unsupervised neural network algorithm is employed for the classification of the same morphometric parameters into ten classes characterized by morphometric position (crest, channel, ridge and plan area) subdivided by slope ranges. These terrain features are generic landform element and can be used to improve mapping and modeling of soils, vegetation, and land use, as well as ecological, hydrological and geomorphological features. These landform elements are the smallest homogeneous divisions of the land surface at the given resolution. The result showed that the SOM is an efficient scalable tool for analyzing geomorphometric features as meaningful landform elements, and uses the full potential of morphometric characteristics.  相似文献   

16.
设计城市地貌图应注重城市地貌在建城区、边缘区和城市经济辐射区范围内的区域分异规律。编制城市地貌图应遵循：环境功能，应用性，突出重点和图面协调三个原则。据此编制了成都市１：６５００建城区，１：５万边缘区和１：２０万城市经济辐射区三种城市地貌图。  相似文献   

17.
High resolution topographic data along fault zones are important aids in the delineation of recently active breaks. A 15 km-long portion of the south-central San Andreas Fault (SAF) along the southern Cholame segment contains well preserved tectonic landforms such as benches, troughs, scarps, and aligned ridges that indicate recurring earthquake slip. Recently acquired LiDAR topographic data along the entire southern SAF (“B4” project) have shot densities of 3–4 m− 2. Computed from the LiDAR returns, Digital Elevation Models (DEMs) of 0.25 to 0.5 m resolution using local binning with inverse distance weighting and 0.8 m or larger search radii depict the tectonic landforms at paleoseismic sites well enough to assess them confidently. Mapping of recently active breaks using a LiDAR-only based approach compares well with aerial photographic and field based methods. The fault zone varies in width from meters to nearly 1 km and is comprised of numerous en echelon meter to kilometer-length overlapping sub parallel fault surfaces bounding differentially moving blocks that elongate parallel to the SAF. The semantic variations of what constitutes “active” and the importance of secondary traces influence the breadth and complexity of the resulting fault trace maps.  相似文献   

18.
Soil erosion is the most influential component of land degradation for its strong impacts on both natural and agricultural environments. In order to support effective intervention and recovery policies for eroded areas, monitoring techniques should take into account the space–time variability of the processes involved, and make use of assessed mapping methodologies as baseline criteria for studying the dynamics of landform development. When using multispectral data for mapping eroded areas, low spectral separability is a significant limit in areas with complex features, where soil materials are frequently remixed by surface runoff. Since multispectral satellite images are a valuable data source for multi-temporal analyses of erosion processes at the medium scale, we assessed how accurately a badland area can be identified from LANDSAT TM and ETM data. A protocol for an optimal mapping was built up by testing the performance of different supervised algorithms and input layers (spectral and morphological). Tests were carried out in a well-known badland area of Basilicata, Italy, with an extension of  8000 ha. Results obtained from the use of spectral bands (with and without thermal channel) and principal components returned an overall accuracy ranging from 53% (for classification on first three components) to 72% (for classification on all bands from TM), with low values for the kappa coefficient (0.30–0.50), showing that the spectral information alone are insufficient to accurately identify badland areas. In order to improve mapping, we found that the integration of slopes and aspects derived from a Digital Elevation Model (DEM) can overcome problems inherent to the low separability of spectral signatures. The use of morphological data was tested for different classification algorithms and integration approaches. In discriminating badlands, the better performing algorithm was MLC (Maximum Likelihood Classifier) and the best results were obtained by integrating all seven bands (including TIR) with slope and aspect maps as input within the classifier (A > 0.85 and K  0.75 for both the sensors). We selected such parameters because they play an important role in characterising badlands of study area from a morphological perspective but the proposed approach is also conceptually simple and can be easily exported to other areas. The obtained results support the hypothesis that the combined use of remote sensing imagery and auxiliary morphological data significantly improves the mapping of badlands over large areas with heterogeneous features, thus providing a useful methodology for long-term studies on soil erosion processes.  相似文献   

19.
新疆地貌空间分布格局分析   总被引：4，自引：1，他引：3  
程维明  柴慧霞  周成虎  陈曦 《地理研究》2009,28(5):1157-1169
以高分辨率遥感影像为本底数据的最新新疆地貌数据,能提高定量化地貌格局分析结果的准确性、客观性和科学性。本文利用地学统计和GIS空间分析方法,基于最新新疆地貌数据,定量化分析了地貌的分布特征、空间格局。结果表明:(1)大地貌单元中,平原地貌约占新疆总面积的1/3;(2)地势分级,中海拔地貌占绝对优势,约占全疆总面积1/2;(3)形态类型中,丘陵地貌在地势起伏中占主导地位,面积最大,主要分布在两大沙漠中,以沙丘形式分布;(4)基本地貌类型,中海拔丘陵最多,占总面积的21.417%;(5)成因类型中,流水、风成和干燥作用占主导地位;(6)受不同形成条件和控制范围的影响,新疆成因类型的分布特征随着海拔和起伏的变化而变化;(7)总体上,新疆地貌的空间格局呈现出两大特征:水平环形特征和垂直地带性特征。  相似文献   

20.
Developing approaches to automate the analysis of the massive amounts of data sent back from the Moon will generate significant benefits for the field of lunar geomorphology.In this paper,we outline an automated method for mapping lunar landforms that is based on digital terrain analysis.An iterative self-organizing(ISO)cluster unsupervised classification enables the automatic mapping of landforms via a series of input raster bands that utilize six geomorphometric parameters.These parameters divide landforms into a number of spatially extended,topographically homogeneous segments that exhibit similar terrain attributes and neighborhood properties.To illustrate the applicability of our approach,we apply it to three representative test sites on the Moon,automatically presenting our results as a thematic landform map.We also quantitatively evaluated this approach using a series of confusion matrices,achieving overall accuracies as high as 83.34% and Kappa coefficients(K)as high as 0.77.An immediate version of our algorithm can also be applied for automatically mapping large-scale lunar landforms and for the quantitative comparison of lunar surface morphologies.  相似文献   

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