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1.
土壤厚度信息对土壤碳储量估算、水文-生态过程模拟等有着重要影响,但我国北方石质山区缺乏现势性好、分辨率高的土壤厚度分布数据及其快速获取方法。基于北方石质山区土壤厚度的分布特点,先将地貌信息和植被类型叠加生成制图单元,再根据每类单元的特征,针对性地选取地形参数和地表覆被参数作为指示土壤厚度空间分布的环境变量,结合少量土壤样点,依据模糊推理模型,构建了基于分层制图策略的土壤厚度空间推测方法。以河北省滦平县虎什哈流域为例,利用从ASTER GDEMs提取的地形变量和从我国环境减灾卫星影像(HJ-A)提取的地表覆被信息对土壤厚度进行了推测。结果表明,该方法精度较高,是利用免费地形和遥感数据进行低成本快速土壤制图的实用途径。  相似文献   

2.
This paper documents resolution dependencies in terrain analysis and describes how they vary across landform location. Six terrain attributes were evaluated as a function of DEM resolution—slope, plan curvature, profile curvature, north–south slope orientation, east–west slope orientation, and topographic wetness index. The research highlights the effect of varying spatial resolution through a spatial sampling/resampling scheme while maintaining sets of indexed sample points at various resolutions. Tested sample points therefore coincide exactly between two directly compared resolutions in terms of their location and elevation value. An unsupervised landform classification procedure based on statistical clustering algorithms was employed to define landform classes in a reproducible manner. Correlation and regression analyses identified sensitive and consistent responses for each attribute as resolution was changed, although the tested terrain attributes responded in characteristically different ways. These responses displayed distinguishable patterns among various landform classes, a conclusion that was further verified by a series of two‐sample, two‐tailed t‐tests.  相似文献   

3.
朱磊  盛建东  贾宏涛 《干旱区地理》2019,42(5):1115-1123
准确、高效地掌握草原土壤属性的空间分布能够为草地资源境管理提供基础信息和参考依据。相比于传统土壤调查方法,基于模糊逻辑的土壤—环境推理能够提高野外采样效率和预测制图精度,被广泛应用于数字土壤制图。但由于土壤自身的空间变异性及其与环境条件间的非线性,现有推理模型的稳定性较低,尚未在高寒草原区进行应用。选择新疆巴音布鲁克典型亚高山草原地区约4 km^2区域为研究区,以高程、坡度、坡向、沿剖面曲率、沿等高线曲率、地形湿度指数6个地形因子为土壤环境因子,采用模糊C均值聚类(Fuzzy C-means Clustering,FCM)方法对环境因子聚类,得到9个环境因子组合,并在隶属度值高的环境因子组合中心共设置18个典型点。运用土壤—环境推理方法模拟研究区表层土壤pH值空间分布,其变化范围在7.170~8.186之间。选取35个独立样本进行精度检验(均匀采样点16个,横截面采样点9个,垂直带采样点10个),模拟结果与实测值基本吻合,且基于模糊聚类和土壤—环境推理方法的模拟精度高于普通克里格法和反距离权重法。通过基于模糊逻辑和土壤—环境推理的数字土壤制图方法在小尺度区域的运用验证,结果表明基于典型点的采样方案能够快速、有效地对区域土壤属性进行空间模拟,该方法对于类似小尺度的研究区同样有效。  相似文献   

4.
Abstract

We present a model for describing the visibility of a polyhedral terrain from a fixed viewpoint, based on a collection of nested horizons. We briefly introduce the concepts of mathematical and digital terrain models, and some background notions for visibility problems on terrains. Then, we define horizons on a polyhedral terrain, and introduce a visibility model, that we call the horizon map. We present a construction algorithm and a data structure for encoding the horizon map, and show how it can be used for solving point visibility queries with respect to a fixed viewpoint.  相似文献   

5.
Abstract

Rule-based classifiers are used regularly with geographical information systems to map categorical attributes on the basis of a set of numeric or unordered categorical attributes. Although a variety of methods exist for inducing rule-based classifiers from training data, these tend to produce large numbers of rules when the data has noise. This paper describes a method for inducing compact rule-sets whose classification accuracy can, at least in some domains, compare favourably with that achieved by larger less succinct rule-sets produced by alternative methods. One rule is induced for each output class. The condition list for this rule represents a box in n-dimensional attribute space, formed by intersecting conditions which exclude other classes. Despite this simplicity, the classifier performed well in the test application prediction of soil classes in the Port Hills, New Zealand, on the basis of regolith type and topographic attributes obtained from a digital terrain model.  相似文献   

6.
Accurately mapping the spatial distribution of soil total nitrogen is important to precision agriculture and environmental management. Geostatistical methods have been frequently used for predictive mapping of soil properties. Recently, a local regression method, geographically weighted regression (GWR), got the attention of environmentalists as an alternative in spatial modeling of environmental attributes, due to its capability of incorporating various auxiliary variables with spatially varied correlation coefficients. The objective of this study is to compare GWR and ordinary cokriging (OCK) in predictive mapping of soil total nitrogen (TN) using multiple environmental variables. 353 soil Samples within the surface horizon of 0–20 cm in a study area were collected, and their TN contents were measured for calibrating and validating the GWR and OCK interpolations. The environmental variables finally chosen as auxiliary data include elevation, land use types, and soil types. Results indicate that, although OCK is slightly better than GWR in global accuracy of soil TN prediction (the adjusted R2 for GWR and OCK are 0.5746 and 0.6858, respectively), the soil TN map interpolated by GWR shows many details reflecting the spatial variations of major auxiliary variables while OCK smoothes out almost all local details. Geographically weighted regression could account for both the spatial trend and local variations, whilst OCK had difficulties to capture local variations. It is concluded that GWR is a more promising spatial interpolation method compared to OCK in predicting soil TN and potentially other soil properties, if a suitable set of auxiliary variables are available and selected.  相似文献   

7.
ABSTRACT

Terrain feature detection is a fundamental task in terrain analysis and landscape scene interpretation. Discovering where a specific feature (i.e. sand dune, crater, etc.) is located and how it evolves over time is essential for understanding landform processes and their impacts on the environment, ecosystem, and human population. Traditional induction-based approaches are challenged by their inefficiency for generalizing diverse and complex terrain features as well as their performance for scalable processing of the massive geospatial data available. This paper presents a new deep learning (DL) approach to support automatic detection of terrain features from remotely sensed images. The novelty of this work lies in: (1) a terrain feature database containing 12,000 remotely sensed images (1,000 original images and 11,000 derived images from data augmentation) that supports data-driven model training and new discovery; (2) a DL-based object detection network empowered by ensemble learning and deep and deeper convolutional neural networks to achieve high-accuracy object detection; and (3) fine-tuning the model’s characteristics and behaviors to identify the best combination of hyperparameters and other network factors. The introduction of DL into geospatial applications is expected to contribute significantly to intelligent terrain analysis, landscape scene interpretation, and the maturation of spatial data science.  相似文献   

8.
Abstract

Surface soil texture controls many important ecological, hydrological, and geomorphic processes in arid regions and is therefore important from a land-management perspective. Soil survey efforts have traditionally fulfilled this need, but they are constrained by the size, remoteness, and inaccessibility of many arid regions, which renders simple field measurements prohibitively expensive. This article compares several different predictive soil-mapping techniques with a sparse data set in order to develop surficial soil texture maps. Our results suggest that data collected at the landscape scale can be used as input to predictive soil-mapping techniques to create maps of soil texture at higher fidelity and a fraction of the cost than would be required using traditional methods.  相似文献   

9.
Soil formation depends upon several factors such as parent material, soil biota, topography and climate. It is difficult to use conventional soil survey methods for mapping the depth of soil in complex mountainous terrains. In this context, the present study aimed to estimate the soil depth for a large area (330.35 km2) using different geo-environmental factors through a soil-landscape regression kriging (RK) model in the Darjeeling Himalayas. RK with seven predictor variables such as elevation, slope, aspect, general curvature, topographic wetness index, distance from the streams and land use, was used to estimate the soil depth. While topographic parameters were derived from an 8-m resolution digital elevation model, the ortho-rectified Cartosat-1 satellite image was used to prepare the land use map. Soil depth measured at 148 sites within the study area was used to calibrate and validate the RK model. The result showed that the RK model with the seven predictors could explain 67% spatial variability of soil depth with a prediction variance between 0.23 and 0.42 m at the test site. In the regression analysis, land use (0.133) and slope (–0.016) were identified as significant determinants of soil depth. The prediction map showed higher soil depth in south-facing slopes and near valleys in comparison to other areas. Mean, mean absolute and root mean-square errors were used to access the reliability of the prediction, which indicated a goodness-of-fit of the RK model.  相似文献   

10.
Effects of spatial autocorrelation (SAC), or spatial structure, have often been neglected in the conventional models of pedogeomorphological processes. Based on soil, vegetation, and topographic data collected in a coastal dunefield in western Korea, this research developed three soil moisture–landscape models, each incorporating SAC at fine, broad, and multiple scales, respectively, into a non-spatial ordinary least squares (OLS) model. All of these spatially explicit models showed better performance than the OLS model, as consistently indicated by R2, Akaike’s information criterion, and Moran’s I. In particular, the best model was proved to be the one using spatial eigenvector mapping, a technique that accounts for spatial structure at multiple scales simultaneously. After including SAC, predictor variables with greater inherent spatial structure underwent more reduction in their predictive power than those with less structure. This finding implies that the environmental variables pedogeomorphologists have perceived important in the conventional regression modeling may have a reduced predictive power in reality, in cases where they possess a significant amount of SAC. This research demonstrates that accounting for spatial structure not only helps to avoid the violation of statistical assumptions, but also allows a better understanding of dynamic soil hydrological processes occurring at different spatial scales.  相似文献   

11.
Abstract

Recent developments in theory and computer software mean that it is now relatively straightforward to evaluate how attribute errors are propagated through quantitative spatial models in GIS. A major problem, however, is to estimate the errors associated with the inputs to these spatial models. A first approach is to use the root mean square error, but in many cases it is better to estimate the errors from the degree of spatial variation and the method used for mapping. It is essential to decide at an early stage whether one should use a discrete model of spatial variation (DMSV—homogeneous areas, abrupt boundaries), a continuous model (CMSV—a continuously varying regionalized variable field) or a mixture of both (MMSV—mixed model of spatial variation). Maps of predictions and prediction error standard deviations are different in all three cases, and it is crucial for error estimation which model of spatial variation is used. The choice of model has been insufficiently studied in depth, but can be based on prior information about the kinds of spatial processes and patterns that are present, or on validation results. When undetermined it is sensible to adopt the MMSV in order to bypass the rigidity of the DMSV and CMSV. These issues are explored and illustrated using data on the mean highest groundwater level in a polder area in the Netherlands.  相似文献   

12.
Quantification of spatial gradation of slope positions   总被引：6，自引：0，他引：6  
Transition between slope positions (e.g., ridge, shoulder slope, back slope, foot slope, and valley) is often gradual. Quantification of spatial transitions or spatial gradations between slope positions can increase the accuracy of terrain parameterization for geographical or ecological modeling, especially for digital soil mapping at a fine scale. Current models for characterizing the spatial gradation of slope positions based on a gridded DEM either focus solely on the parameter space or depend on too many rules defined by topographic attributes, which makes such approaches impractical. The typical locations of a slope position contain the characteristics of the slope position in both parameter space and spatial context. Thus, the spatial gradation of slope positions can be quantified by comparing terrain characteristics (spatial and parametrical) of given locations to those at typical locations. Based on this idea, this paper proposes an approach to quantifying the spatial gradation of slope positions by using typical locations as prototypes. This approach includes two parts: the first is to extract the typical locations of each slope position and treat them as the prototypes of this position; and the second is to compute the similarity between a given location and the prototypes based on both local topographic attributes and spatial context. The new approach characterizes slope position gradation in both the attribute domain (i.e., parameter space) and the spatial domain (i.e., geographic space) in an easy and practicable way. Applications show that the new approach can quantitatively describe spatial gradations among a set of slope positions. Comparison of spatial gradation of A-horizon sand percentages with the quantified spatial gradation of slope positions indicates that the latter reflects slope processes, confirming the effectiveness of the approach. The comparison of a soil subgroup map of the study area with the maximum similarity map derived from the approach also suggests that the quantified spatial gradation of slope position can be used to aid geographical modeling such as digital soil mapping.  相似文献   

13.
Estimation of Areal Soil Moisture by use of Terrain Data   总被引：2，自引：0，他引：2  
In this study measured soil moisture is related to primary and secondary topographical attributes within two small-scale drainage basins. The study sites are the Buddby and the Dansarhllarna drainage basins within the NOPEX area. The primary topographic attributes slope, aspect, plan and profile curvature, and the secondary topographic attribute, the wetness index, are derived from a 5 m resolution digital elevation model. The relationship with measured soil moisture in the Buddby basin is investigated by linear regression analysis. Based on mean plot measurements for the whole measurement period two different models were established, resulting in a high R 2 value. The best model was achieved with slope, profile curvature and aspect as regression variables. The models obtained were further used to regionalise the results into basin scale at both Buddby and Dansarhällarna. This demonstrated a soil moisture pattern different from the pattern resulting from the wetness index. Finally, models were established, based on two different dates of field campaigns. The results showed a good agreement with the observed soil moisture values, and a higher R 2 value was obtained when using the wetness index for the medium wet period compared to the wettest period. Further analysis is needed to verify the physical significance of the results and their suitability for hydrological modelling.  相似文献   

14.
在横山县朱家沟小流域采集111个样点,分析土壤属性与地形因子相互关系,进行空间预测分析。结果表明:土壤密度与复合地形指数CTI显著正相关,土壤有机质与复合地形指数CTI、汇流动力指数SPI、沉积物运移指数STI显著负相关,全磷只与坡度β显著负相关。多元线性逐步回归模型对于土壤密度和有机质拟合较好,而对于全磷,预测结果较差;回归-克里格预测有效地减小了残差,消除了平滑效应,预测极差更宽,对于局部的变异及地形、土地利用的关系体现更为细化,提高了预测精度。  相似文献   

15.
ABSTRACT

Cellular automata (CA) models are in growing use for land-use change simulation and future scenario prediction. It is necessary to conduct model assessment that reports the quality of simulation results and how well the models reproduce reliable spatial patterns. Here, we review 347 CA articles published during 1999–2018 identified by a Scholar Google search using ‘cellular automata’, ‘land’ and ‘urban’ as keywords. Our review demonstrates that, during the past two decades, 89% of the publications include model assessment related to dataset, procedure and result using more than ten different methods. Among all methods, cell-by-cell comparison and landscape analysis were most frequently applied in the CA model assessment; specifically, overall accuracy and standard Kappa coefficient respectively rank first and second among all metrics. The end-state assessment is often criticized by modelers because it cannot adequately reflect the modeling ability of CA models. We provide five suggestions to the method selection, aiming to offer a background framework for future method choices as well as urging to focus on the assessment of input data and error propagation, procedure, quantitative and spatial change, and the impact of driving factors.  相似文献   

16.
Abstract

Abstract. To achieve high levels of performance in parallel geoprocessing, the underlying spatial structure and relations of spatial models must be accounted for and exploited during decomposition into parallel processes. Spatial models are classified from two perspectives, the domain of modelling and the scope of operations, and a framework of strategies is developed to guide the decomposition of models with different characteristics into parallel processes. Two models are decomposed using these strategies: hill-shading on digital elevation models and the construction of Delaunay Triangulations. Performance statistics are presented for implementations of these algorithms on a MIMD computer.  相似文献   

17.

Rather than seeing the oceans as an expansive void, researchers using acoustic technologies can detect the heterogeneity of biological resources and view the marine environment as a three-dimensional landscape. Underwater remote sensing, using acoustics, provides high resolution maps of the spatial distribution of organisms in aquatic ecosystems. Analyzing the spatial pattern of species distribution within the water column and the impact of that organization on ecological processes bridges the fields of fisheries and spatial analysis. Tools and concepts familiar to geographers, such as remote sensing, GIS, and landscape ecology, contribute to the investigation of large lake and marine ecosystems.  相似文献   

18.
海南岛不同地形上土壤性质的多样性分析   总被引：19，自引：1，他引：18  
张学雷  陈杰  张甘霖 《地理学报》2003,58(6):839-844
多样性指数长时间以来在生态学领域被用于分析不同生态体的发生规律,本研究将类似手段用于某些土壤性质 (土壤发生层次、土层厚度和土壤容重) 多样性的分析中,讨论基于海南岛土壤－地形体数字化数据库 (SOTER),通过对不同地形上土壤发生层次、土层厚度和土壤容重等某些土壤性质类别SOTER单元的丰富度指数 (S)、多样性指数 (Shannon指数H') 和均匀度指数 (Pielou E) 的计算,类别多度分布模型的应用,并在地理信息系统环境中实现了海南岛不同地形上某些土壤性质多样性分析的数字化表达。  相似文献   

19.
古尔班通古特沙漠植被与环境关系分析   总被引：2，自引：0，他引：2  
The Gurbantunggut Desert is the largest stable and semi-stable sand desert in China, yet few data exist on vegetation pattern and species-environment relationships for these diverse desert landscapes. The sand dunes of the survey area are mainly of the longi- tudinal form from north to south, but checkerboard-shaped and honeycomb-shaped forms are also present, with the height of 10-50 m. We measured vegetation and soil data on north-south transects and compared them with vegetation and soil data on east-west transects. Analysis revealed that the varying trend and strength of the species diversity, dominance and cover of the plant communities in the longitudinal and transverse directions across the landscape are significantly different. The results of CCA ordination show that the microhabitats of soil organic matter （OM）, soil salts （TS）, sorting index （ σ ）, topsoil water-content （SM） and pH relate to the differences in vegetation observed as differences in species assemblage from salt-intolerant ephemerals, micro-subshrubs and subshrubs to salt-tolerant shrubs and micro-arbors. The terrain （alt.） and soil texture （the contents of Mz and Ф 1） affect the spatial differentiation of many species. However, this spatial differentiation is not so marked on transects running longitudinally with the landscape, in the same direction as the dunes. The species of the desert vegetation have formed three assemblages under the action of habitat gradients, relating to three sections running transversely across the landscape, at right angles to the direction of the dune crests. In the mid-east section of the study area the topography is higher, with sand-lands or dune-slopes with coarse particles. Here the dominant vegetation comprises shrubs and subshrubs of Seriphidium santofium and Ephedra distachya, with large numbers of ephemeral and ephemeroid plants of Senecio subdentatus, and Carex physodes in spring and summer. On the soil of the dune-slopes in the mid-west of the study area, with coarse partic  相似文献   

20.
Abstract

This paper describes a framework for the role of geographical information systems (GIS) in the monitoring and management of hazardous waste sites. Compilation of required information, incorporation of existing strategies for waste monitoring, analysis of these data in a GIS environment and the integration of computerized models for transport processes are discussed. Examples for the analysis of spatial data using techniques of cartographic overlay and the implementation of geo-statistical methods on monitoring data are provided from work in progress by the authors. These examples are set in the context of developing a fully integrated monitoring and management system utilizing GIS technology.  相似文献   

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