In addition to soil samples, conventional soil maps, and experienced soil surveyors, text about soils(e.g., soil survey reports) is an important potential data source for extracting soil–environment relationships. Co...In addition to soil samples, conventional soil maps, and experienced soil surveyors, text about soils(e.g., soil survey reports) is an important potential data source for extracting soil–environment relationships. Considering that the words describing soil–environment relationships are often mixed with unrelated words, the first step is to extract the needed words and organize them in a structured way. This paper applies natural language processing(NLP) techniques to automatically extract and structure information from soil survey reports regarding soil–environment relationships. The method includes two steps:(1) construction of a knowledge frame and(2) information extraction using either a rule-based method or a statistic-based method for different types of information. For uniformly written text information, the rule-based approach was used to extract information. These types of variables include slope, elevation, accumulated temperature, annual mean temperature, annual precipitation, and frost-free period. For information contained in text written in diverse styles, the statistic-based method was adopted. These types of variables include landform and parent material. The soil species of China soil survey reports were selected as the experimental dataset. Precision(P), recall(R), and F1-measure(F1) were used to evaluate the performances of the method. For the rule-based method, the P values were 1, the R values were above 92%, and the F1 values were above 96% for all the involved variables. For the method based on the conditional random fields(CRFs), the P, R and F1 values for the parent material were, respectively, 84.15, 83.13, and 83.64%; the values for landform were 88.33, 76.81, and 82.17%, respectively. To explore the impact of text types on the performance of the CRFs-based method, CRFs models were trained and validated separately by the descriptive texts of soil types and typical profiles. For parent material, the maximum F1 value for the descriptive text of soil types was 90.7%, while the maximum F1 value for the descriptive text of soil profiles was only 75%. For landform, the maximum F1 value for the descriptive text of soil types was 85.33%, which was similar to that of the descriptive text of soil profiles(i.e., 85.71%). These results suggest that NLP techniques are effective for the extraction and structuration of soil–environment relationship information from a text data source.展开更多
Language plays a vital role in the communication, sharing and transmission of in- formation among human beings. Geographical languages are essential for understanding, investigating, representing and propagating geo-s...Language plays a vital role in the communication, sharing and transmission of in- formation among human beings. Geographical languages are essential for understanding, investigating, representing and propagating geo-spatial information. Geographical languages have developed and evolved gradually with improvements in science, technology and cogni- tive levels. Concerning the theoretical progress from geographical information ontology, epistemology and linguistic theory, this paper firstly puts forward the concept of a GIS lan- guage and discusses its basic characteristics according to changes in the structures, func- tions and characteristics of geographical languages. This GIS language can be regarded as a system of synthetic digital symbols. It is a comprehensive representation of geographical objects, phenomena and their spatial distributions and dynamic processes. This representa- tion helps us generate a universal perception of geographical space using geographical scenarios or symbols with geometry, statuses, processes, spatio-temporal relationships, semantics and attributes. Furthermore, this paper states that the GIS language represents a new generation of geographical language due to its intrinsic characteristics, structures, func- tions and systematic content. Based on the aforementioned theoretical foundation, this paper illustrates the pivotal status and contributions of the GIS language from the perspective of geographical researchers. The language of GIS is a new geographical language designed for the current era, with features including spatio-temporal multi-dimension representation, in- teractive visualization, virtual geographical scenarios, multi-sensor perception and expedient broadcasting via the web. The GIS language is the highest-level geographical language developed to date, integrat- ing semantic definitions, feature extraction, geographical dynamic representation and spa- tio-temporal factors and unifying the computation of geographical phenomena and objects. The GIS language possesses five important characteristics： abstraction, systematicness, strictness, precision and hierarchy. In summary, the GIS language provides a new means for people to recognize, understand and simulate entire geo-environments. Therefore, explora- tion of the GIS language＇s functions in contemporary geographical developments is becoming increasingly important. Similarly, construction of the conceptual model and scientific systems of the GIS language will promote the development of the disciplines of geography and geo- graphical information sciences. Therefore, this paper investigates the prospects of the GIS language from the perspectives of digital technology, geographical norms, geographical modeling and the disciplinary development of geography.展开更多
A scientific delineation of geographical boundaries reflects the cognitive level of scientific abstraction and systematic analysis of the spatial variation of geographical objects and is a basic scientific issue of ge...A scientific delineation of geographical boundaries reflects the cognitive level of scientific abstraction and systematic analysis of the spatial variation of geographical objects and is a basic scientific issue of geography. From the perspective of earth system science,this study first explicates the core issues(e.g., basic concepts, scientific contents, and basic properties) of geographical boundaries. Based on the principles of scientificity and systematicness, we then classify geographical boundaries in terms of intrinsic mechanisms, extrinsic appearance and scientific attributes. Furthermore, this paper analyzes the mathematical connotation and representation methods of geographical boundaries, discusses the characteristics of and differences between traditional and modern methods for geographical boundary delineation. Finally, we present a framework for a “geographical boundary model”with an integration of qualitative, quantitative, and positioning methods. Focusing on geographical boundary(a basic theoretical problem in geography), this study engaged in concept definition and method analysis, with the findings enriching the theory and methodology of geographical information science.展开更多
In Southwestern China,the development of karst landforms and planation surfaces is closely related to local tectonics,fluvial incision,and base level changes,and climate changes.However,researches on when these karst ...In Southwestern China,the development of karst landforms and planation surfaces is closely related to local tectonics,fluvial incision,and base level changes,and climate changes.However,researches on when these karst landforms and planation surfaces formed and how they evolved along drainage development are scarce.Fortunately,horizontal caves with numerous fluvial deposits in high karst mountains can be served as time markers in landform evolution.Here we select large horizontal caves to perform studies of geomorphology,sedimentology,and geochronology.Fieldwork revealed that more than 25 km long horizontal cave passages are perched 1500 m higher than the local base level,but filled with several phases of fluvial sediments and breakdown slabs.The first phase of fluvial gravels and related cave drainage was dated back to 6.4 Ma using cosmogenic nuclide burial dating,and the stalagmite covering the cave collapse was dated by the U-Pb method to be older than 1.56 Ma.These results show that the continuous horizontal cave drainage system and the planation surface were developed before the Late Miocene.The lowering process of the base level as a result of the sharp fluvial incision and water level lowering,along with the regional uplift,led to the abandonment of the horizontal cave and the elevated planation surface at the Late Miocene.After that,the phase of cave collapse,thick fluvial sand,and clay sediments in the recharge of cave areas were deposited at around 1.6 Ma and during the Middle Pleistocene,respectively.Subsequently,speleothems were widely deposited on the collapse and clay sediments during the period from 600 to 90 ka,whereas the deposition of cave fluvial sediments terminated suddenly.The tectonic could control the denudation of surface caprocks and the development of karst conduits before the Late Miocene,whereas the river incision acted as the main driver for the base level lowering and the destruction of the horizontal cave drainage at high altitudes.In addition,the rapid incision and retreat of Silurian gorges finally caused the formation of karst mesas in the Middle Pleistocene.展开更多
Texture analysis methods offer substantial advantages and potential in examining macro-topographic features of dunes.Despite these advantages,comprehensive approaches that integrate digital elevation model(DEM)with qu...Texture analysis methods offer substantial advantages and potential in examining macro-topographic features of dunes.Despite these advantages,comprehensive approaches that integrate digital elevation model(DEM)with quantitative texture features have not been fully developed.This study introduced an automatic classification framework for dunes that combines texture and topographic features and validated it through a typical coastal aeolian landform,namely,dunes in the Namib Desert.A three-stage approach was outlined:(1)segmentation of dune units was conducted using digital terrain analysis;(2)six texture features(angular second moment,contrast,correlation,variance,entropy,and inverse difference moment)were extracted from the gray-level co-occurrence matrix(GLCM)and subsequently quantified;and(3)texture–topographic indices were integrated into the random forest(RF)model for classification.The results show that the RF model fused with texture features can accurately identify dune morphological characteristics;through accuracy evaluation and remote sensing image verification,the overall accuracy reaches 78.0%(kappa coefficient=0.72),outperforming traditional spectral-based methods.In addition,spatial analysis reveals that coastal dunes exhibit complex texture patterns,with texture homogeneity being closely linked to dune-type transitions.Specifically,homogeneous textures correspond to simple and stable forms such as barchans,while heterogeneous textures are associated with complex or composite dunes.The complexity,periodicity,and directionality of texture features are highly consistent with the spatial distribution of dunes.Validation using high-resolution remote sensing imagery(Sentinel-2)further confirms that the method effectively clusters similar dunes and distinguishes different dune types.Additionally,the dune classification results have a good correspondence with changes in near-surface wind regimes.Overall,the findings suggest that texture features derived from DEM can accurately capture the dynamic characteristics of dune morphology,offering a novel approach for automatic dune classification.Compared with traditional methods,the developed approach facilitates large-scale and high-precision dune mapping while reducing the workload of manual interpretation,thus advancing research on aeolian geomorphology.展开更多
In China′s Loess Plateau area, gully head is the most active zone of a drainage system in gully areas. The differentiation of loess gully head follows geospatial patterns and reflects the process of the loess landfor...In China′s Loess Plateau area, gully head is the most active zone of a drainage system in gully areas. The differentiation of loess gully head follows geospatial patterns and reflects the process of the loess landform development and evolution of its drainage system to some extent. In this study, the geomorphic meaning, basic characteristics, morphological structure and the basic types of loess gully heads were systematically analysed. Then, the loess gully head′s conceptual model was established, and an extraction method based on Digital Elevation Model(DEM) for loess gully head features and elements was proposed. Through analysing the achieved statistics of loess gully head features, loess gully heads have apparently similar and different characteristics depending on the different loess landforms where they are found. The loess head characteristics reflect their growth period and evolution tendency to a certain degree, and they indirectly represent evolutionary mechanisms. In addition, the loess gully developmental stages and the evolutionary processes can be deduced by using loess gully head characteristics. This study is of great significance for development and improvement of the theoretical system for describing loess gully landforms.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 represent the development degree of local landforms. The critical stable regions of the Loess Plateau represent the degree of development of loess landforms. Its chief significance is that the per- ception of stable areas can be used to determine the minimal geographical unit.展开更多
Specific Catchment Area （SCA） is defined as the upstream catchment area of a unit contour. As one of the key terrain parameters, it is widely used in the modeling of hydrology, soil erosion and ecological environmen...Specific Catchment Area （SCA） is defined as the upstream catchment area of a unit contour. As one of the key terrain parameters, it is widely used in the modeling of hydrology, soil erosion and ecological environment. However, SCA value changes significantly at different DEM resolutions, which inevitably affect terrain analysis results. SCA can be described as the ratio of Catchment Area （CA） and DEM grid length. In this paper, the scale effect of CA is firstly investigated. With Jiuyuangou Gully, a watershed about 70 km2 in northern Shaanxi Province of China, as the test area, it is found that the impacts of DEM scale on CA are different in spatial distribution. CA value in upslope location becomes bigger with the decrease of the DEM resolution. When the location is close to downstream areas the impact of DEM scale on CA is gradually weakening. The scale effect of CA can be concluded as a mathematic trend of exponential decline. Then, a downscaling model of SCA is put forward by introducing the scale factor and the location factor. The scaling model can realize the conversion of SCA value from a coarse DEM resolution to a finer one at pixel level. Experiment results show that the downscaled SCA was well revised, and consistent with SCA at the target resolution with respect to the statistical indexes, histogram and spatial distribution. With the advantages of no empirical parameters, the scaling model could be considered as a simple and objective model for SCA scaling in a rugged drainage area.展开更多
The automatic recognition of landforms is regarded as one of the most important procedures to classify landforms and deepen the understanding on the morphology of the earth. However, landform types are rather complex ...The automatic recognition of landforms is regarded as one of the most important procedures to classify landforms and deepen the understanding on the morphology of the earth. However, landform types are rather complex and gradual changes often occur in these landforms, thus increasing the difficulty in automatically recognizing and classifying landforms. In this study, small-scale watersheds, which are regarded as natural geomorphological elements, were extracted and selected as basic analysis and recognition units based on the data of SRTM DEM. In addition, datasets integrated with terrain derivatives(e.g., average slope gradient, and elevation range) and texture derivatives(e.g., slope gradient contrast and elevation variance) were constructed to quantify the topographical characteristics of watersheds. Finally, Random Forest(RF) method was employed to automatically select features and classify landforms based on their topographical characteristics. The proposed method was applied and validated in seven case areas in the Northern Shaanxi Loess Plateau for its complex andgradual changed landforms. Experimental results show that the highest recognition accuracy based on the selected derivations is 92.06%. During the recognition procedure, the contributions of terrain derivations were higher than that of texture derivations within selected derivative datasets. Loess terrace and loess mid-mountain obtained the highest accuracy among the seven typical loess landforms. However, the recognition precision of loess hill, loess hill–ridge, and loess sloping ridge is relatively low. The experiment also shows that watershed-based strategy could achieve better results than object-based strategy, and the method of RF could effectively extract and recognize the feature of landforms.展开更多
It has been two decades since virtual geographic environments(VGEs)were initially proposed.While relevant theories and technologies are evolving,data organization models have always been the foundation of VGE developm...It has been two decades since virtual geographic environments(VGEs)were initially proposed.While relevant theories and technologies are evolving,data organization models have always been the foundation of VGE development,and they require further exploration.Based on the comprehensive consideration of the characteristics of VGEs,geographic scene is proposed to organize geographic information and data.We empirically find that geographic scene provides a suitable organization schema to support geo-visualization,geo-simulation,and geo-collaboration.To systematically investigate the concept and method of geographic scene,Geographic Scenario is proposed as the theory on developing geographic scene,and corresponding key issues of the Geographic Scenario are illustrated in this article.Prospects of the proposed method are discussed with the hope of informing future studies of VGEs.展开更多
Rice(Oryza sativa L.) is the most important staple crop of China, and its production is related to both natural condition and human activities. It is fundamental to comprehensively assess the influence of terrain cond...Rice(Oryza sativa L.) is the most important staple crop of China, and its production is related to both natural condition and human activities. It is fundamental to comprehensively assess the influence of terrain conditions on rice production to ensure a steady increase in rice production. Although many studies have focused on the impact of one or several specific factors on crop production, few studies have investigated the direct influence of terrain conditions on rice production. Therefore, we selected Hunan Province, one of the major rice-producing areas in China, which exhibits complex terrain conditions, as our study area. Based on remote sensing data and statistical data, we applied spatial statistical analysis to explore the effects of terrain factors on rice production in terms of the following three aspects: the spatial patterns of paddy fields, the rice production process and the final yield. We found that 1) terrain has a significant impact on the spatial distribution of paddy fields at both the regional scale and the county scale; 2) terrain controls the distribution of temperature, sunlight and soil, and these three environmental factors consequently directly impact rice growth; 3) compared with the patterns of paddy fields and the rice production process, the influences of terrain factors on the rice yield are not as evident, with the exception of elevation; and 4) the spatial distribution of paddy fields mismatched that of production resources due to terrain factors. Our results strongly suggest that managers should scientifically guide farmers to choose suitable varieties and planting systems and allocate rice production resources in the northern plain regions to ensure food security.展开更多
The glacial landforms of the Qinghai-Tibetan Plateau(QTP)provide a unique opportunity to research hemispheric and global environmental changes.In this study,we focus on the glacial history of the palaeo-Daocheng Ice C...The glacial landforms of the Qinghai-Tibetan Plateau(QTP)provide a unique opportunity to research hemispheric and global environmental changes.In this study,we focus on the glacial history of the palaeo-Daocheng Ice Cap(p-DIC)in the southeastern QTP during the last glacial cycle.Based on field investigations,morphostratigraphy,and surface exposure dating of roche moutonnée,polished surface and moraine debris through the terrestrial cosmogenic nuclides(TCN)^10Be and^26Al.We identify glacial deposits of the last deglaciation,with minimum ages of 14.9±1.3-18.7±1.7 ka,the Last Glacial Maximum(LGM)of 24.7±2.2 ka,and the early part of the last glacial period(marine oxygen isotope stage(MIS)3)of 37.1±3.4-45.2±3.9 ka.Our results show that in this region,the extent of the glacial advance during MIS 3 was larger than that during the traditional LGM(MIS 2).These ages are consistent with prior chronologies,and the^10Be age is consistent with the^26Al age for the same sample.Thus,these data provide reliable constraints on climate change in the QTP,during the last glaciation.展开更多
A detailed landslide susceptibility map was produced in the Youfang catchment using logistic regression method with datasets developed for a geographic information system(GIS).Known as one of the most landslide-prone ...A detailed landslide susceptibility map was produced in the Youfang catchment using logistic regression method with datasets developed for a geographic information system(GIS).Known as one of the most landslide-prone areas in China, the Youfang catchment of Longnan mountain region,which lies in the transitional area among QinghaiTibet Plateau, loess Plateau and Sichuan Basin, was selected as a representative case to evaluate the frequency and distribution of landslides.Statistical relationships for landslide susceptibility assessment were developed using landslide and landslide causative factor databases.Logistic regression(LR)was used to create the landslide susceptibility maps based on a series of available data sources: landslide inventory; distance to drainage systems, faults and roads; slope angle and aspect; topographic elevation and topographical wetness index, and land use.The quality of the landslide susceptibility map produced in this paper was validated and the result can be used fordesigning protective and mitigation measures against landslide hazards.The landslide susceptibility map is expected to provide a fundamental tool for landslide hazards assessment and risk management in the Youfang catchment.展开更多
Conventional soil maps contain valuable knowledge on soil–environment relationships.Such knowledge can be extracted for use when updating conventional soil maps with improved environmental data.Existing methods take ...Conventional soil maps contain valuable knowledge on soil–environment relationships.Such knowledge can be extracted for use when updating conventional soil maps with improved environmental data.Existing methods take all polygons of the same map unit on a map as a whole to extract the soil–environment relationship.Such approach ignores the difference in the environmental conditions represented by individual soil polygons of the same map unit.This paper proposes a method of mining soil–environment relationships from individual soil polygons to update conventional soil maps.The proposed method consists of three major steps.Firstly,the soil–environment relationships represented by each individual polygon on a conventional soil map are extracted in the form of frequency distribution curves for the involved environmental covariates.Secondly,for each environmental covariate,these frequency distribution curves from individual polygons of the same soil map unit are synthesized to form the overall soil–environment relationship for that soil map unit across the mapped area.And lastly,the extracted soil–environment relationships are applied to updating the conventional soil map with new,improved environmental data by adopting a soil land inference model(SoLIM)framework.This study applied the proposed method to updating a conventional soil map of the Raffelson watershed in La Crosse County,Wisconsin,United States.The result from the proposed method was compared with that from the previous method of taking all polygons within the same soil map unit on a map as a whole.Evaluation results with independent soil samples showed that the proposed method exhibited better performance and produced higher accuracy.展开更多
Terrain texture analysis is an important method of digital terrain analysis in quantitative geomorphological research and in the exploration of the spatial heterogeneity and autocorrelation of terrain features. Howeve...Terrain texture analysis is an important method of digital terrain analysis in quantitative geomorphological research and in the exploration of the spatial heterogeneity and autocorrelation of terrain features. However, a major issue often neglected in previous studies is the calculation unit of the terrain texture, that is, the stability analysis unit. As the test size increases, the derived terrain textures become increasingly similar so that their differences can be ignored. The test size of terrain texture is defined as the stability analysis unit. This study randomly selected 48 areas within the Loess Plateau in northern Shaanxi in China as the study sites and used the gray level co-occurrence matrix to calculate the terrain texture. The stability analysis unit of the terrain texture was then extracted, and its spatial distribution pattern in the Loess Plateau was studiedusing spatial interpolation method. Four terrain texture metrics, i.e., homogeneity, energy, correlation, and contrast, were extracted on the basis of the stability analysis unit, and the spatial variation patterns of these parameters were studied. Results showed that the spatial distribution pattern and the terrain texture metrics reflected a trend of high–low–high from north to south, which correlated with the spatial distribution of the landforms at the Loess Plateau. In addition, the terrain texture measures was significantly correlated with the terrain factors of gully density and slope, and this relationship showed that terrain texture measures based on the stability analysis unit could reflect the basic characteristics of terrain morphology. The stability analysis unit provided a reasonable analytical scale for terrain texture analysis and could be used as a measure of the regional topography to accurately describe basic terrain characteristics.展开更多
Shoulder lines are the most important landform demarcations for geographical analysis,soil erosion modeling and land use planning in the Loess Plateau area of China.This paper proposes an automatic,effective and accur...Shoulder lines are the most important landform demarcations for geographical analysis,soil erosion modeling and land use planning in the Loess Plateau area of China.This paper proposes an automatic,effective and accurate method of determining loess shoulder line from DEMs by integrating a hydrological D8 algorithm and a snake model.The watershed boundary line is adopted as the initial contour which evolves to identify the exact position of loess shoulder-line by the guidance of an external force of snake model from DEMs.Experiments show that the method overcomes the difficulties in both threshold selection for edge detection and the disconnecting issues in former extraction approaches.The accuracy evaluation of shoulder-line maps from the two test sites of the loess plateau area show obvious improvements in the extraction.The average contour matching distance of the new method is 12.0 m on 5 m resolution DEM,and shows improvement in the accuracy and continuity.The comparisons of accuracy evaluations of the two test sites show that the snake model method performs better in the loess plain area than in the area with high gully density.展开更多
Water motion in estuarine waters is the result of the action of various dynamic factors. Firstly, based on the hydro- dynamic characteristics in estuarine waters, neglecting the nonlinear effects of various flow hydro...Water motion in estuarine waters is the result of the action of various dynamic factors. Firstly, based on the hydro- dynamic characteristics in estuarine waters, neglecting the nonlinear effects of various flow hydrodynamic factors, the logarithm velocity profile of tidal current and the cubic velocity profile of Hansen and Rattray （1965） made for linear super- position at a sense of first order, a new model for velocity profile in estuarine waters is established. Then, by introducing the least square method combination of enumeration, the velocity profile data of wind-driven current measured in the laboratory and that observed at the North and the South Branches of the Yangtze Estuary are verified and compared with other formulas, all with satisfactory results. The results show that the new model not only considers the influences of various dynamic factors, such as tide, wind force, run-off and density pressure with high accuracy, but also provides reasonable boundary conditions on the bottom for hydrodynamics numerical simulation in estuarine waters. Thereby, the accuracy and credibility of numerical computation and prediction of water flow are improved. The research is theoretically important for the estuarine hydrodynamics.展开更多
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 surfac...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.展开更多
Receptor models are a useful tool for identifying sources of polycyclic aromatic hydrocarbons(PAHs)in multiple environmental media.In this study,three different receptor models(including the principal component analys...Receptor models are a useful tool for identifying sources of polycyclic aromatic hydrocarbons(PAHs)in multiple environmental media.In this study,three different receptor models(including the principal component analysis-multiple linear regression(PCA-MLR),positive matrix factorization(PMF),and Unmix models)were used to apportion the sources of 16 priority PAHs in a sediment core of Lake Dagze Co.TheΣPAHs(sum of all 16 measured PAHs)concentrations ranged from 51.89 to 132.82 ng/g with an average of 80.39 ng/g.TheΣPAHs were dominated by 2-3 ring PAHs,accounting for 80.12%on average,thereby indicating that they mainly originated from biomass and coal combustion and/or from long-range atmospheric transportation.The three models produced consistent source apportionment results.The greatest contributor toΣPAHs was biomass combustion,followed by coal combustion,vehicle emissions,and petrogenic sources.Moreover,the temporal variation of the common sources was well-correlated among models.The multi-method comparison and evaluation results showed that all three models were useful tools for source apportionment of PAHs,with the PMF model providing better results than the PCA-MLR and Unmix models.The temporal trends of factor contributions were verified by PAHs with different ring numbers.Significant correlations were found between the simulated concentrations of each source factor and the PAHs with different ring numbers(P<0.01),except for the petrogenic source identified by the Unmix model(P>0.05).This study can provide useful information for further investigation of source apportionment of PAHs in the sediment cores.展开更多
The Fenglin and Fengcong landform units are considered to be an important representation for defining the degree of development of Karst landforms. However, these terrain features have been proven difficult to delinea...The Fenglin and Fengcong landform units are considered to be an important representation for defining the degree of development of Karst landforms. However, these terrain features have been proven difficult to delineate and extract automatically because of their complex morphology. In this paper, a new method for identifying the Fenglin and Fengcong landform units is proposed. This method consists of two steps:(1) terrain openness calculation and(2) toe line extraction. The proposed method is applied and validated in the Karst case area of Guilin by using ASTER GDEM with one arc-second resolution. The openness of both the positive and negative terrain and a threshold were used to extract toe lines for segmenting depressions and pinnacles in Fenglin and Fengcong landforms. A comparison between the extracted Fenglin and Fengcong landform units and their real units from high resolution images wascarried out to evaluate the capability of the proposed method. Results show the proposed method can effectively extract the Fenglin and Fengcong landform units, and has an overall accuracy of 93.28%. The proposed method is simple and easy to implement and is expected to play an important role in the automatic extraction of similar landform units in the Karst area.展开更多
基金supported by the National Natural Science Foundation of China (41431177 and 41601413)the National Basic Research Program of China (2015CB954102)+1 种基金the Natural Science Research Program of Jiangsu Province, China (BK20150975 and 14KJA170001)the Outstanding Innovation Team in Colleges and Universities in Jiangsu Province, China
文摘In addition to soil samples, conventional soil maps, and experienced soil surveyors, text about soils(e.g., soil survey reports) is an important potential data source for extracting soil–environment relationships. Considering that the words describing soil–environment relationships are often mixed with unrelated words, the first step is to extract the needed words and organize them in a structured way. This paper applies natural language processing(NLP) techniques to automatically extract and structure information from soil survey reports regarding soil–environment relationships. The method includes two steps:(1) construction of a knowledge frame and(2) information extraction using either a rule-based method or a statistic-based method for different types of information. For uniformly written text information, the rule-based approach was used to extract information. These types of variables include slope, elevation, accumulated temperature, annual mean temperature, annual precipitation, and frost-free period. For information contained in text written in diverse styles, the statistic-based method was adopted. These types of variables include landform and parent material. The soil species of China soil survey reports were selected as the experimental dataset. Precision(P), recall(R), and F1-measure(F1) were used to evaluate the performances of the method. For the rule-based method, the P values were 1, the R values were above 92%, and the F1 values were above 96% for all the involved variables. For the method based on the conditional random fields(CRFs), the P, R and F1 values for the parent material were, respectively, 84.15, 83.13, and 83.64%; the values for landform were 88.33, 76.81, and 82.17%, respectively. To explore the impact of text types on the performance of the CRFs-based method, CRFs models were trained and validated separately by the descriptive texts of soil types and typical profiles. For parent material, the maximum F1 value for the descriptive text of soil types was 90.7%, while the maximum F1 value for the descriptive text of soil profiles was only 75%. For landform, the maximum F1 value for the descriptive text of soil types was 85.33%, which was similar to that of the descriptive text of soil profiles(i.e., 85.71%). These results suggest that NLP techniques are effective for the extraction and structuration of soil–environment relationship information from a text data source.
基金Foundation： National Natural Science Foundation of China, No.41201398, No.40930531 Opening Foundation of State Key Laboratory of Resources and Environment Information System of China, No.2010KF0002SA Key Con- structive Disciplines Projects of Human Geography in Hunan Province
文摘Language plays a vital role in the communication, sharing and transmission of in- formation among human beings. Geographical languages are essential for understanding, investigating, representing and propagating geo-spatial information. Geographical languages have developed and evolved gradually with improvements in science, technology and cogni- tive levels. Concerning the theoretical progress from geographical information ontology, epistemology and linguistic theory, this paper firstly puts forward the concept of a GIS lan- guage and discusses its basic characteristics according to changes in the structures, func- tions and characteristics of geographical languages. This GIS language can be regarded as a system of synthetic digital symbols. It is a comprehensive representation of geographical objects, phenomena and their spatial distributions and dynamic processes. This representa- tion helps us generate a universal perception of geographical space using geographical scenarios or symbols with geometry, statuses, processes, spatio-temporal relationships, semantics and attributes. Furthermore, this paper states that the GIS language represents a new generation of geographical language due to its intrinsic characteristics, structures, func- tions and systematic content. Based on the aforementioned theoretical foundation, this paper illustrates the pivotal status and contributions of the GIS language from the perspective of geographical researchers. The language of GIS is a new geographical language designed for the current era, with features including spatio-temporal multi-dimension representation, in- teractive visualization, virtual geographical scenarios, multi-sensor perception and expedient broadcasting via the web. The GIS language is the highest-level geographical language developed to date, integrat- ing semantic definitions, feature extraction, geographical dynamic representation and spa- tio-temporal factors and unifying the computation of geographical phenomena and objects. The GIS language possesses five important characteristics： abstraction, systematicness, strictness, precision and hierarchy. In summary, the GIS language provides a new means for people to recognize, understand and simulate entire geo-environments. Therefore, explora- tion of the GIS language＇s functions in contemporary geographical developments is becoming increasingly important. Similarly, construction of the conceptual model and scientific systems of the GIS language will promote the development of the disciplines of geography and geo- graphical information sciences. Therefore, this paper investigates the prospects of the GIS language from the perspectives of digital technology, geographical norms, geographical modeling and the disciplinary development of geography.
基金National Natural Science Foundation of China,No.41930102。
文摘A scientific delineation of geographical boundaries reflects the cognitive level of scientific abstraction and systematic analysis of the spatial variation of geographical objects and is a basic scientific issue of geography. From the perspective of earth system science,this study first explicates the core issues(e.g., basic concepts, scientific contents, and basic properties) of geographical boundaries. Based on the principles of scientificity and systematicness, we then classify geographical boundaries in terms of intrinsic mechanisms, extrinsic appearance and scientific attributes. Furthermore, this paper analyzes the mathematical connotation and representation methods of geographical boundaries, discusses the characteristics of and differences between traditional and modern methods for geographical boundary delineation. Finally, we present a framework for a “geographical boundary model”with an integration of qualitative, quantitative, and positioning methods. Focusing on geographical boundary(a basic theoretical problem in geography), this study engaged in concept definition and method analysis, with the findings enriching the theory and methodology of geographical information science.
基金supported by the foundation of the Institute of Karst Geology,Chinese Academy of Geological Sciences(Nos.201317,2014005,2014034,2016011)National Natural Science Foundation of China(No.41270226)。
文摘In Southwestern China,the development of karst landforms and planation surfaces is closely related to local tectonics,fluvial incision,and base level changes,and climate changes.However,researches on when these karst landforms and planation surfaces formed and how they evolved along drainage development are scarce.Fortunately,horizontal caves with numerous fluvial deposits in high karst mountains can be served as time markers in landform evolution.Here we select large horizontal caves to perform studies of geomorphology,sedimentology,and geochronology.Fieldwork revealed that more than 25 km long horizontal cave passages are perched 1500 m higher than the local base level,but filled with several phases of fluvial sediments and breakdown slabs.The first phase of fluvial gravels and related cave drainage was dated back to 6.4 Ma using cosmogenic nuclide burial dating,and the stalagmite covering the cave collapse was dated by the U-Pb method to be older than 1.56 Ma.These results show that the continuous horizontal cave drainage system and the planation surface were developed before the Late Miocene.The lowering process of the base level as a result of the sharp fluvial incision and water level lowering,along with the regional uplift,led to the abandonment of the horizontal cave and the elevated planation surface at the Late Miocene.After that,the phase of cave collapse,thick fluvial sand,and clay sediments in the recharge of cave areas were deposited at around 1.6 Ma and during the Middle Pleistocene,respectively.Subsequently,speleothems were widely deposited on the collapse and clay sediments during the period from 600 to 90 ka,whereas the deposition of cave fluvial sediments terminated suddenly.The tectonic could control the denudation of surface caprocks and the development of karst conduits before the Late Miocene,whereas the river incision acted as the main driver for the base level lowering and the destruction of the horizontal cave drainage at high altitudes.In addition,the rapid incision and retreat of Silurian gorges finally caused the formation of karst mesas in the Middle Pleistocene.
基金supported by the National Natural Science Foundation of China(42271421).
文摘Texture analysis methods offer substantial advantages and potential in examining macro-topographic features of dunes.Despite these advantages,comprehensive approaches that integrate digital elevation model(DEM)with quantitative texture features have not been fully developed.This study introduced an automatic classification framework for dunes that combines texture and topographic features and validated it through a typical coastal aeolian landform,namely,dunes in the Namib Desert.A three-stage approach was outlined:(1)segmentation of dune units was conducted using digital terrain analysis;(2)six texture features(angular second moment,contrast,correlation,variance,entropy,and inverse difference moment)were extracted from the gray-level co-occurrence matrix(GLCM)and subsequently quantified;and(3)texture–topographic indices were integrated into the random forest(RF)model for classification.The results show that the RF model fused with texture features can accurately identify dune morphological characteristics;through accuracy evaluation and remote sensing image verification,the overall accuracy reaches 78.0%(kappa coefficient=0.72),outperforming traditional spectral-based methods.In addition,spatial analysis reveals that coastal dunes exhibit complex texture patterns,with texture homogeneity being closely linked to dune-type transitions.Specifically,homogeneous textures correspond to simple and stable forms such as barchans,while heterogeneous textures are associated with complex or composite dunes.The complexity,periodicity,and directionality of texture features are highly consistent with the spatial distribution of dunes.Validation using high-resolution remote sensing imagery(Sentinel-2)further confirms that the method effectively clusters similar dunes and distinguishes different dune types.Additionally,the dune classification results have a good correspondence with changes in near-surface wind regimes.Overall,the findings suggest that texture features derived from DEM can accurately capture the dynamic characteristics of dune morphology,offering a novel approach for automatic dune classification.Compared with traditional methods,the developed approach facilitates large-scale and high-precision dune mapping while reducing the workload of manual interpretation,thus advancing research on aeolian geomorphology.
基金Under the auspices of National Youth Science Foundation of China(No.41001294)Key Project of National Natural Science Foundation of China(No.40930531)Research Fund of State Key Laboratory Resources and Environment Information System(No.2010KF0002SA)
文摘In China′s Loess Plateau area, gully head is the most active zone of a drainage system in gully areas. The differentiation of loess gully head follows geospatial patterns and reflects the process of the loess landform development and evolution of its drainage system to some extent. In this study, the geomorphic meaning, basic characteristics, morphological structure and the basic types of loess gully heads were systematically analysed. Then, the loess gully head′s conceptual model was established, and an extraction method based on Digital Elevation Model(DEM) for loess gully head features and elements was proposed. Through analysing the achieved statistics of loess gully head features, loess gully heads have apparently similar and different characteristics depending on the different loess landforms where they are found. The loess head characteristics reflect their growth period and evolution tendency to a certain degree, and they indirectly represent evolutionary mechanisms. In addition, the loess gully developmental stages and the evolutionary processes can be deduced by using loess gully head characteristics. This study is of great significance for development and improvement of the theoretical system for describing loess gully landforms.
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 represent the development degree of local landforms. The critical stable regions of the Loess Plateau represent the degree of development of loess landforms. Its chief significance is that the per- ception of stable areas can be used to determine the minimal geographical unit.
基金Key Project of National Natural Science Foundation of China No.40930531 National Youth Science Foun-dation of China No.40901185 Specialized Research Fund for the Doctoral Program of Higher Education No.20093207120008
文摘Specific Catchment Area （SCA） is defined as the upstream catchment area of a unit contour. As one of the key terrain parameters, it is widely used in the modeling of hydrology, soil erosion and ecological environment. However, SCA value changes significantly at different DEM resolutions, which inevitably affect terrain analysis results. SCA can be described as the ratio of Catchment Area （CA） and DEM grid length. In this paper, the scale effect of CA is firstly investigated. With Jiuyuangou Gully, a watershed about 70 km2 in northern Shaanxi Province of China, as the test area, it is found that the impacts of DEM scale on CA are different in spatial distribution. CA value in upslope location becomes bigger with the decrease of the DEM resolution. When the location is close to downstream areas the impact of DEM scale on CA is gradually weakening. The scale effect of CA can be concluded as a mathematic trend of exponential decline. Then, a downscaling model of SCA is put forward by introducing the scale factor and the location factor. The scaling model can realize the conversion of SCA value from a coarse DEM resolution to a finer one at pixel level. Experiment results show that the downscaled SCA was well revised, and consistent with SCA at the target resolution with respect to the statistical indexes, histogram and spatial distribution. With the advantages of no empirical parameters, the scaling model could be considered as a simple and objective model for SCA scaling in a rugged drainage area.
基金supported by the National Natural Science Foundation of China (Grant NOs. 41601411, 41571398, 41671389)the Priority Academic Program Development of Jiangsu Higher Education Institutions-PAPD (Grant No.164320H101)
文摘The automatic recognition of landforms is regarded as one of the most important procedures to classify landforms and deepen the understanding on the morphology of the earth. However, landform types are rather complex and gradual changes often occur in these landforms, thus increasing the difficulty in automatically recognizing and classifying landforms. In this study, small-scale watersheds, which are regarded as natural geomorphological elements, were extracted and selected as basic analysis and recognition units based on the data of SRTM DEM. In addition, datasets integrated with terrain derivatives(e.g., average slope gradient, and elevation range) and texture derivatives(e.g., slope gradient contrast and elevation variance) were constructed to quantify the topographical characteristics of watersheds. Finally, Random Forest(RF) method was employed to automatically select features and classify landforms based on their topographical characteristics. The proposed method was applied and validated in seven case areas in the Northern Shaanxi Loess Plateau for its complex andgradual changed landforms. Experimental results show that the highest recognition accuracy based on the selected derivations is 92.06%. During the recognition procedure, the contributions of terrain derivations were higher than that of texture derivations within selected derivative datasets. Loess terrace and loess mid-mountain obtained the highest accuracy among the seven typical loess landforms. However, the recognition precision of loess hill, loess hill–ridge, and loess sloping ridge is relatively low. The experiment also shows that watershed-based strategy could achieve better results than object-based strategy, and the method of RF could effectively extract and recognize the feature of landforms.
基金supported by the Key Fund of National Natural Science Foundation of China[grant number 41631175]The National Key Research and Development Program of China[grant number 2017YFB0503500]+1 种基金National Natural Science Foundation of China[grant number 41622108]Priority Academic Program Development of Jiangsu Higher Education Institutions[grant number 164320H116]。
文摘It has been two decades since virtual geographic environments(VGEs)were initially proposed.While relevant theories and technologies are evolving,data organization models have always been the foundation of VGE development,and they require further exploration.Based on the comprehensive consideration of the characteristics of VGEs,geographic scene is proposed to organize geographic information and data.We empirically find that geographic scene provides a suitable organization schema to support geo-visualization,geo-simulation,and geo-collaboration.To systematically investigate the concept and method of geographic scene,Geographic Scenario is proposed as the theory on developing geographic scene,and corresponding key issues of the Geographic Scenario are illustrated in this article.Prospects of the proposed method are discussed with the hope of informing future studies of VGEs.
基金Creative Research Groups of National Natural Science Foundation of China,No.41621061National Natural Science Foundation of China,No.41571493,No.31561143003
文摘Rice(Oryza sativa L.) is the most important staple crop of China, and its production is related to both natural condition and human activities. It is fundamental to comprehensively assess the influence of terrain conditions on rice production to ensure a steady increase in rice production. Although many studies have focused on the impact of one or several specific factors on crop production, few studies have investigated the direct influence of terrain conditions on rice production. Therefore, we selected Hunan Province, one of the major rice-producing areas in China, which exhibits complex terrain conditions, as our study area. Based on remote sensing data and statistical data, we applied spatial statistical analysis to explore the effects of terrain factors on rice production in terms of the following three aspects: the spatial patterns of paddy fields, the rice production process and the final yield. We found that 1) terrain has a significant impact on the spatial distribution of paddy fields at both the regional scale and the county scale; 2) terrain controls the distribution of temperature, sunlight and soil, and these three environmental factors consequently directly impact rice growth; 3) compared with the patterns of paddy fields and the rice production process, the influences of terrain factors on the rice yield are not as evident, with the exception of elevation; and 4) the spatial distribution of paddy fields mismatched that of production resources due to terrain factors. Our results strongly suggest that managers should scientifically guide farmers to choose suitable varieties and planting systems and allocate rice production resources in the northern plain regions to ensure food security.
基金supported by the National Natural Science Foundation of China(Grant No.40572097)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)(Grant No.164320H116)by the Yulong Mountain tourism development and management committee special project
文摘The glacial landforms of the Qinghai-Tibetan Plateau(QTP)provide a unique opportunity to research hemispheric and global environmental changes.In this study,we focus on the glacial history of the palaeo-Daocheng Ice Cap(p-DIC)in the southeastern QTP during the last glacial cycle.Based on field investigations,morphostratigraphy,and surface exposure dating of roche moutonnée,polished surface and moraine debris through the terrestrial cosmogenic nuclides(TCN)^10Be and^26Al.We identify glacial deposits of the last deglaciation,with minimum ages of 14.9±1.3-18.7±1.7 ka,the Last Glacial Maximum(LGM)of 24.7±2.2 ka,and the early part of the last glacial period(marine oxygen isotope stage(MIS)3)of 37.1±3.4-45.2±3.9 ka.Our results show that in this region,the extent of the glacial advance during MIS 3 was larger than that during the traditional LGM(MIS 2).These ages are consistent with prior chronologies,and the^10Be age is consistent with the^26Al age for the same sample.Thus,these data provide reliable constraints on climate change in the QTP,during the last glaciation.
基金supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions(164320H101)the Opening Fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection of Chengdu University of Technology,China(SKLGP2012K012)+4 种基金the Opening Fund of Key Laboratory for Geo-hazards in Loess area(GLA2014005)the National Natural Science Foundation of China(No.40801212 and No.41201424)the 973 National Basic Research Program(Nos.2013CB733203,2013CB733204)the 863 National High-Tech Rand D Program(No.2012AA121302)the FP6 project"Mountain Risks"of the European Commission(No.MRTNCT-2006-035798)
文摘A detailed landslide susceptibility map was produced in the Youfang catchment using logistic regression method with datasets developed for a geographic information system(GIS).Known as one of the most landslide-prone areas in China, the Youfang catchment of Longnan mountain region,which lies in the transitional area among QinghaiTibet Plateau, loess Plateau and Sichuan Basin, was selected as a representative case to evaluate the frequency and distribution of landslides.Statistical relationships for landslide susceptibility assessment were developed using landslide and landslide causative factor databases.Logistic regression(LR)was used to create the landslide susceptibility maps based on a series of available data sources: landslide inventory; distance to drainage systems, faults and roads; slope angle and aspect; topographic elevation and topographical wetness index, and land use.The quality of the landslide susceptibility map produced in this paper was validated and the result can be used fordesigning protective and mitigation measures against landslide hazards.The landslide susceptibility map is expected to provide a fundamental tool for landslide hazards assessment and risk management in the Youfang catchment.
基金supported by the National Natural Science Foundation of China (41431177 and 41422109)the Innovation Project of State Key Laboratory of Resources and Environmental Information System of China (O88RA20CYA)the Outstanding Innovation Team in Colleges and Universities in Jiangsu Province, China
文摘Conventional soil maps contain valuable knowledge on soil–environment relationships.Such knowledge can be extracted for use when updating conventional soil maps with improved environmental data.Existing methods take all polygons of the same map unit on a map as a whole to extract the soil–environment relationship.Such approach ignores the difference in the environmental conditions represented by individual soil polygons of the same map unit.This paper proposes a method of mining soil–environment relationships from individual soil polygons to update conventional soil maps.The proposed method consists of three major steps.Firstly,the soil–environment relationships represented by each individual polygon on a conventional soil map are extracted in the form of frequency distribution curves for the involved environmental covariates.Secondly,for each environmental covariate,these frequency distribution curves from individual polygons of the same soil map unit are synthesized to form the overall soil–environment relationship for that soil map unit across the mapped area.And lastly,the extracted soil–environment relationships are applied to updating the conventional soil map with new,improved environmental data by adopting a soil land inference model(SoLIM)framework.This study applied the proposed method to updating a conventional soil map of the Raffelson watershed in La Crosse County,Wisconsin,United States.The result from the proposed method was compared with that from the previous method of taking all polygons within the same soil map unit on a map as a whole.Evaluation results with independent soil samples showed that the proposed method exhibited better performance and produced higher accuracy.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41471316, 41571383, 41671389)the Priority Academic Program Development of Jiangsu Higher Education Institutions-PAPD (Grant No. 164320H101)the Key Project of Natural Science Research of Anhui Provincial Department of Education (Grant No. KJ2015A171)
文摘Terrain texture analysis is an important method of digital terrain analysis in quantitative geomorphological research and in the exploration of the spatial heterogeneity and autocorrelation of terrain features. However, a major issue often neglected in previous studies is the calculation unit of the terrain texture, that is, the stability analysis unit. As the test size increases, the derived terrain textures become increasingly similar so that their differences can be ignored. The test size of terrain texture is defined as the stability analysis unit. This study randomly selected 48 areas within the Loess Plateau in northern Shaanxi in China as the study sites and used the gray level co-occurrence matrix to calculate the terrain texture. The stability analysis unit of the terrain texture was then extracted, and its spatial distribution pattern in the Loess Plateau was studiedusing spatial interpolation method. Four terrain texture metrics, i.e., homogeneity, energy, correlation, and contrast, were extracted on the basis of the stability analysis unit, and the spatial variation patterns of these parameters were studied. Results showed that the spatial distribution pattern and the terrain texture metrics reflected a trend of high–low–high from north to south, which correlated with the spatial distribution of the landforms at the Loess Plateau. In addition, the terrain texture measures was significantly correlated with the terrain factors of gully density and slope, and this relationship showed that terrain texture measures based on the stability analysis unit could reflect the basic characteristics of terrain morphology. The stability analysis unit provided a reasonable analytical scale for terrain texture analysis and could be used as a measure of the regional topography to accurately describe basic terrain characteristics.
基金supported by the National Natural Science Foundation of China (Grant Nos. 40930531, 41001294, 41301422)the Open Project Foundation of State Key Laboratory of Resources and Environmental Information System in China (Grant No. 2010KF0002SA)
文摘Shoulder lines are the most important landform demarcations for geographical analysis,soil erosion modeling and land use planning in the Loess Plateau area of China.This paper proposes an automatic,effective and accurate method of determining loess shoulder line from DEMs by integrating a hydrological D8 algorithm and a snake model.The watershed boundary line is adopted as the initial contour which evolves to identify the exact position of loess shoulder-line by the guidance of an external force of snake model from DEMs.Experiments show that the method overcomes the difficulties in both threshold selection for edge detection and the disconnecting issues in former extraction approaches.The accuracy evaluation of shoulder-line maps from the two test sites of the loess plateau area show obvious improvements in the extraction.The average contour matching distance of the new method is 12.0 m on 5 m resolution DEM,and shows improvement in the accuracy and continuity.The comparisons of accuracy evaluations of the two test sites show that the snake model method performs better in the loess plain area than in the area with high gully density.
基金supported by the National Natural Science Foundation of China(Grant No.50339010)the Public Welfare Projects of the Ministry of Water Resources(Grant No.200701026)
文摘Water motion in estuarine waters is the result of the action of various dynamic factors. Firstly, based on the hydro- dynamic characteristics in estuarine waters, neglecting the nonlinear effects of various flow hydrodynamic factors, the logarithm velocity profile of tidal current and the cubic velocity profile of Hansen and Rattray （1965） made for linear super- position at a sense of first order, a new model for velocity profile in estuarine waters is established. Then, by introducing the least square method combination of enumeration, the velocity profile data of wind-driven current measured in the laboratory and that observed at the North and the South Branches of the Yangtze Estuary are verified and compared with other formulas, all with satisfactory results. The results show that the new model not only considers the influences of various dynamic factors, such as tide, wind force, run-off and density pressure with high accuracy, but also provides reasonable boundary conditions on the bottom for hydrodynamics numerical simulation in estuarine waters. Thereby, the accuracy and credibility of numerical computation and prediction of water flow are improved. The research is theoretically important for the estuarine hydrodynamics.
基金Under the auspices of National Natural Science Foundation of China (No.40930531,41171320,41001301)
文摘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.
基金supported by the National Natural Science Foundation of China(Nos.41773097,41971286)the Postgraduate Research Innovation project of Jiangsu Province(No.KYCX21_1330)。
文摘Receptor models are a useful tool for identifying sources of polycyclic aromatic hydrocarbons(PAHs)in multiple environmental media.In this study,three different receptor models(including the principal component analysis-multiple linear regression(PCA-MLR),positive matrix factorization(PMF),and Unmix models)were used to apportion the sources of 16 priority PAHs in a sediment core of Lake Dagze Co.TheΣPAHs(sum of all 16 measured PAHs)concentrations ranged from 51.89 to 132.82 ng/g with an average of 80.39 ng/g.TheΣPAHs were dominated by 2-3 ring PAHs,accounting for 80.12%on average,thereby indicating that they mainly originated from biomass and coal combustion and/or from long-range atmospheric transportation.The three models produced consistent source apportionment results.The greatest contributor toΣPAHs was biomass combustion,followed by coal combustion,vehicle emissions,and petrogenic sources.Moreover,the temporal variation of the common sources was well-correlated among models.The multi-method comparison and evaluation results showed that all three models were useful tools for source apportionment of PAHs,with the PMF model providing better results than the PCA-MLR and Unmix models.The temporal trends of factor contributions were verified by PAHs with different ring numbers.Significant correlations were found between the simulated concentrations of each source factor and the PAHs with different ring numbers(P<0.01),except for the petrogenic source identified by the Unmix model(P>0.05).This study can provide useful information for further investigation of source apportionment of PAHs in the sediment cores.
基金supported by the National Natural Science Foundation of China (NO. 41601411, 41671389, 41571398, 41701449) Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University (Grant No. 17S02) A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions-PAPD (Grant No. 164320H101)
文摘The Fenglin and Fengcong landform units are considered to be an important representation for defining the degree of development of Karst landforms. However, these terrain features have been proven difficult to delineate and extract automatically because of their complex morphology. In this paper, a new method for identifying the Fenglin and Fengcong landform units is proposed. This method consists of two steps:(1) terrain openness calculation and(2) toe line extraction. The proposed method is applied and validated in the Karst case area of Guilin by using ASTER GDEM with one arc-second resolution. The openness of both the positive and negative terrain and a threshold were used to extract toe lines for segmenting depressions and pinnacles in Fenglin and Fengcong landforms. A comparison between the extracted Fenglin and Fengcong landform units and their real units from high resolution images wascarried out to evaluate the capability of the proposed method. Results show the proposed method can effectively extract the Fenglin and Fengcong landform units, and has an overall accuracy of 93.28%. The proposed method is simple and easy to implement and is expected to play an important role in the automatic extraction of similar landform units in the Karst area.
