Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evalua...Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evaluation and hazard control in the real world. Analyzing the related scale issues is thus urgent for a better understanding of erosion variations as well as reducing such erosion. In this review article, water erosion dynamics across three spatial scales including plot, watershed, and regional scales were selected and discussed. For the study purposes and objectives, the advantages and disadvantages of these scales all demonstrate clear spatial-scale dependence. Plot scale studies are primarily focused on abundant data collection and mechanism discrimination of erosion generation, while watershed scale studies provide valuable information for watershed management and hazard control as well as the development of quantitatively distributed models. Regional studies concentrate more on large-scale erosion assessment, and serve policymakers and stakeholders in achieving the basis for regulatory policy for comprehensive land uses. The results of this study show that the driving forces and mechanisms of water erosion variations among the scales are quite different. As a result, several major aspects contributing to variations in water erosion across the scales are stressed: differences in the methodologies across various scales, different sink-source roles on water erosion processes, and diverse climatic zones and morphological regions. This variability becomes more complex in the context of accelerated global change. The changing climatic factors and earth surface features are considered the fourth key reason responsible for the increased variability of water erosion across spatial scales.展开更多
An image trust root is a special type of soft trust root for trusted computing. However,image trust root generation is difficult,as it needs a corresponding stable logic feature generation model and algorithm for dyna...An image trust root is a special type of soft trust root for trusted computing. However,image trust root generation is difficult,as it needs a corresponding stable logic feature generation model and algorithm for dynamical and sustained authentication. This paper proposes a basic function of constructing new scale-spaces with deep detecting ability and high stability for image features aimed at image root generation. According to the heat distribution and spreading principle of various kinds of infinitesimal heat sources in the space medium,a multi-embed nonlinear diffusion equation that corresponds to the multi-embed nonlinear scale-space is proposed,a HARRIS-HESSIAN scale-space evaluation operator that aims at the structure acceleration characteristics of a local region and can make use of image pixels' relative spreading movement principle was constructed,then a single-parameter global symmetric proportion(SPGSP) operator was also constructed. An authentication test with 3000 to 5000 cloud entities shows the new scale-space can work well and is stable,when the whole cloud has 5%-50% behavior with un-trusted entities. Consequently,it can be used as the corresponding stable logic feature generation model and algorithm for all kinds of images,and logic relationships among image features for trust roots.展开更多
Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from i...Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from images, and the description of spatial features on maps.However, little achievements have been made for it by far.In this paper, spatial similarity relation was put forward with the introduction of automated map generalization in the construction of multi-scale map databases;then the definition of spatial similarity relations was presented based on set theory, the concept of spatial similarity degree was given, and the characteristics of spatial similarity were discussed in detail, in-cluding reflexivity, symmetry, non-transitivity, self-similarity in multi-scale spaces, and scale-dependence.Finally a classification system for spatial similarity relations in multi-scale map spaces was addressed.This research may be useful to automated map generalization, spatial similarity retrieval and spatial reasoning.展开更多
Aims Darwin’s naturalization hypothesis proposes that successfully established alien species are less closely related to native species due to differences in their ecological niches.Studies have provided support both...Aims Darwin’s naturalization hypothesis proposes that successfully established alien species are less closely related to native species due to differences in their ecological niches.Studies have provided support both for and against this hypothesis.One reason for this is the tendency for phylogenetic clustering between aliens and natives at broad spatial scales with overdispersion at fine scales.However,little is known about how the phylogenetic relatedness of alien species alters the phylogenetic structure of the communities they invade,and at which spatial scales effects may manifest.Here,we examine if invaded understorey plant communities,i.e.containing both native and alien taxa,are phylogenetically clustered or overdispersed,how relatedness changes with spatial scale and how aliens affect phylogenetic patterns in understorey communities.Methods Field surveys were conducted in dry forest understorey communities in south-east Australia at five spatial scales(1,20,500,1500 and 4500 m2).Standardized effect sizes of two metrics were used to quantify phylogenetic relatedness between communities and their alien and native subcommunities,and to examine how phylogenetic patterns change with spatial scale:(i)mean pairwise distance and(ii)mean nearest taxon distance(MNTD).Important Findings Aliens were closely related to each other,and this relatedness tended to increase with scale.Native species and the full community exhibited either no clear pattern of relatedness with increasing spatial scale or were no different from random.At intermediate spatial scales(20-500 m2),the whole community tended towards random whereas the natives were strongly overdispersed and the alien subcommunity strongly clustered.This suggests that invasion by closely related aliens shifts community phylogenetic structure from overdispersed towards random.Aliens and natives were distantly related across spatial scales,supporting Darwin’s naturalization hypothesis,but only when phylogenetic distance was quantified as MNTD.Phylogenetic dissimilarity between aliens and natives increased with spatial scale,counter to expected patterns.Our findings suggest that the strong phylogenetic clustering of aliens is driven by human-mediated introductions involving closely related taxa that can establish and spread successfully.Unexpected scale-dependent patterns of phylogenetic relatedness may result from stochastic processes such as fire and dispersal events and suggest that competition and habitat filtering do not exclusively dominate phylogenetic relationships at fine and coarse spatial scales,respectively.Distinguishing between metrics that focus on different evolutionary depths is important,as different metrics can exhibit different scale-dependent patterns.展开更多
Recently correlation filter based trackers have attracted considerable attention for their high computational efficiency. However, they cannot handle occlusion and scale variation well enough. This paper aims at preve...Recently correlation filter based trackers have attracted considerable attention for their high computational efficiency. However, they cannot handle occlusion and scale variation well enough. This paper aims at preventing the tracker from failure in these two situations by integrating the depth information into a correlation filter based tracker. By using RGB-D data, we construct a depth context model to reveal the spatial correlation between the target and its surrounding regions. Furthermore, we adopt a region growing method to make our tracker robust to occlusion and scale variation. Additional optimizations such as a model updating scheme are applied to improve the performance for longer video sequences. Both qualitative and quantitative evaluations on challenging benchmark image sequences demonstrate that the proposed tracker performs favourably against state-of-the-art algorithms.展开更多
基金Under the auspices of National Natural Science Foundation of China (No. 40925003, 40930528, 40801041)
文摘Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evaluation and hazard control in the real world. Analyzing the related scale issues is thus urgent for a better understanding of erosion variations as well as reducing such erosion. In this review article, water erosion dynamics across three spatial scales including plot, watershed, and regional scales were selected and discussed. For the study purposes and objectives, the advantages and disadvantages of these scales all demonstrate clear spatial-scale dependence. Plot scale studies are primarily focused on abundant data collection and mechanism discrimination of erosion generation, while watershed scale studies provide valuable information for watershed management and hazard control as well as the development of quantitatively distributed models. Regional studies concentrate more on large-scale erosion assessment, and serve policymakers and stakeholders in achieving the basis for regulatory policy for comprehensive land uses. The results of this study show that the driving forces and mechanisms of water erosion variations among the scales are quite different. As a result, several major aspects contributing to variations in water erosion across the scales are stressed: differences in the methodologies across various scales, different sink-source roles on water erosion processes, and diverse climatic zones and morphological regions. This variability becomes more complex in the context of accelerated global change. The changing climatic factors and earth surface features are considered the fourth key reason responsible for the increased variability of water erosion across spatial scales.
基金The national natural science foundation (61672442,61503316,61273290,61373147)Xiamen Scientific Plan Project (2014S0048,3502Z20123037)+1 种基金Fujian Scientific Plan Project (2013HZ00041)Fujian provincial education office A-class project(JA13238)
文摘An image trust root is a special type of soft trust root for trusted computing. However,image trust root generation is difficult,as it needs a corresponding stable logic feature generation model and algorithm for dynamical and sustained authentication. This paper proposes a basic function of constructing new scale-spaces with deep detecting ability and high stability for image features aimed at image root generation. According to the heat distribution and spreading principle of various kinds of infinitesimal heat sources in the space medium,a multi-embed nonlinear diffusion equation that corresponds to the multi-embed nonlinear scale-space is proposed,a HARRIS-HESSIAN scale-space evaluation operator that aims at the structure acceleration characteristics of a local region and can make use of image pixels' relative spreading movement principle was constructed,then a single-parameter global symmetric proportion(SPGSP) operator was also constructed. An authentication test with 3000 to 5000 cloud entities shows the new scale-space can work well and is stable,when the whole cloud has 5%-50% behavior with un-trusted entities. Consequently,it can be used as the corresponding stable logic feature generation model and algorithm for all kinds of images,and logic relationships among image features for trust roots.
文摘Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from images, and the description of spatial features on maps.However, little achievements have been made for it by far.In this paper, spatial similarity relation was put forward with the introduction of automated map generalization in the construction of multi-scale map databases;then the definition of spatial similarity relations was presented based on set theory, the concept of spatial similarity degree was given, and the characteristics of spatial similarity were discussed in detail, in-cluding reflexivity, symmetry, non-transitivity, self-similarity in multi-scale spaces, and scale-dependence.Finally a classification system for spatial similarity relations in multi-scale map spaces was addressed.This research may be useful to automated map generalization, spatial similarity retrieval and spatial reasoning.
基金supported by the Australian Research Council Discovery Project(DP150103017)and an Australian Government Research Training Program(RTP)Scholarship.
文摘Aims Darwin’s naturalization hypothesis proposes that successfully established alien species are less closely related to native species due to differences in their ecological niches.Studies have provided support both for and against this hypothesis.One reason for this is the tendency for phylogenetic clustering between aliens and natives at broad spatial scales with overdispersion at fine scales.However,little is known about how the phylogenetic relatedness of alien species alters the phylogenetic structure of the communities they invade,and at which spatial scales effects may manifest.Here,we examine if invaded understorey plant communities,i.e.containing both native and alien taxa,are phylogenetically clustered or overdispersed,how relatedness changes with spatial scale and how aliens affect phylogenetic patterns in understorey communities.Methods Field surveys were conducted in dry forest understorey communities in south-east Australia at five spatial scales(1,20,500,1500 and 4500 m2).Standardized effect sizes of two metrics were used to quantify phylogenetic relatedness between communities and their alien and native subcommunities,and to examine how phylogenetic patterns change with spatial scale:(i)mean pairwise distance and(ii)mean nearest taxon distance(MNTD).Important Findings Aliens were closely related to each other,and this relatedness tended to increase with scale.Native species and the full community exhibited either no clear pattern of relatedness with increasing spatial scale or were no different from random.At intermediate spatial scales(20-500 m2),the whole community tended towards random whereas the natives were strongly overdispersed and the alien subcommunity strongly clustered.This suggests that invasion by closely related aliens shifts community phylogenetic structure from overdispersed towards random.Aliens and natives were distantly related across spatial scales,supporting Darwin’s naturalization hypothesis,but only when phylogenetic distance was quantified as MNTD.Phylogenetic dissimilarity between aliens and natives increased with spatial scale,counter to expected patterns.Our findings suggest that the strong phylogenetic clustering of aliens is driven by human-mediated introductions involving closely related taxa that can establish and spread successfully.Unexpected scale-dependent patterns of phylogenetic relatedness may result from stochastic processes such as fire and dispersal events and suggest that competition and habitat filtering do not exclusively dominate phylogenetic relationships at fine and coarse spatial scales,respectively.Distinguishing between metrics that focus on different evolutionary depths is important,as different metrics can exhibit different scale-dependent patterns.
基金Project supported by the National Natural Science Foundation of China(Nos.61502509,61402504,and 61272145)the National High-Tech R&D Program(863)of China(No.2012AA012706)the Research Fund for the Doctoral Program of Higher Education of China(No.21024307130004)
文摘Recently correlation filter based trackers have attracted considerable attention for their high computational efficiency. However, they cannot handle occlusion and scale variation well enough. This paper aims at preventing the tracker from failure in these two situations by integrating the depth information into a correlation filter based tracker. By using RGB-D data, we construct a depth context model to reveal the spatial correlation between the target and its surrounding regions. Furthermore, we adopt a region growing method to make our tracker robust to occlusion and scale variation. Additional optimizations such as a model updating scheme are applied to improve the performance for longer video sequences. Both qualitative and quantitative evaluations on challenging benchmark image sequences demonstrate that the proposed tracker performs favourably against state-of-the-art algorithms.
