GIS应用模型分类体系与复杂性评价

本文主要讨论了G IS应用模型概念;分析了G IS应用模型分类方法,建立了G IS应用模型分类体系;给出了G IS应用模型复杂性描述方法,在此基础上,建立了基于统计方法的应用模型复杂性评价方法,分别定义了应用模型复杂性量化级别、评价指标及权;最后采用本文提出的定量统计方法,对小流域地貌演化模型的复杂性进行了评价。     

国外城市交通系统的空间研究进展

城市交通空间研究历史悠久,最早追朔到19世纪初,整体上经过了萌芽探索（19世纪初至19世纪末）、深化发展（20世纪初至50年代）、快速发展（20世纪60年代至80年代）和丰富全面（20世纪90年代以来）四个阶段：研究领域主要集中于交通—城市空间耦合、城市交通空间通达性、空间句法及形态、空间复杂性等方面,其中交通—城市空间耦合研究历史久远,贯穿始末,空间通达性兴起于20世纪60年代,空间句法集中于20世纪70-80年代,空间复杂性则起步较晚,兴盛于21世纪初;整体上,国外城市交通空间复杂性研究薄弱,集成复杂系统科学理论／方法,结合GIS地计算的城市交通空间复杂性规律研究势必成为未来研究的重心和中心。     

Sketch-based Identification of Bench and Terrace Slope Breaks in the Laramie Basin, Wyoming

This study presents a semi‐automated approach to support the identification of fluvial landform slope breaks in the Laramie Basin, southeastern Wyoming. The landforms in question form the edges of terraces and benches and tend to be subtle and varied depending on where they appear in the landscape. Because of this variation combined with DEM error, conventional raster filtering methods were unable to readily identify the benches with any consistency. In an effort to automate the collection of benches, a two stage, sketch‐based algorithm was designed to detect bench edges on a semi‐automated basis and was integrated into a commercial GIS environment for testing and execution. The approach of tailoring an algorithm to detect a particular feature proved viable and, in fact, more consistent in many cases than heads‐up digitizing. However, feature complexity appears to be a significant driver in the accuracy of the algorithmic approach with the unlikely finding that more complex features are more accurately identified than less complex features. This research demonstrates that user cognition, DEM resolution, algorithm functionality and landform characteristics are thus all important and interrelated factors requiring consideration when implementing approaches to topographic feature identification.     

复杂度、关联度与城市技术演化路径——基于北京、上海、深圳的对比分析

演化经济地理强调与本地的技术关联对技术演化的影响,在建设科技创新中心的过程中,向复杂技术的升级需要充分考虑本地技术结构及演化特点。论文以北京、上海和深圳3个国际科技创新中心建设城市为例,将复杂性和关联性纳入研究框架,比较分析技术关联和复杂性对城市技术演化的影响。研究发现,北京、上海和深圳的技术结构、技术关联度、复杂性和演化路径存在明显的差异。上海的技术关联度较高,而复杂度偏低;深圳的技术关联度最低,技术复杂度最高;北京居中。从演化趋势看,北京经历了明显的向复杂技术演化的过程;深圳的整体技术复杂度上升幅度最大,但在2006年以后出现向低复杂度技术多元化发展的趋势;上海的技术复杂度上升幅度最小。计量分析表明,与本地技术关联越强的技术越有利于成为3个城市下一阶段的优势技术,但复杂度高的技术更容易成为北京下一阶段的优势技术,对上海和深圳的技术演化没有显著影响。未来国际科技创新中心建设需要充分考虑本地技术基础和演化特征,并制定针对性的技术发展策略。     

Geomorphic connectivity and its application for understanding landscape complexities: a focus on the hydro-geomorphic systems of India

Geomorphic processes operate at multiple spatio-temporal scales and different levels of hierarchy. It is therefore necessary to understand the linkages of landscapes across various scales and levels to gain insights into their interactions and feedbacks. Connectivity is an emergent property of the hydro-geomorphic systems, and it is gradually evolving into a unifying concept in geomorphology. The connectivity approach has the potential to be applied extensively to diverse hydro-geomorphic systems of India to understand their complexity as well as for designing effective management practices for river systems and wetlands, optimizing water resources for agriculture, and monitoring and restoration of habitats. Studies on connectivity, particularly in geomorphic context, have been growing steadily in India, albeit at a much slower pace compared to the global trends. This article undertakes a brief overview of the global developments particularly in terms of providing some clarity among the different types of geomorphic connectivity and their inter-relationships and feedbacks. We then take stock of the connectivity research in India in recent years as applied in different hydrogeomorphic systems across the country. We utilize a number of Indian case studies to illustrate the important developments and applications of connectivity concepts, and also present future perspective of this important field with special relevance to India. © 2020 John Wiley & Sons, Ltd.     

How does network structure and complexity in river systems affect population abundance and persistence?

Models of habitat connectivity, and how network structure and connectivity affects resident populations, are increasingly being developed for terrestrial habitat networks. Rivers, unlike many terrestrial habitat networks, follow a rigid hierarchical branching structure to form dendritic networks. It has been hypothesised that this unique structure must have implications for population processes. We developed a theoretical model to relate local-scale habitat quality and connectivity to landscape-scale population dynamics of mobile organisms (e.g. fish, aquatic invertebrates). River networks were modelled as directed graphs, with nodes being habitat patches, and edges the connections between them. Using population simulation analyses, we investigated the effects of network structure on population abundance and persistence. Network structural complexity affected landscape-scale population abundance, but the apparent effect depended upon how structure was quantified. There were no noticeable effects of dendritic network structure on population persistence. Previous research on the effects of habitat network structure on population persistence has used metapopulation patch occupancy models, which do not directly consider population dynamics. Our results show that spatially-explicit population modelling is possible, and that it provides information beyond that possible with patch occupancy models (e.g. population abundance). More importantly, it calls into question whether metapopulation models provide an adequate representation of population dynamics in dendritic habitat networks.     

Propagating error in land-cover-change analyses: impact of temporal dependence under increased thematic complexity

We examined the impact of temporal dependence between patterns of error in classified time-series imagery through a simulation modeling approach. This research extended the land-cover-change simulation model we previously developed to investigate: (1) the assumption of temporal independence between patterns of error in classified time-series imagery; and (2) the interaction of patterns of change and patterns of error in a post-classification change analysis. In this research, the thematic complexity of the classified land-cover maps was increased by increasing the number of simulated land-cover classes. Simulating maps with increased categorical resolution permitted the incorporation of: (1) higher-order, more complex spatial and temporal interactions between land-cover classes; and (2) patterns of error that better reproduce the complex error interactions that often occur in time-series classified imagery. The overall modeling framework was divided into two primary components: (1) generation of a map representing true change; and (2) generation of a suite of change maps that had been perturbed by specific patterns of error. All component maps in the model were produced using simulated annealing, which enabled us to create a series of map realizations with user-defined spatial and temporal patterns. Comparing the true map of change to the error-perturbed maps of change using accuracy assessment statistics showed that increasing the temporal dependence between classification errors did not improve the accuracy of resulting maps of change when the categorical scale of the land-cover classified maps was increased. The increased structural complexity within the time series of maps effectively inhibited the impact of temporal dependence. However, results demonstrated that there are interactions between patterns of error and patterns of change in a post-classification change analysis. These interactions played a major role in determining the accuracy associated with the maps of change.     

Wavelet analysis of the hydrological time series of Dalai Lake, Inner Mongolia, China

An important new development in hydrological data analysis in the last decade is the application of wavelet analysis. Here, wavelet theory is used to study the complexity and multi-scale periodicity of the hydrological time series of the Dalai Lake Basin in Inner Mongolia. Two large rivers, the Kelulun and the Wurxun, are the main inflows to Dalai Lake, which is currently shrinking. The annual and monthly flows of the Kelulun River are shown to vary more than those of the Wurxun River, and the monthly flows of the two rivers vary much more than their annual flows. Db5 wavelets are shown to be more suitable for annual flow calculations, whereas Db4 wavelets are more suitable for monthly flow calculations. Multi-scale wavelet analysis of the annual and monthly flows of the Kelulun and Wurxun rivers shows that the variation of the two rivers is similar and has a 25-year cycle, 12 years of wet and 12 years of drought periods, and our results show that both rivers are expected to transition into a wet period beginning in 2012. Therefore, the Dalai Lake Basin, which has been in a drought period since 2000, is expected to gradually transit into a wet period from 2012 onward.