A Triangular Form‐based Multiple Flow Algorithm to Estimate Overland Flow Distribution and Accumulation on a Digital Elevation Model

In this study, we present a newly developed method for the estimation of surface flow paths on a digital elevation model (DEM). The objective is to use a form‐based algorithm, analyzing flow over single cells by dividing them into eight triangular facets and to estimate the surface flow paths on a raster DEM. For each cell on a gridded DEM, the triangular form‐based multiple flow algorithm (TFM) was used to distribute flow to one or more of the eight neighbor cells, which determined the flow paths over the DEM. Because each of the eight facets covering a cell has a constant slope and aspect, the estimations of – for example – flow direction and divergence/convergence are more intuitive and less complicated than many traditional raster‐based solutions. Experiments were undertaken by estimating the specific catchment area (SCA) over a number of mathematical surfaces, as well as on a real‐world DEM. Comparisons were made between the derived SCA by the TFM algorithm with eight other algorithms reported in the literature. The results show that the TFM algorithm produced the closest outcomes to the theoretical values of the SCA compared with other algorithms, derived more consistent outcomes, and was less influenced by surface shapes. The real‐world DEM test shows that the TFM was capable of modeling flow distribution without noticeable ‘artefacts’, and its ability to track flow paths makes it an appropriate platform for dynamic surface flow simulation.     

A Hybrid Link‐Node Approach for Finding Shortest Paths in Road Networks with Turn Restrictions

Turn restrictions, such as ‘no left turn’ or ‘no U‐turn’, are commonly encountered in real road networks. These turn restrictions must be explicitly considered in the shortest path problem and ignoring them may lead to infeasible paths. In the present study, a hybrid link‐node Dijkstra's (HLND) algorithm is proposed to exactly solve the shortest path problem in road networks with turn restrictions. A new hybrid link–node labelling approach is devised by using a link–based labelling strategy at restricted nodes with turn restrictions, and a node‐based labelling strategy at unrestricted nodes without turn restrictions. Computational results for several real road networks show that the proposed HLND algorithm obtains the same optimal results as the link‐based Dijkstra's algorithm, while having a similar computational performance to the classical node‐based Dijkstra's algorithm.     

基于水流扩展思想的网络空间Voronoi图生成

Voronoi图是地理空间设施分布特征提取的重要几何模型,基于不同的空间距离概念可建立不同的Voronoi图。本研究顾及城市网络空间中设施点的服务功能及相互联系发生于网络路径距离而非传统的欧式距离的事实,针对网络空间Voronoi图模型,建立一种网络空间Voronoi图生成的栅格扩展算法。首先对图结构的边目标剖分为细小的线性单元,称作网络空间的栅格化,引入水流扩展思想,将事件点发生源视为“水源”,以栅格单元长度为扩展步长,让水流方向沿着网络上的可通行路径同时向外蔓延,直至与其他水流相遇或者到达边的尽头。该算法可方便地加入网络图结构中的多种约束,如街道边的单向行驶、结点的限制性连接等实际空间限制条件。通过大规模实际数据的“数字城市”POI点服务范围的试验表明该算法的效率高。     

Finding outdoor boundaries for 3D space‐based navigation

Outdoor navigation is widely used in daily life, but faces various issues related to the fidelity of outdoor navigation networks. For instance, agents (pedestrians) are often guided via unrealistic detours around places without clear paths (e.g., squares) or if there are vertical constraints such as overpasses/bridges. This is partly explained by the fact that the main sources of navigation networks in current outdoor navigation are two‐dimensional road/street networks. Utilizing a three‐dimensional space‐based navigation model, compatible with some indoor approaches, is a popular way to address the above‐mentioned issues. A 3D space‐based navigation model is generated by treating 3D spaces as nodes and the shared faces as edges. Inputs of this model are enclosed 3D spaces (volumes). However, outdoor spaces are generally open and unbounded. This article puts forward an approach to enclose outdoor spaces and mimic the indoor environments to derive a network based on connectivity and accessibility of spaces. The approach uses 2.5D maps and consists of three major steps: object footprint determination, footprint classification and space creation. Two use cases demonstrate the proposed approach. Enclosing outdoor spaces opens a new research direction toward providing seamless indoor/outdoor navigation for a range of agents.     

Optimal Routefinding with Unlimited Possible Directions of Movement

Finding optimal paths through raster databases is limited by the very nature of the raster data itself. This limitation restricts the possible directions of movement through the database from the infinite possibilities found in the real world to a finite number of possibilities defined by the cell‐to‐cell movement that characterizes raster databases. A Triangulated Irregular Network (TIN)‐based alternative optimization model that allows unlimited possible directions of movement is presented. While not without its own limitations, this new approach offers a viable alternative to raster‐based optimal routefinding.     

Possibilities of using raster data in client‐side web maps

Companies and individual developers have recently put serious effort into improving web mapping libraries. A significant front in this development is hardware‐accelerated vector graphics. Owing to those efforts, and the continuously evolving World Wide Web, users can visualize large vector layers, and even animate them. On the other hand, this rapid development cannot be observed with raster data. There are some data abstraction libraries for reading raster files, although web mapping libraries do not use them to offer raster capabilities. Since there are no mature raster management pipelines on the web, this study explores two inherently different techniques for handling raster data. One of them uses the traditional, texture‐based method. The other is a hybrid technique rendering raster layers as vectors, overcoming some limitations of the raster model. While the traditional technique gives a smooth user experience, the hybrid method shows promising results for rendering hexagonal coverages.     

基于栅格数据的最优路径算法分析与设计

最优路径分析是GIS中基本空间分析之一,迄今为止,国内外出现不少关于最短路径/最优路径算法的研究,但其数据模型主要以矢量数据模型或网络模型为主,而建立在栅格数据模型上的最优路径算法的相关研究较少。基于栅格的最优路径算法是一些专业应用模型的基础,如道路通达度模型、城市引力模型、洪水演进过程模型等,其算法设计非常重要。本文在前人的研究基础上,提出一种用于计算栅格最优路径的算法,对其计算过程进行了详细的分析与描述,并根据实验结果总结了其优点和缺点。     

面向目标的栅格矢量一体化三维数据模型

首先对现有的三维空间数据模型进行了讨论 ,分析了栅格、矢量和混合数据模型的特点 ,提出了一种面向目标的栅格矢量一体化数据模型。该模型将栅格数据以矢量方式进行组织 ,从而同时具有矢量和栅格数据模型的优点 ,也克服了目前普遍应用的混合模型所存在的缺点。还提出了一种三维空间的三级栅格划分和行次序编码方法。该方法存储空间小 ,便于快速索引和计算。最后 ,给出了具体的数据结构     

Semantic enrichment of octree structured point clouds for multi‐story 3D pathfinding

3D indoor navigation in multi‐story buildings and under changing environments is still difficult to perform. 3D models of buildings are commonly not available or outdated. 3D point clouds turned out to be a very practical way to capture 3D interior spaces and provide a notion of an empty space. Therefore, pathfinding in point clouds is rapidly emerging. However, processing of raw point clouds can be very expensive, as these are semantically poor and unstructured data. In this article we present an innovative octree‐based approach for processing of 3D indoor point clouds for the purpose of multi‐story pathfinding. We semantically identify the construction elements, which are of importance for the indoor navigation of humans (i.e., floors, walls, stairs, and obstacles), and use these to delineate the available navigable space. To illustrate the usability of this approach, we applied it to real‐world data sets and computed paths considering user constraints. The structuring of the point cloud into an octree approximation improves the point cloud processing and provides a structure for the empty space of the point cloud. It is also helpful to compute paths sufficiently accurate in their consideration of the spatial complexity. The entire process is automatic and able to deal with a large number of multi‐story indoor environments.     

Fast Image‐Space Silhouette Extraction for Non‐Photorealistic Landscape Rendering

Landscape illustration, a core visualization technique for field geologists and geomorphologists, employs the parsimonious use of linework to represent surface structure in a straightforward and intuitive manner. Under the rubric of non‐photorealistic rendering (NPR), automated procedures in this vein render silhouettes and creases to represent, respectively, view‐dependent and view‐independent landscape features. This article presents two algorithms and implementations for rendering silhouettes from adaptive tessellations of point‐normal (PN) triangles at speeds approaching those suitable for animation. PN triangles use cubic polynomial models to provide a surface that appears smooth at any required resolution. The first algorithm, drawing on standard silhouette detection techniques in surface meshes, builds object space facet adjacencies and image space pixel adjacencies in the graphics pipeline following adaptive tessellation. The second makes exclusive use of image space analysis without referencing the underlying scene world geometry. Other than initial pre‐processing operations, recent advances in the OpenGL API allow implementations for both algorithms to be hosted entirely on the graphics processing unit (GPU), eliminating slowdowns through data transfer across the system memory bus. We show that both algorithms provide viable paths to real‐time animation of pen and ink style landscape illustrations but that the second demonstrates superior performance over the first.     

A Space‐Time Raster GIS Data Model for Spatiotemporal Analysis of Vegetation Responses to a Freeze Event

Many past space‐time GIS data models viewed the world mainly from a spatial perspective. They attached a time stamp to each state of an entity or the entire area of study. This approach is less efficient for certain spatio‐temporal analyses that focus on how locations change over time, which require researchers to view each location from a temporal perspective. In this article, we present a data model to organize multi‐temporal remote sensing datasets and track their changes at the individual pixel level. This data model can also integrate raster datasets from heterogeneous sources under a unified framework. The proposed data model consists of several object classes under a hierarchical structure. Each object class is associated with specific properties and behaviors to facilitate efficient spatio‐temporal analyses. We apply this data model to a case study of analyzing the impact of the 2007 freeze in Knoxville, Tennessee. The characteristics of different vegetation clusters before, during, and after the 2007 freeze event are compared. Our findings indicate that the majority of the study area is impacted by this freeze event, and different vegetation types show different response patterns to this freeze.     

面向路径优化的变分辨率栅格成本表面模型建模方法

成本表面模型是在连续空间中进行路径优化的基础。目前,在连续空间中进行路径优化多是基于单分辨率成本表面模型的。但在使用该模型解决诸如输电、调水、公路和铁路、输油输气等路径优化问题时,存在一些缺点,例如数据冗余、计算成本高、易受地物“边缘效应”影响等。针对这些问题,本文提出了一种面向路径优化的GIS变分辨率栅格成本表面模型,并详细阐述了这种数据模型的设计思想和建模方法。实验结果证明,该模型能有效的对地物密集度和地形复杂度进行建模,解决单分辨率模型遇到的问题。将该模型与传统的单分辨率成本表面模型的计算结果进行对比分析,表明本文建立的模型在多种环境下均能选出合理的路径,且计算效率得到明显提高。     

Assessing Raster GIS Approximation for Euclidean Shortest Path Routing

Identifying a route that avoids obstacles in continuous space is important for infrastructure alignment, robotic travel, and virtual object path planning, among others, because movement through space is not restricted to a predefined road or other network. Vector and raster GIS (geographic information system) solution approaches have been developed to find good/efficient routes. On the vector side, recent solution approaches exploit spatial knowledge and utilize GIS functionality, offering significant computational advantages in finding an optimal solution to this path routing problem. Raster‐based shortest path techniques are widely applied in route planning for wayfinding, corridor alignment, robotics and video gaming to derive an obstacle avoiding path, but represent an approximation approach for solving this problem. This research compares vector and raster approaches for identifying obstacle‐avoiding shortest paths/routes. Empirical assessment is carried out for a number of planning applications, highlighting representational issues, computational requirements and resulting path efficiency.     

Building Agent‐Based Walking Models by Machine‐Learning on Diverse Databases of Space‐Time Trajectory Samples

We introduce a novel scheme for automatically deriving synthetic walking (locomotion) and movement (steering and avoidance) behavior in simulation from simple trajectory samples. We use a combination of observed and recorded real‐world movement trajectory samples in conjunction with synthetic, agent‐generated, movement as inputs to a machine‐learning scheme. This scheme produces movement behavior for non‐sampled scenarios in simulation, for applications that can differ widely from the original collection settings. It does this by benchmarking a simulated pedestrian's relative behavioral geography, local physical environment, and neighboring agent‐pedestrians; using spatial analysis, spatial data access, classification, and clustering. The scheme then weights, trains, and tunes likely synthetic movement behavior, per‐agent, per‐location, per‐time‐step, and per‐scenario. To prove its usefulness, we demonstrate the task of generating synthetic, non‐sampled, agent‐based pedestrian movement in simulated urban environments, where the scheme proves to be a useful substitute for traditional transition‐driven methods for determining agent behavior. The potential broader applications of the scheme are numerous and include the design and delivery of location‐based services, evaluation of architectures for mobile communications technologies, what‐if experimentation in agent‐based models with hypotheses that are informed or translated from data, and the construction of algorithms for extracting and annotating space‐time paths in massive data‐sets.     

Error assessment of grid‐based terrain shading algorithms for solar radiation modeling over complex terrain

In mountainous regions, solar radiation exhibits a strong spatial heterogeneity due to terrain shading effects. Terrain shading algorithms based on digital elevation models can be categorized into two types: area‐based and point‐specific. In this article, we evaluated two shading algorithms using designed mathematic surfaces. Theoretical shading effects over four Gauss synthetic surfaces were calculated and used to evaluate the terrain shading algorithms. We evaluated the area‐based terrain shading algorithm, Hillshade tool of ArcGIS, and the point‐specific shading algorithm from Solar Analyst (SA) in ArcGIS. Both algorithms showed shading overestimation, and Hillshade showed more accuracy with a mean absolute error (MAE) of 1.20%, as compared to the MAE of 1.66% of SA. The MAE of Hillshade increases exponentially as the spatial extent of the study area increases because the solar position for all locations on the surface is the same in Hillshade. Consequently, we suggest that the surface should be divided into more tiles in Hillshade when the discrepancy in the latitude of the whole surface is greater than 4°. Skyshed, which represents the horizon angle distribution in SA, is error‐prone over more complex terrain because horizon angle interpolation is problematic for such areas. We also propose a new terrain shading algorithm, with solar positions calculated using local latitude for each cell and the horizon angle calculated for every specific time interval, but without projections. The new model performs better than Hillshade and SA with an MAE of 0.55%.     

Integrated compression of vehicle spatio‐temporal trajectories under the road stroke network constraint

With fast growth of all kinds of trajectory datasets, how to effectively manage the trajectory data of moving objects has received a lot of attention. This study proposes a spatio‐temporal data integrated compression method of vehicle trajectories based on stroke paths coding compression under the road stroke network constraint. The road stroke network is first constructed according to the principle of continuous coherence in Gestalt psychology, and then two types of Huffman tree—a road strokes Huffman tree and a stroke paths Huffman tree—are built, based respectively on the importance function of road strokes and vehicle visiting frequency of stroke paths. After the vehicle trajectories are map matched to the spatial paths in the road network, the Huffman codes of the road strokes and stroke paths are used to compress the trajectory spatial paths. An opening window algorithm is used to simplify the trajectory temporal data depicted on a time–distance polyline by setting the maximum allowable speed difference as the threshold. Through analysis of the relative spatio‐temporal relationship between the preceding and latter feature tracking points, the spatio‐temporal data of the feature tracking points are all converted to binary codes together, accordingly achieving integrated compression of trajectory spatio‐temporal data. A series of comparative experiments between the proposed method and representative state‐of‐the‐art methods are carried out on a real massive taxi trajectory dataset from five aspects, and the experimental results indicate that our method has the highest compression ratio. Meanwhile, this method also has favorable performance in other aspects: compression and decompression time overhead, storage space overhead, and historical dataset training time overhead.     

Enhancing data privacy with semantic trajectories: A raster‐based framework for GPS stop/move management

Tracking facilities on smartphones generate enormous amounts of GPS trajectories, which provide new opportunities to study movement patterns and improve transportation planning. Converting GPS trajectories into semantically meaningful trips is attracting increasing research effort with respect to the development of algorithms, frameworks, and software tools. There are, however, few works focused on designing new semantic enrichment functionalities taking privacy into account. This article presents a raster‐based framework which not only detects significant stop locations, segments GPS records into stop/move structures, and brings semantic insights to trips, but also provides possibilities to anonymize users’ movements and sensitive stay/move locations into raster cells/regions so that a multi‐level data sharing structure is achieved for a variety of data sharing purposes.     

Finding least-cost paths across a continuous raster surface with discrete vector networks

The problem of finding the least-cost path from a source point to a destination point can be dealt with by routing across a continuous surface or routing along a discrete network. The solutions within these two contexts are linked to the use of a raster- or a vector-based least-cost path algorithm. This study presents a technique which integrates raster- and vector-based least-cost path algorithms for determining the least-cost path across a continuous raster surface with discrete vector networks. The technique incorporates ancillary vector data sets that are required to examine the travel cost at each link, connections between nodes, and the representation of intersecting links in the discrete vector network into raster-based least-cost path analysis. The integrated technique presented here is applicable to all-terrain vehicle navigation where a continuous raster surface and discrete vector networks need to be considered simultaneously in order to find least-cost paths. This paper describes the concept behind, and details of, the integrated technique. Applications of the technique with synthetic and real-world data sets are also presented. They provide proof that the technique is effective in finding least-cost paths across a continuous raster surface with discrete vector networks.     

RS与GIS一体化数据结构的研究

详细阐述了RS与GIS一体化的概念 ,通过对RS与GIS一体化方面的研究与分析 ,进一步明确RS与GIS一体化对空间数据存储结构的要求 ,着重探讨了几种典型的用于RS与GIS一体化的数据结构 ,针对现有数据结构存在的问题与不足 ,提出了一种具有普遍适用价值的基于语义网络的空间数据存储结构 ,并给出一个应用实例     

Terra Populus’ architecture for integrated big geospatial services

Big geospatial data is an emerging sub‐area of geographic information science, big data, and cyberinfrastructure. Big geospatial data poses two unique challenges. First, raster and vector data structures and analyses have developed on largely separate paths for the last 20 years. This is creating an impediment to geospatial researchers seeking to utilize big data platforms that do not promote heterogeneous data types. Second, big spatial data repositories have yet to be integrated with big data computation platforms in ways that allow researchers to spatio‐temporally analyze big geospatial datasets. IPUMS‐Terra, a National Science Foundation cyberInfrastructure project, addresses these challenges by providing a unified framework of integrated geospatial services which access, analyze, and transform big heterogeneous spatio‐temporal data. As IPUMS‐Terra's data volume grows, we seek to integrate geospatial platforms that will scale geospatial analyses and address current bottlenecks within our system. However, our work shows that there are still unresolved challenges for big geospatial analysis. The most pertinent is that there is a lack of a unified framework for conducting scalable integrated vector and raster data analysis. We conducted a comparative analysis between PostgreSQL with PostGIS and SciDB and concluded that SciDB is the superior platform for scalable raster zonal analyses.