Multidimensional-unified topological relations computation: a hierarchical geometric algebra-based approach

This article presents a geometric algebra-based model for topological relation computation. This computational model is composed of three major components: the Grassmann structure preserving hierarchical multivector-tree representation (MVTree), multidimensional unified operators for intersection relation computation, and the judgement rules for assembling the intersections into topological relations. With this model, the intersection relations between the different dimensional objects (nodes at different levels) are computed using the Tree Meet operator. The meet operation between two arbitrary objects is accomplished by transforming the computation into the meet product between each pair of MVTree nodes, which produces a series of intersection relations in the form of MVTree. This intersection tree is then processed through a set of judgement rules to determine the topological relations between two objects in the hierarchy. Case studies of topological relations between two triangles in 3D space are employed to illustrate the model. The results show that with the new model, the topological relations can be computed in a simple way without referring to dimension. This dimensionless way of computing topological relations from geographic data is significant given the increased dimensionality of geographic information in the digital era.     

Adjustment computation of HASM: a high-accuracy and high-speed method

We developed a method for high-accuracy surface modeling (HASM) in terms of the fundamental theorem of surfaces, which has theoretically found a solution for error problems. However, the computing speed of HASM was too slow to be widely applied in practice. Thus, adjustment computation of HASM (HASM-AC) is developed in this article. For comparatively testing HASM-AC accuracy, a mathematical surface is first selected so that the true value is able to be predetermined to avoid uncontrollable data errors. The numerical test indicates that HASM-AC has the highest accuracy and its accuracy is 20.67, 15.67, and 14.67 times higher than the inverse distance weighting (IDW), kriging, and spline, respectively. Then, a 0.4 km × 0.5 km rectangular area is used to test the effects of different spatial resolutions and sampling intervals on accuracy. This real-world test demonstrates that HASM-AC accuracy increases at a much better and stable pace as the spatial resolution becomes finer and sampling intervals get shorter, compared to the classic methods. Finally, the computing speed is tested in an area with 6000 × 6000 grid cells where Qinghai, Gansu, and Sichuan provinces meet. The computing speed of HASM-AC is 11, 8, and 563 times faster than IDW, spline, and kriging, respectively, which makes HASM-AC able to process data in a huge size and make real-time visualization realizable. In short, HASM-AC performs best in both the numerical and real-world tests.     

A Review of: Environmental Modelling with GIS.

Cartographic modelling operations provide powerful tools for analysing and manipulating geographic data in the raster data model. This research extends these operations to the vector data model. It first discusses how the spatial scopes of analysis can be defined for point, line, and polygon features analogous to the raster cell. Then it introduces the local, focal, and zonal operations available for vector features, followed by providing a prototype syntax that might guide the implementation of these operations. Through example applications, this research also demonstrates the usefulness of these operations by comparing them with traditional vector spatial analysis.     

Using GIS to analyse a severe forest blowdown in the Southern Rocky Mountains

Many studies have helped us understand where blowdowns occur, how forests regenerate and respond to large disturbances. However, few studies have analysed how physical and biological factors affect blowdowns or interact with one another to determine susceptibility to blowdown. These factors range from the natural physical setting to past disturbances, and human-related features, such as roads and timber harvest units. These factors were examined in this study. Patches of the blown-down forest were mapped for the 1997 Routt-Divide blowdown, which affected over 10 000 ha of subalpine forest in north-central Colorado. A systematic sampling scheme was used to extract information on predictors for sampling points inside and outside the blowdown. Data on predictors were used in Classification and Regression Trees (CART) and logistic regression to model blowdown occurrence and severity. Two models were applied, and both were able to predict with an overall success rate of 75% or more. These two models produced similar results, showing that the Routt-Divide blowdown was most influenced by factors pertaining to the physical setting: distance to the Continental Divide, wind exposure, elevation, aspect, and cover type. Surprisingly, soil permeability and water-holding capacity and distance to natural edges (e.g. forest-meadow) were not correlated significantly with the blowdown pattern.     

Population landscape: a geometric approach to studying spatial patterns of the US urban hierarchy

We present a geometric and graphic approach to studying spatial patterns of urban hierarchy in the US. The multiplicatively weighted Voronoi diagram is found to be effective for visualizing theoretical regions delineated by socio‐economic variables. The population landscape of the continental US demonstrates overall and stepwise patterns reflecting population, neighborhood and distance, with overwhelming influence from huge metropolitan areas. Stepwise exploration and cluster analysis of the spatial pattern reveal an urban hierarchy. Attributes and arrangement are the two important factors of urban hierarchy, with attribute having a stronger local influence and arrangement having a stronger global influence. The study also presents a variation of Zipf's law to visualize the rank‐size distribution from tabular and statistical space to map space.     

Assessment of downstream trends in channel gradient, total and specific stream power: a GIS approach

Geographic Information Systems (GIS) analyses of Digital Elevation Models (DEMs) coupled with catchment area based discharge estimation techniques provide a relatively simple means of modelling contiguous downstream trends in channel gradient, total stream power, and in riverscapes conducive to regime analysis, also specific stream power. For a small, high relief, coastal catchment in SE Australia, good agreement was obtained between channel gradients derived from a 25 m cell-size DEM and field survey equivalents over distances of several kilometres, indicating that channel gradients derived from DEMs can have a reasonable degree of absolute as well as relative accuracy over multi-kilometre reach scales. Assessment of downstream rates of change in channel gradient and specific stream power across four river systems suggests that some of the river reaches most responsive to high magnitude floods occur in zones where these variables rapidly decrease downstream. Modelling of downstream trends in channel gradient, total and specific stream power from catchment-wide DEMs has potential to provide a framework with which to investigate conceptual and empirical models between channel gradient, stream power and the form and dynamics of river systems.     

A unified approach for location-allocation analysis: integrating GIS,distributed computing and spatial optimization

Location-allocation modeling is an important area of research in spatial optimization and GIScience. A large number of analytical models for location-allocation analysis have been developed in the past 50 years to meet the requirements of different planning and spatial-analytic applications, ranging from the location of emergency response units (EMS) to warehouses and transportation hubs. Despite their great number, many location-allocation models are intrinsically linked to one another. A well-known example is the theoretical link between the classic p-median problem and coverage location problems. Recently, Lei and Church showed that a large number of classic and new location models can be posed as special case problems of a new modeling construct called the vector assignment ordered median problem (VAOMP). Lei and Church also reported extremely high computational complexity in optimally solving the best integer linear programming (ILP) formulation developed for the VAOMP even for medium-sized problems in certain cases.

In this article, we develop an efficient unified solver for location-allocation analysis based on the VAOMP model without using ILP solvers. Our aim is to develop a fast heuristic algorithm based on the Tabu Search (TS) meta-heuristic, and message passing interface (MPI) suitable for obtaining optimal or near-optimal solutions for the VAOMP in a real-time environment. The unified approach is particularly interesting from the perspective of GIScience and spatial decision support systems (DSS) as it makes it possible to solve a wide variety of location models in a unified manner in a GIS environment. Computational results show that the TS method can often obtain in seconds, solutions that are better than those obtained using the ILP-based approach in hours or a day.     

MODEL: a multicriteria ordinal evaluation tool for GIS

While the integration of geographical information systems (GIS) and multicriteria decision aiding (MCDA) has attracted increasing interest from researchers in recent years, due to the wide array of applications that can benefit from GIS as well as the different types of decision problems and various models that can be used through MCDA, plenty of opportunities of integrating GIS and MCDA remain. In this article, we present the result of such an opportunity in the form of a methodology and software that is currently used by the Naval Hydrographic and Oceanographic Service in France. Furthermore, this tool may be used in conjunction with other GIS–MCDA applications with a single decision maker, multiple decision makers or even where the decision has a hierarchical structure.     

Human geography and its relationship to GIS: a perspective from the vantage point of GIS

Concern abounds over what is a never ending sequence of paradigm shifts within human geography. One result is the marginalisation of previous work. Considerable concern has been expressed among those working with geographical information systems (GIS) over the relationship of this area of work to human geography. Behind much of this turmoil is the ascendancy of post‐modernism, an approach with which many human geographers are unable to actively engage in debate. At a time when the other social sciences are incorporating space into their research, human geography and GIS are parting company with the two facing very different futures.     

Ecological criteria, participant preferences and location models: A GIS approach toward ATV trail planning

This paper presents a geographic information system (GIS)-based method for recreational trail location for all-terrain vehicles (ATVs) which considers environmental factors, as well as rider preferences for trail attributes. The method utilizes the Least-Cost Path algorithm within a GIS framework to optimize trail location. The trail location algorithm considered trail impacts and benefits associated with water bodies, slope, land ownership, noise, trail separation, views, and rider preferences for vegetation types and loop trails. Alternative trails were generated to highlight the influence of different preferences for trail attributes and to demonstrate the capabilities of the Least-Cost Path algorithm as applied to trail location. The method shows promise for use in generating ATV trails, as well as other types of recreational trails, for consideration in recreational planning and analysis.     

Barrier dynamics for GIS: a design pattern for geospatial barriers

When separation between geospatial features is desired, an obstacle or barrier is used to maintain distance between the features. Barriers are used in a wide variety of domains, such as hazards, transportation, and public safety. Floodwalls, for example, prevent flooding rivers or lakes from inundating buildings. This work presents an ontology design pattern for barriers and barring events useful for GIS. In this ontology design pattern, active features (e.g., the water-body that is causing flooding) and target features (e.g., buildings requiring flood protection) are defined. Along with these key features, the ontology design pattern also captures certain barring events. These are the dynamics that arise from the placement of barriers and include Blocking, Enclosing, KeepingIn and KeepingOut, involving interactions among barriers, and active and target features. The set of classes that model these features and events as well as the relations between them are presented and formalized. This design pattern is ready for integration in a GIS to allow queries on barriers and barring events that do not currently have explicit support in most GIS.     

基于场所的GIS中的不确定性问题及分类框架

基于场所的GIS直接表达人类地理空间知识的管理和加工过程,而不确定性是人类智能的基本特点,因此GIS的智能化需要研究其中的不确定性问题。与传统的GIS相比,基于场所的GIS中的不确定性问题更为丰富,既包括随机性,也包括含糊性,而不确定性的主体既可以是地理要素、场所和空间关系,也包括命题和规则。该文介绍该领域相关的研究成果,基于不确定性主体、类型、表达手段及相关的活动4个视角,建立了基于场所的GIS中所涉及的不确定性框架,从而为相关的不确定性建模提供指导。     

Semantic interoperability:a metadata mediator approach

1 IntroductionWith fast development of infonnahon technology (IT), such as network and collUnbocation teClmology, itis necesseq to sharing geographical information (GI) through network. There are a lot of GI resourcesconnected by the netWork, which giVes good chance for accessing GI, but how to get the infonnationwhich we Wanted is a Challenge. That is because data is not only a Symbol, but it also needs to indiCate themeaning which it eXPresses. Due to the shared data coining from dif…     

3D building roof reconstruction from airborne LiDAR point clouds: a framework based on a spatial database

Three-dimensional (3D) building models are essential for 3D Geographic Information Systems and play an important role in various urban management applications. Although several light detection and ranging (LiDAR) data-based reconstruction approaches have made significant advances toward the fully automatic generation of 3D building models, the process is still tedious and time-consuming, especially for massive point clouds. This paper introduces a new framework that utilizes a spatial database to achieve high performance via parallel computation for fully automatic 3D building roof reconstruction from airborne LiDAR data. The framework integrates data-driven and model-driven methods to produce building roof models of the primary structure with detailed features. The framework is composed of five major components: (1) a density-based clustering algorithm to segment individual buildings, (2) an improved boundary-tracing algorithm, (3) a hybrid method for segmenting planar patches that selects seed points in parameter space and grows the regions in spatial space, (4) a boundary regularization approach that considers outliers and (5) a method for reconstructing the topological and geometrical information of building roofs using the intersections of planar patches. The entire process is based on a spatial database, which has the following advantages: (a) managing and querying data efficiently, especially for millions of LiDAR points, (b) utilizing the spatial analysis functions provided by the system, reducing tedious and time-consuming computation, and (c) using parallel computing while reconstructing 3D building roof models, improving performance.     

Broad area mapping of monthly soil erosion risk using fuzzy decision tree approach: integration of multi-source data within GIS

Soil erosion poses a serious problem for sustainable agriculture and the environment. There is a need to develop a simple and practical approach for broad area mapping of soil erosion risk that uses the uncertain but available information as input data within the constraints of reasonable cost and time. In this work, a predictive approach for conducting analytical erosion risk assessment across broad areas is developed, which combines a fuzzy decision tree (FDT), remote sensing and Geographic Information System (GIS). This approach is applicable to situations with a limited amount of input data and can easily adjust assessment factors according to actual need. In this study, four dominating factors affecting soil erosion were considered: soil, topography, land cover and climate. GIS thematic layers of these factors were constructed followed by fuzzified analysis through trapezoidal shaped membership functions. Based on subdivided erosion response units (ERUs), an optimal FDT was determined to classify monthly soil erosion risk into five levels. High-risk and very high-risk soil erosion in the study area is mainly concentrated from June to August, with July and August showing the highest risk covering more than 80% of the study area. November to March is dominated by low risk over more than 90% of the study area, while medium risk is dominant in April, May, September and October. Compared with field survey data, the fuzzy decision erosion risk assessment approach was shown to be applicable and economical for rapidly identifying and locating soil erosion risk with limited input data by means of remote sensing and GIS.