共查询到20条相似文献，搜索用时 437 毫秒
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The multi‐objective land allocation problem is to optimize the selection of land for different uses based on a set of decision objectives. For most applications, a geographical information system (GIS) is either absent or loosely coupled through file exchange. In this article the evolutionary algorithm (EA), a heuristic solution method for optimization problems, is integrated with a raster GIS to form a spatial decision support system (SDSS) for multi‐objective conservation reserve design. The SDSS effectively combines the functions of a GIS for data management, analysis, and visualization, with the optimization capability of the EA; and provides a uniform way to solve conservation reserve design problems with different types of constraints and objectives. The SDSS is demonstrated through application to the creation of conservation reserves in Bolivia to protect 17 endemic mammals. 相似文献
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A heuristic‐based approach to mitigating positional errors in patrol data for species distribution modeling 
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下载免费PDF全文 Species distribution modeling (SDM) at fine spatial resolutions requires species occurrence data of high positional accuracy to achieve good model performance. However, wildlife occurrences recorded by patrols in ranger‐based monitoring programs suffer from positional errors, because recorded locations represent the positions of the ranger and differ from the actual occurrence locations of wildlife (hereinafter referred to as positional errors in patrol data). This study presented an evaluation of the impact of such positional errors in patrol data on SDM and developed a heuristic‐based approach to mitigating the positional errors. The approach derives probable wildlife occurrence locations from ranger positions, utilizing heuristics based on species preferred habitat and the observer's field of view. The evaluations were conducted through a case study of SDM using patrol records of the black‐and‐white snub‐nosed monkey (Rhinopithecus bieti) in Yunnan, China. The performance of the approach was also compared against alternative sampling methods. The results showed that the positional errors in R. bieti patrol data had an adverse effect on SDM performance, and that the proposed approach can effectively mitigate the impact of the positional errors to greatly improve SDM performance. 相似文献
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Denis J. Dean 《Transactions in GIS》2013,17(2):159-181
Geospatial data analysis techniques are widely used to find optimal routes from specified starting points to specified destinations. Optimality is defined in terms of minimizing some impedance value over the length of the route – the value to be minimized might be distance, travel time, financial cost, or any other metric. Conventional analysis procedures assume that impedance values of all possible travel routes are known a priori, and when this assumption holds, efficient solution strategies exist that allow truly optimal solutions to be found for even very large problems. When impedance values are not known with certainty a priori, exact solution strategies do not exist and heuristics must be employed. This study evaluated how the quality of the solutions generated by one such heuristic were impacted by the nature of the uncertainty in the cost database, the nature of the costs themselves, and the parameters used in the heuristic algorithm. It was found that all of these factors influenced the qualities of the solutions produced by the heuristic, but encouragingly, an easily controlled parameter of the heuristic algorithm itself played the most important role in controlling solution quality. 相似文献
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Rajesh Chittor Sundaram Elham Naghizade Renata Borovica‐Gajic Martin Tomko 《Transactions in GIS》2020,24(4):1001-1032
Missing data in Volunteered Geographic Information (VGI) are an unavoidable consequence of data collection by non‐experts, guided by only vague and informal mapping guidelines. While various Missing Value Imputation (MVI) techniques have been proposed as data cleansing strategies, they have primarily targeted numerical data attributes in non‐spatial databases. There remains a significant gap in methods for imputing nominal attribute values (e.g., Street Name) in map databases. Here, we present an imputation algorithm called the Membership Imputation Algorithm (MIA), targeting spatial databases and enabling imputation of nominal values in spatially referenced records. By targeting membership classes of spatial objects, MIA harnesses spatio‐temporal characteristics of data and proposes efficient heuristics to impute the class name (i.e., a membership). Experimental results show that the proposed algorithm is able to impute the membership with high levels of accuracy (over 94%) when assigning Street Name(s), across highly diverse regional contexts. MIA is effective in challenging spatial contexts such as street intersections. Our research serves as a first step in highlighting the effectiveness of spatio‐temporal measures as a key driver for nominal imputation techniques. 相似文献
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A spatial parallel heuristic approach for solving very large‐scale vehicle routing problems 下载免费PDF全文
下载免费PDF全文 Wei Tu Qingquan Li Qiuping Li Jiasong Zhu Baoding Zhou Biyu Chen 《Transactions in GIS》2017,21(6):1130-1147
The vehicle routing problem (VRP) is one of the most prominent problems in spatial optimization because of its broad applications in both the public and private sectors. This article presents a novel spatial parallel heuristic approach for solving large‐scale VRPs with capacity constraints. A spatial partitioning strategy is devised to divide a region of interest into a set of small spatial cells to allow the use of a parallel local search with a spatial neighbor reduction strategy. An additional local search and perturbation mechanism around the border area of spatial cells is used to improve route segments across spatial cells to overcome the border effect. The results of one man‐made VRP benchmark and three real‐world super‐large‐scale VRP instances with tens of thousands of nodes verify that the presented spatial parallel heuristic approach achieves a comparable solution with much less computing time. 相似文献
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Estimates of solar radiation distribution in urban areas are often limited by the complexity of urban environments. These limitations arise from spatial structures such as buildings and trees that affect spatial and temporal distributions of solar fluxes over urban surfaces. The traditional solar radiation models implemented in GIS can address this problem only partially. They can be adequately used only for 2‐D surfaces such as terrain and rooftops. However, vertical surfaces, such as facades, require a 3‐D approach. This study presents a new 3‐D solar radiation model for urban areas represented by 3‐D city models. The v.sun module implemented in GRASS GIS is based on the existing solar radiation methodology used in the topographic r.sun model with a new capability to process 3‐D vector data representing complex urban environments. The calculation procedure is based on the combined vector‐voxel approach segmenting the 3‐D vector objects to smaller polygon elements according to a voxel data structure of the volume region. The shadowing effects of surrounding objects are considered using a unique shadowing algorithm. The proposed model has been applied to the sample urban area with results showing strong spatial and temporal variations of solar radiation flows over complex urban surfaces. 相似文献
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One of the simplest location models in terms of its constraint structure in location‐allocation modeling is the location set‐covering problem (LSCP). Although there have been a variety of geographic applications of the set‐covering problem (SCP), the use of the SCP as a facility location model is one of the most common. In the early applications of the LSCP, both potential facility sites as well as demand were represented by points discretely located in geographic space. The advent of geographic information systems (GIS), however, has made possible a greater range of object representations that can reduce representation error. The purpose of this article is to outline a methodology using GIS and K = 3 central place lattices to solve the LSCP when demand is continuously distributed over a bounded area and potential facility sites have not been defined a priori. Although, demand is assumed to exist over an area, it is shown how area coverage can be accomplished by the coverage of a point pattern. Potential facility site distributions based on spacings that are powers of one‐third the coverage distance are also shown to provide more efficient coverage than arbitrarily chosen spacings. Using GIS to make interactive adjustments to an incomplete coverage also provides an efficient alternative to smaller spacings between potential facility sites for reducing the number of facilities necessary for complete coverage. 相似文献
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Spatial co‐location pattern mining aims to discover a collection of Boolean spatial features, which are frequently located in close geographic proximity to each other. Existing methods for identifying spatial co‐location patterns usually require users to specify two thresholds, i.e. the prevalence threshold for measuring the prevalence of candidate co‐location patterns and distance threshold to search the spatial co‐location patterns. However, these two thresholds are difficult to determine in practice, and improper thresholds may lead to the misidentification of useful patterns and the incorrect reporting of meaningless patterns. The multi‐scale approach proposed in this study overcomes this limitation. Initially, the prevalence of candidate co‐location patterns is measured statistically by using a significance test, and a non‐parametric model is developed to construct the null distribution of features with the consideration of spatial auto‐correlation. Next, the spatial co‐location patterns are explored at multi‐scales instead of single scale (or distance threshold) discovery. The validity of the co‐location patterns is evaluated based on the concept of lifetime. Experiments on both synthetic and ecological datasets show that spatial co‐location patterns are discovered correctly and completely by using the proposed method; on the other hand, the subjectivity in discovery of spatial co‐location patterns is reduced significantly. 相似文献
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CHRISTOPHER J BROOKES 《Transactions in GIS》1997,2(3):201-212
Locating optimal sites on raster suitability maps is a complex problem when the size of the sites is larger than the cell size. There are a number of techniques for generating suitability maps, but these maps are not solutions to the site location problem. Feasible solutions are clusters of contiguous cells which meet spatial criteria concerning the size and shape of the clusters. Locaring optimal sites involves a trade-off between the intrinsic suitability of individual cells and the spatial configuration of cells. This paper describes a genetic algorithm which searches for optimal clusters and thereby locates optimal sites. The genetic algorithm uses a parameterized regiongrowing program to translate numeric strings into regions on a raster and employs raster GIS functions to evaluate utility scores. In a range of simulated problems, comparisons with an exhaustive search show that the genetic algorithm is efficient and robust. The results indicate that the genetic algorithm can find good solutions to real problems when exhaustive search methods are impractical. 相似文献
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In this article we present a heuristic map simplification algorithm based on a novel topology‐inferred graph model. Compared with the existing algorithms, which only focus either on geometry simplification or on topological consistency, our algorithm simplifies the map composed of series of polylines and constraint points while maintaining the topological relationships in the map, maximizing the number of removal points, and minimizing error distance efficiently. Unlike some traditional geometry simplification algorithms, such as Douglas and Peucker's, which add points incrementally, we remove points sequentially based on a priority determined by heuristic functions. In the first stage, we build a graph to model the topology of points in the map from which we determine whether a point is removable or not. As map generalization is needed in different applications with different requirements, we present two heuristic functions to determine the priority of points removal for two different purposes: to save storage space and to reduce computation time. The time complexity of our algorithm is which is efficient enough to be considered for real‐time applications. Experiments on real maps were conducted and the results indicate that our algorithm produces high quality results; one heuristic function results in higher removal points saving storage space and the other improves the time performance significantly. 相似文献
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Spatial optimization for land acquisition problems: A review of models,solution methods,and GIS support 总被引：1，自引：0，他引：1
This article reviews the interdisciplinary research field of spatial optimization for land acquisition problems. We start with a theoretical framework to identify three categories of spatial optimization models: problems with aspatial constraints, location models, and problems with topological constraints. Exact, heuristic, and metaheuristic approaches to solving these problems are critically discussed. Tools that are available in commercial and open‐source GIS packages are reviewed from four aspects. We first survey the off‐the‐shelf support and then the development environments in these packages. A case study of the one‐center problem is used to illustrate the computational performance of different solution methods. Finally the advantages and disadvantages of current GIS data models are discussed. The article concludes with challenges and future directions for solving spatial optimization problems for land acquisition. 相似文献
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A Hybrid Link‐Node Approach for Finding Shortest Paths in Road Networks with Turn Restrictions 下载免费PDF全文
下载免费PDF全文 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. 相似文献
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ADCN: An anisotropic density‐based clustering algorithm for discovering spatial point patterns with noise 下载免费PDF全文
下载免费PDF全文 Density‐based clustering algorithms such as DBSCAN have been widely used for spatial knowledge discovery as they offer several key advantages compared with other clustering algorithms. They can discover clusters with arbitrary shapes, are robust to noise, and do not require prior knowledge (or estimation) of the number of clusters. The idea of using a scan circle centered at each point with a search radius Eps to find at least MinPts points as a criterion for deriving local density is easily understandable and sufficient for exploring isotropic spatial point patterns. However, there are many cases that cannot be adequately captured this way, particularly if they involve linear features or shapes with a continuously changing density, such as a spiral. In such cases, DBSCAN tends to either create an increasing number of small clusters or add noise points into large clusters. Therefore, in this article, we propose a novel anisotropic density‐based clustering algorithm (ADCN). To motivate our work, we introduce synthetic and real‐world cases that cannot be handled sufficiently by DBSCAN (or OPTICS). We then present our clustering algorithm and test it with a wide range of cases. We demonstrate that our algorithm can perform equally as well as DBSCAN in cases that do not benefit explicitly from an anisotropic perspective, and that it outperforms DBSCAN in cases that do. Finally, we show that our approach has the same time complexity as DBSCAN and OPTICS, namely O(n log n) when using a spatial index and O(n2) otherwise. We provide an implementation and test the runtime over multiple cases. 相似文献
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While cellular automata have become popular tools for modeling land‐use changes, there is a lack of studies reporting their application at very fine spatial resolutions (e.g. 5 m resolution). Traditional cell‐based CA do not generate reliable results at such resolutions because single cells might only represent components of land‐use entities (i.e. houses or parks in urban residential areas), while recently proposed entity‐based CA models usually ignore the internal heterogeneity of the entities. This article describes a patch‐based CA model designed to deal with this problem by integrating cell and object concepts. A patch is defined as a collection of adjacent cells that might have different attributes, but that represent a single land‐use entity. In this model, a transition probability map was calculated at each cell location for each land‐use transition using a weight of evidence method; then, land‐use changes were simulated by employing a patch‐based procedure based on the probability maps. This CA model, along with a traditional cell‐based model were tested in the eastern part of the Elbow River watershed in southern Alberta, Canada, an area that is under considerable pressure for land development due to its proximity to the fast growing city of Calgary. The simulation results for the two models were compared to historical data using visual comparison, Ksimulation indices, and landscape metrics. The results reveal that the patch‐based CA model generates more compact and realistic land‐use patterns than the traditional cell‐based CA. The Ksimulation values indicate that the land‐use maps obtained with the patch‐based CA are in higher agreement with the historical data than those created by the cell‐based model, particularly regarding the location of change. The landscape metrics reveal that the patch‐based model is able to adequately capture the land‐use dynamics as observed in the historical data, while the cell‐based CA is not able to provide a similar interpretation. The patch‐based approach proposed in this study appears to be a simple and valuable solution to take into account the internal heterogeneity of land‐use classes at fine spatial resolutions and simulate their transitions over time. 相似文献
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Gengchen Mai Krzysztof Janowicz Ling Cai Rui Zhu Blake Regalia Bo Yan Meilin Shi Ni Lao 《Transactions in GIS》2020,24(3):623-655
Learning knowledge graph (KG) embeddings is an emerging technique for a variety of downstream tasks such as summarization, link prediction, information retrieval, and question answering. However, most existing KG embedding models neglect space and, therefore, do not perform well when applied to (geo)spatial data and tasks. Most models that do consider space primarily rely on some notions of distance. These models suffer from higher computational complexity during training while still losing information beyond the relative distance between entities. In this work, we propose a location‐aware KG embedding model called SE‐KGE. It directly encodes spatial information such as point coordinates or bounding boxes of geographic entities into the KG embedding space. The resulting model is capable of handling different types of spatial reasoning. We also construct a geographic knowledge graph as well as a set of geographic query–answer pairs called DBGeo to evaluate the performance of SE‐KGE in comparison to multiple baselines. Evaluation results show that SE‐KGE outperforms these baselines on the DBGeo data set for the geographic logic query answering task. This demonstrates the effectiveness of our spatially‐explicit model and the importance of considering the scale of different geographic entities. Finally, we introduce a novel downstream task called spatial semantic lifting which links an arbitrary location in the study area to entities in the KG via some relations. Evaluation on DBGeo shows that our model outperforms the baseline by a substantial margin. 相似文献
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Qualitative locations describe spatial objects by relating the spatial objects to a frame of reference (e.g. a regional partition in this study) with qualitative relations. Existing models only formalize spatial objects, frames of reference, and their relations at one scale, thus limiting their applicability in representing location changes of spatial objects across scales. A topology‐based, multi‐scale qualitative location model is proposed to represent the associations of multiple representations of the same objects with respect to the frames of reference at different levels. Multi‐scale regional partitions are first presented to be the frames of reference at multiple levels of scale. Multi‐scale locations are then formalized to relate multiple representations of the same objects to the multiple frames of reference by topological relations. Since spatial objects, frames of reference, and topological relations in qualitative locations are scale dependent, scale transformation approaches are presented to derive possible coarse locations from detailed locations by incorporating polygon merging, polygon‐to‐line and polygon‐to‐point operators. 相似文献
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Qualitative representation of spatial locations and their similarity measurements are essential for the analysis of linguistic term‐based data. Existing methods have focused on the similarities of spatial relations and spatial scenes but have not considered the variations in geometrical representations and relations over scales. This study developed some new measures to assess the similarities of both single‐ and multi‐scale qualitative locations. Region‐ and cell‐based models were used to formalize qualitative locations of spatial objects with respect to multi‐scale frames of reference. The similarities were assessed by integrating the similarities of frames and qualitative relations. The frame similarity measures how two objects are compared considering the common elements that they occupy in the reference frames. Moreover, the similarity of qualitative relation measures how two relations relate two objects to the corresponding elements in the frames. The location similarities at a single level integrate the similarities of the frames and qualitative relations, whereas the location similarities at multiple scales incorporate the variations in qualitative locations over scales. These methods were used to assess location similarities concerning residential areas, roads, and lakes. The results indicated that the location‐based measurements can disclose the distributions of the similarities and that the cell‐based model is more accurate than the region‐based model. 相似文献
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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. 相似文献
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Much effort has been applied to the study of land use multi‐objective optimization. However, most of these studies have focused on the final land use scenarios in the projected year, without considering how to reach the final optimized land use scenario. To fill this gap, a spatio‐temporal land use multi‐objective optimization (STLU‐MOO) model is innovatively proposed in this research to determine possible spatial land use solutions over time. The STLU‐MOO is an extension of a genetic land use multi‐objective optimization model (LU‐MOO) in which the LU‐MOO is generally carried out in different years, and the solutions at year T will affect the solutions at year T + 1. We used the Wuhan agglomeration (WHA) as our case study area. The STLU‐MOO model was employed separately for the nine cities in the WHA, and social, economic, and environmental objectives have been considered. The success of the experiments in the case study demonstrated the value and novelty of our proposed STLU‐MOO model. In addition, the results also indicated that the objectives considered in the case study were in conflict. According to the results, the optimal land use plan in 2050 can be traced back to 2040, 2030, and 2020, providing a series of Pareto solutions over the years which can provide spatio‐temporal land use multi‐objective optimization solutions to support the land use planning process. 相似文献