How to compare movement? A review of physical movement similarity measures in geographic information science and beyond

In geographic information science, a plethora of different approaches and methods is used to assess the similarity of movement. Some of these approaches term two moving objects similar if they share akin paths. Others require objects to move at similar speed and yet others consider movement similar if it occurs at the same time. We believe that a structured and comprehensive classification of movement comparison measures is missing. We argue that such a classification not only depicts the status quo of qualitative and quantitative movement analysis, but also allows for identifying those aspects of movement for which similarity measures are scarce or entirely missing.

In this review paper we, first, decompose movement into its spatial, temporal, and spatiotemporal movement parameters. A movement parameter is a physical quantity of movement, such as speed, spatial path, or temporal duration. For each of these parameters we then review qualitative and quantitative methods of how to compare movement. Thus, we provide a systematic and comprehensive classification of different movement similarity measures used in geographic information science. This classification is a valuable first step toward a GIS toolbox comprising all relevant movement comparison methods.     

Broad-scale spatial pattern of forest landscape types in the Guiana Shield

Detecting broad scale spatial patterns across the South American rainforest biome is still a major challenge. Although several countries do possess their own, more or less detailed land-cover map, these are based on classifications that appear largely discordant from a country to another. Up to now, continental scale remote sensing studies failed to fill this gap. They mostly result in crude representations of the rainforest biome as a single, uniform vegetation class, in contrast with open vegetations. A few studies identified broad scale spatial patterns, but only when they managed to map a particular forest characteristic such as biomass. The main objective of this study is to identify, characterize and map distinct forest landscape types within the evergreen lowland rainforest at the sub-continental scale of the Guiana Shield (north-east tropical South-America 10° North-2° South; 66° West-50° West). This study is based on the analysis of a 1-year daily data set (from January 1st to December 31st, 2000) from the VEGETATION sensor onboard the SPOT-4 satellite (1-km spatial resolution). We interpreted remotely sensed landscape classes (RSLC) from field and high resolution remote sensing data of 21 sites in French Guiana. We cross-analyzed remote sensing data, field observations and environmental data using multivariate analysis. We obtained 33 remotely sensed landscape classes (RSLC) among which five forest-RSLC representing 78% of the forested area. The latter were classified as different broad forest landscape types according to a gradient of canopy openness. Their mapping revealed a new and meaningful broad-scale spatial pattern of forest landscape types. At the scale of the Guiana Shield, we observed a spatial patterns similarity between climatic and forest landscape types. The two most open forest-RSLCs were observed mainly within the north-west to south-east dry belt. The three other forest-RSLCs were observed in wetter and less anthropized areas, particularly in the newly recognized “Guianan dense forest arch”. Better management and conservation policies, as well as improvement of biological and ecological knowledge, require accurate and stable representations of the geographical components of ecosystems. Our results represent a decisive step in this way for the Guiana Shield area and contribute to fill one of the major shortfall in the knowledge of tropical forests.     

A New Construction Method for Circle Cartograms

An area cartogram is a transformed map on which areas of regions are proportional to statistical data values; it is considered to be a powerful tool for the visual representation of statistical data. A circle cartogram is a type of area cartograms, on which regions are represented by circles. Its first construction algorithm is proposed by Dorling in 1996, based on the following requirements to construct visually elegant cartograms: 1) maintain the similarity of configurations between circles and regions, 2) express the contiguity of regions on cartograms if possible, and 3) avoid overlap of circles. The algorithm is widely used for its easiness to use and its ability to express a spatial distribution of data; however, the relative positions of circles on cartograms sometimes greatly differ from the geographical maps, since the algorithm does not consider the first requirements explicitly. In this paper, it is first pointed out that the construction problem of circle cartograms resembles that of distance cartograms, and the only difference is the existence of third requirement. Then a new construction method for circle cartograms is proposed based on the distance cartogram construction method; the proposed method is formulated as non-linear minimization with inequality constraint conditions. Finally its applicability is confirmed using dataset, including the comparison with the result of previous algorithm.     

Map Generalization with a Triangulated Data Structure

Automation of map generalization requires facilities to monitor the spatial relationships and interactions among multiple map objects. An experimental map generalization system has been developed which addresses this issue by representing spatial objects within a simplicial data structure (SDS) based on constrained Delaunay triangulation of the source data. Geometric generalization operators that have been implemented include object exaggeration, collapse, amalgamation, boundary reduction and displacement. The generalization operators exploit a set of primitive SDS functions to determine topological and proximal relationships, measure map objects, apply transformations, and detect and resolve spatial conflicts. Proximal search functions are used for efficient analysis of the structure and dimensions of the intervening spaces between map objects. Because geometric generalization takes place within a fully triangulated representation of the map surface, the presence of overlap conflicts, resulting from individual operators, can be detected due to the introduction of singularities in the triangulation, the structure of which is used to generate displacement vectors to resolve the conflict. Examples of the application of the implemented operators are described and illustrated using large scale topographic map data.     

Approach to calculating spatial similarity degrees of the same river basin networks on multi-scale maps

Obtaining spatial similarity degrees among the same objects on multi-scale maps is of importance in map generalization. This paper firstly defines the concepts of ‘map scale change’ and ‘spatial similarity degree’; then it proposes a model for calculating the spatial similarity degree between a river basin network at one scale and its generalized version at another scale. After this, it validates the new model and gets 16 points in the model validation process. The x-coordinate and y-coordinate of each point are map scale change and spatial similarity degree, respectively. Last, a formula for calculating spatial similarity degree taking map scale change as the only variable is obtained by the curve fitting method. The formula along with the model can be used to automate the algorithms for simplifying river basin networks.     

Mapping collective human activity in an urban environment based on mobile phone data

Identifying and characterizing variations of human activity – specifically changes in intensity and similarity – in urban environments provide insights into the social component of those eminently complex systems. Using large volumes of user-generated mobile phone data, we derive mobile communication profiles that we use as a proxy for the collective human activity. In this article, geocomputational methods and geovisual analytics such as self-organizing maps (SOM) are used to explore the variations of these profiles, and its implications for collective human activity. We evaluate the merits of SOM as a cross-dimensional clustering technique and derived temporal trajectories of variations within the mobile communication profiles. The trajectories’ characteristics such as length are discussed, suggesting spatial variations in intensity and similarity in collective human activity. Trajectories are linked back to the geographic space to map the spatial and temporal variation of trajectory characteristics. Different trajectory lengths suggest that mobile phone activity is correlated with the spatial configuration of the city, and so at different times of the day. Our approach contributes to the understanding of the space-time social dynamics within urban environments.     

Objective and Subjective Comparison in Choroplethic Mapping

Abstract

Visual map comparison can supplement statistical analysis by providing information as to where and how spatial correspondence occurs. The associations that may be discovered are influenced by the nature of the map features being compared and the criteria used for making the comparisons. In this paper the author has tried to identify the elements of visual recognition that map readers use to associate or differentiate geographical distributions represented by choropleth maps. The main components of the multivariate map reading process are pointed out, including the perceptual interactions between the actual locations of map tones and the overall similarity between map patterns.     

Quantitative relations between spatial similarity degree and map scale change of individual linear objects in multi-scale map spaces

Quantitative relations between spatial similarity degree and map scale change in multi-scale map spaces play important roles in map generalization and construction of spatial data infrastructure. Nevertheless, no achievements have been made regarding this issue. To fill the gap, this paper firstly proposes a model for calculating spatial similarity degrees between an individual linear object at one scale and its generalized counterpart at the other scale. Then psychological experiments are designed to validate the new model, taking four different individual linear objects at five different scales as test samples. The experiments have shown that spatial similarity degrees calculated by the new model can be accepted by a majority of the subjects. After this, it constructs a formula that can calculate spatial similarity degree using map scale change (and vice versa) for individual linear objects in multi-scale map spaces by the curve fitting method using the point data from the psychological experiments. Both the formula and the model can calculate quantitative relations between spatial similarity degree and map scale change of individual linear objects in multi-scale map spaces, which facilitates automation of map generalization algorithms for linear features.     

Investigating relationships between Landsat-7 ETM data and spatial segregation of LULC types under shifting agriculture in southern Cameroon

This paper investigates statistical relationships between land use/land cover (LULC), Landsat-7 ETM⁺ imagery and landscape mosaic structure in southern Cameroon where the conversion of tropical rain forest to shifting cultivation leads to dynamic processes, acting on the spatial aggregation of various LULC types. A Global Positioning System (GPS) was used in the field to identify a total of 171 shifting cultivation patches representing eight LULC types in two sub-areas. Because of the lack of a cloud-free image for the date of field sampling, the ETM⁺ imagery was acquired 2 months after field survey, during which it was assumed that no significant changes in LULC occurred (all dry season). Per pixel correlations were developed between spectral reflectance data, vegetation indices and LULC. As an exploratory study, several statistical methods (analysis of variance, means separations (Tukey HSD), principal component analysis (PCA), geo-statistical analysis, image classification and landscape metrics) were applied on point data and sensor images for evaluating the spatial variability within the landscape. Most variables explained 30–72% of LULC variation in the whole dataset. Those variables with high information content of LULC (infrared bands 4, 5, 7 and derived indices and PC1) also showed long ranges (6 km) spatial dependence as compared to those varying only within 1 km range. The results of these statistical analyses suggested the need to group some LULC types and the application of the Maximum Likelihood Classifier (MLC) for supervised classification provided a LULC map with the highest accuracy (81%) after consolidation of perennial LULC types, such as bush fallow, forest fallow and cocoa plantations. Landscape metrics computed from this map showed a high level of patch diversity and connectivity within the landscape and provided input data that can further be used to simulate predictive maps as substitute to cloud-covered sensor imageries. Landsat-7 ETM⁺ imagery proved to be useful in discriminating (with about 80% accuracy) the most dynamic LULC types such cropped plots and young fallow patches (shifting every season) and the extension front of the agricultural landscape.     

综合聚类和上下文特征的高光谱影像分类

常规高光谱影像逐像素分类往往没有考虑空间相关性,分类结果未体现地物的空间关联和分布特征。为了在分类中充分利用空间特征,利用聚类信息并结合隐马尔可夫随机场模型讨论了高光谱遥感影像光谱-空间分类方法。首先,在不同特征提取方法（最小噪声分离、独立成分分析和主成分分析）下,使用不同聚类方法（k-均值、迭代自组织分析算法和模糊c-均值算法）借助隐马尔可夫随机场获取优化的分割图;然后,采用4连通区域标记法对分割区域标记生成图像对象,并根据支持向量机的逐像素分类结果采用多数投票法对图像对象进行分类;最后,借助凹槽窗口邻域滤波技术改进分类结果,削弱“椒盐”现象。该方法综合了监督分类和非监督分类的优势,通过聚类引入地物空间相关性信息,通过隐马尔可夫随机场引入上下文特征,较好地弥补了单纯基于光谱信息分类的不足。     

Cartography: Making Sense of Our Worlds

Abstract

One goal of cartographic research is to improve the usefulness of maps. To do so, we must consider the process of spatial knowledge acquisition, the role of maps in that process, and the content of cognitive representations derived. Research from psychology, geography, and other disciplines related to these issues is reviewed. This review is used to suggest potential new directions for research with particular attention to spatial problem solving and geographic instruction. A classroom experiment related to these issues is then described. The experiment highlights some of the implications that a concern for the process of spatial knowledge acquisition will have on questions and methods of cartographic research as well as on the use of maps in geographic instruction. It also provides evidence of independent but interrelated verbal and spatial components of regional images that can be altered by directed map work.     

2D地图的建筑物场景结构提取方法及其在城市增强现实中的应用

城市AR中,场景结构的自动获取,对自适应信息表达具有重要意义,是解决“层叠式”信息表现形式引发的信息指示不明、场景感知混乱等问题的关键步骤。然而,场景结构信息隐藏在场景图像中,直接提取十分困难。2D地图描述了地理实体的位置、轮廓和空间布局,可作为场景结构提取的先验信息。针对城市AR中场景结构获取难、效率低的问题,本文提出一种基于2D地图的建筑物场景结构自动化提取方法。在地理配准的基础上,首先根据2D地图中建筑物的轮廓和属性信息,构建场景图像语义分割的结构线索;然后将其作为过分割处理后场景图像合并的依据,生成多个包含语义信息的图像区域;最后根据图像区域与2D地图中建筑物轮廓之间的映射关系,提取出场景图像中的区域轮廓、场景深度和平面朝向等场景结构信息。试验选取了格拉茨地区32个建筑物场景进行测试。结果表明本文方法能实时地提取建筑物场景结构,且建筑物立面提取的质量明显优于对比方法。提取的场景结构能应用于城市AR多种自适应信息表达方法中,使信息标注更明确,遮挡关系更清晰。     

Detecting subpixel deciduous components to complement traditional land cover classifications in Southwest Finland

To ensure successful conservation of ecological and cultural landscape values, detailed and up-to-date spatial information of existing habitat patterns is essential. However, traditional satellite-based and raster classifications rely on pixels that are assigned to a single category and often generalized. For many fragmented key habitats, such a strategy is too coarse and complementary data is needed. In this paper, we aim at detecting pixel-wise fractional coverage of broadleaved woodland and grassland components in a hemiboreal landscape. This approach targets ecologically relevant deciduous fractions and complements traditional crisp land cover classifications. We modeled fractional components using a k-NN approach, which was based on multispectral satellite data, assisted by a digital elevation model and a contemporary map database. The modeled components were then analyzed based on landscape structure indicators, and evaluated in conjunction with CORINE classification. The results indicate that both broadleaved forest and grassland components are widely distributed in the study area, principally organized as transition zones and small patches. Landscape structure indicators show a substantial variation based on the fractional threshold, pinpointing their dependency on the classification scheme and grain. The modeled components, on the other hand, suggest high internal variation for most CORINE classes, indicating their heterogeneous appearance and showing that the presence of deciduous components in the landscape are not properly captured in a coarse land cover classification. To gain a realistic perception of the landscape, and use this information for the needs of spatial planning, both fractional results and existing land cover classifications are needed. This is because they mutually contribute to an improved understanding of habitat patterns and structures, and should be used to complement each other.     

一种基于Fréchet距离的断裂等高线内插算法

等高线内插是提高地形图精度的一个常用手段,在地图综合等领域中有很重要的作用。在实际地形图数据库中,等高线除了存在完整的计曲线以外,还有一部分断裂的首曲线。已有的等高线内插研究中未考虑对此类数据的处理,为此,本文提出了一种基于Fréchet距离的断裂等高线内插算法。首先提出了等高线度量关系的计算方法,然后对等高线的节点均匀加密,并利用Fréchet距离进行相似度判断以选择参考等高线,最后根据“最近点”的方式进行插值。通过对江苏某地区实际数据的试验,验证了该算法的合理性,对于鞍部地区的内插,有更好的适应性和准确性。     

一种应用三角形划分的空间对象形状匹配方法

为解决现有空间对象形状相似性匹配准确率较低的问题,提出一种应用三角形划分的形状相似性匹配方法。该方法按形状主方向对面状空间对象进行分割,按串联、并联和组合形式对空间对象进行三角形划分,准确描述面状空间对象的形状特征,度量空间对象间的形状相似性。通过形状数据集匹配、不同年份面状水系图层匹配和矢量地图草图检索,测试本方法的形状检索性能,并和其他空间对象形状匹配方法进行对比。实验结果表明,本方法具有更高的形状检索准确率。三角形划分形状匹配方法具有平移、旋转、尺度不变性和较强的形状描述识别能力。     

Mapping areas of asynchronous‐temporal interaction in animal‐telemetry data

Animal interactions are a crucial aspect of behavioral ecology that affect mating, territorial behavior, resource use, and disease spread. Commonly, animals will interact because of shared resources. Recent methods have used time geography to map landscape areas where interactions were possible. However, such methods do not identify areas of less direct interaction, like through smell or sight. These indirect or asynchronous interactions are also a crucial aspect of animal behavioral ecology and affect group behaviors such as leading/following hierarchies and joint resource use. Asynchronous interactions are difficult to map because they can occur in a synchronous space at asynchronous times, as well as in asynchronous spaces at a synchronous time. Here, we present a method termed the temporally asynchronous‐joint potential path area (ta‐jPPA) that maps areas of potential temporally asynchronous–spatially synchronous interactions. We used simulated data to statistically test ta‐jPPA and empirical data to demonstrate how ta‐jPPA can find patterns in habitat use.     

Mapping the distribution of the main host for plague in a complex landscape in Kazakhstan: An object-based approach using SPOT-5 XS,Landsat 7 ETM+, SRTM and multiple Random Forests

Plague is a zoonotic infectious disease present in great gerbil populations in Kazakhstan. Infectious disease dynamics are influenced by the spatial distribution of the carriers (hosts) of the disease. The great gerbil, the main host in our study area, lives in burrows, which can be recognized on high resolution satellite imagery. In this study, using earth observation data at various spatial scales, we map the spatial distribution of burrows in a semi-desert landscape.The study area consists of various landscape types. To evaluate whether identification of burrows by classification is possible in these landscape types, the study area was subdivided into eight landscape units, on the basis of Landsat 7 ETM+ derived Tasselled Cap Greenness and Brightness, and SRTM derived standard deviation in elevation.In the field, 904 burrows were mapped. Using two segmented 2.5 m resolution SPOT-5 XS satellite scenes, reference object sets were created. Random Forests were built for both SPOT scenes and used to classify the images. Additionally, a stratified classification was carried out, by building separate Random Forests per landscape unit.Burrows were successfully classified in all landscape units. In the ‘steppe on floodplain’ areas, classification worked best: producer's and user's accuracy in those areas reached 88% and 100%, respectively. In the ‘floodplain’ areas with a more heterogeneous vegetation cover, classification worked least well; there, accuracies were 86 and 58% respectively. Stratified classification improved the results in all landscape units where comparison was possible (four), increasing kappa coefficients by 13, 10, 9 and 1%, respectively.In this study, an innovative stratification method using high- and medium resolution imagery was applied in order to map host distribution on a large spatial scale. The burrow maps we developed will help to detect changes in the distribution of great gerbil populations and, moreover, serve as a unique empirical data set which can be used as input for epidemiological plague models. This is an important step in understanding the dynamics of plague.     

Vineyard site suitability analysis by use of multicriteria approach applied on geo-spatial data

Abstract

In this research, multicriteria decision analysis with pairwise comparison weighting method was utilized to determine the suitable locations for vineyard plantation in Sarkoy region of Turkey. Soil maps, meteorological measurements, slope, aspect and elevation maps were used as input to conduct spatial analysis. Different methods were compared and pairwise comparison method was identified as the most appropriate method of weighting for this spatial analysis. Current vineyard areas were determined using Worldview-2 imagery and their spatial distribution compared with the resulting suitability map to determine the current suitability. Comparisons showed current vineyards were mostly established in locations where suitability map expresses low capability. Further inspection unveiled that, these low capability lands are closer to the transportation networks and city/county centres that tend to be in sea level elevations as opposed to vine grapes thriving in higher altitudes. Results also enabled providing suggestions on alternative sites for new vineyard plantation.     

BinSq: visualizing geographic dot density patterns with gridded maps

ABSTRACT

Dot maps have become a popular way to visualize discrete geographic data. Yet, beyond showing how the data are spatially distributed, dot maps are often visually cluttered in terms of consistency, overlap, and representativeness. Existing clutter reduction techniques like jittering, refinement, distortion, and aggregation also address this issue, but do so by arbitrarily displacing dots from their exact location, removing dots from the map, changing the spatial reference of the map, or reducing its level of detail, respectively. We present BinSq, a novel visualization technique to compare variations in dot density patterns without visual clutter. Based on a careful synthesis of existing clutter reduction techniques, BinSq reduces the wide variety of dot density variations on the map to a representative subset of density intervals that are more distinguishable. The subset is derived from a nested binning operation that introduces order and regularity to the map. Thereafter, a dot prioritization operation improves the representativeness of the map by equalizing visible data values to correspond with the actual data. In this paper, we describe the algorithmic implementation of BinSq, explore its parametric design space, and discuss its capabilities in comparison to six existing clutter reduction techniques for dot maps.     

基于禁忌搜索的点状注记研究

地图注记是为待定位注记求取注记位置的过程,它是自动地图制图中的一个重要的难题,其中点状注记问题可以看作是一个组合优化问题。解决优化组合问题,目前有许多成熟的算法,比如模拟退火法,遗传算法,神经网络优化算法以及禁忌算法等等。目前,模拟退火法,遗传算法和神经网络优化算法已经被用来优化点状注记的配置问题。本文将介绍禁忌算法在点状注记配置中的应用,并用国家1∶250000地形图点状居民地图层数据实验,证明该方法有较高的搜索效率,得到的注记结果基本上解决了压盖问题。