ISPRS Int. J. Geo-Inf., Volume 4, Issue 2 (June 2015) – 32 articles , Pages 418-1032

By developing an interactive open source-based WebGIS information portal on war and peace for the online services of the Federal Agency for Civic Education, the Bonn International Center for Conversion (BICC) translates scientific knowledge into easily understandable and subsumable up-to-date information for the general public and young scholars. By aggregating globally scattered data and information on various peace- and conflict-related topics as well as presenting their spatial visualization through interactive maps, BICC contributes to a better understanding of peace and conflict processes. Users are invited to explore the relationship of various variables and their decisive roles in such processes. Full article

Creating as-built plans of building interiors is a challenging task. In this paper we present a semi-automatic modelling system for creating residential building interior plans and their integration with existing map data to produce building models. Taking a set of imprecise measurements made with an interactive mobile phone room mapping application, the system performs spatial adjustments in accordance with soft and hard constraints imposed on the building plan geometry. The approach uses an optimisation model that exploits a high accuracy building outline, such as can be found in topographic map data, and the building topology to improve the quality of interior measurements and generate a standardised output. We test our system on building plans of five residential homes. Our evaluation shows that the approach enables construction of accurate interior plans from imprecise measurements. The experiments report an average accuracy of 0.24 m, close to the 0.20 m recommended by the CityGML LoD4 specification. Full article

In this paper, we propose a navigation approach for smartphones that enables visitors of major events to avoid crowded areas or narrow streets and to navigate out of dense crowds quickly. Two types of sensor data are integrated. Real-time optical images acquired and transmitted by an airborne camera system are used to compute an estimation of a crowd density map. For this purpose, a patch-based approach with a Gabor filter bank for texture classification in combination with an interest point detector and a smoothing function is applied. Furthermore, the crowd density is estimated based on location and movement speed of in situ smartphone measurements. This information allows for the enhancement of the overall crowd density layer. The composed density information is input to a least-cost routing workflow. Two possible use cases are presented, namely (i) an emergency application and (ii) a basic routing application. A prototypical implementation of the system is conducted as proof of concept. Our approach is capable of increasing the security level for major events. Visitors are able to avoid dense crowds by routing around them, while security and rescue forces are able to find the fastest way into the crowd. Full article

According to the EU Habitats Directive, heathlands are “natural habitats of community interest”. Heathland management aims at conserving these habitats threatened by various changes, including successional processes leading to forest vegetation. We investigate the dynamics of woody species to the detriment of heathland over a period of 60 years in the Fontainebleau forest and we examine the effects of soil types, soil depth and topography parameters on heathland stability. We assess changes in forest cover between 1946 and 2003 by comparing vegetation maps derived from aerial photographs coupled to GIS analyses. The results show the loss of more than 75% of heathland during 1946–2003 due to tree colonisation of abandoned heathland. We detected differences in the dynamics of colonisation between coniferous and deciduous trees. The colonisation of heathland by coniferous species was faster over the last 20 years of our study period. Tree encroachment was faster in north-facing areas and in areas of acidic luvisols. While this dynamic was very slow in acid sandstone soils, heathland stability was more important in shallow soils on flat and south facing areas. Our study has the potential to assist land managers in selecting those heathland areas that will be easier to conserve and/or to restore by focusing on areas and spatial conditions that prevent forest colonisation and hence favour the long-term stability of heathland. Full article

While free and open source software becomes increasingly important in geospatial research and industry, open science perspectives are generally less reflected in universities’ educational programs. We present an example of how free and open source software can be incorporated into geospatial education to promote open and reproducible science. Since 2008 graduate students at North Carolina State University have the opportunity to take a course on geospatial modeling and analysis that is taught with both proprietary and free and open source software. In this course, students perform geospatial tasks simultaneously in the proprietary package ArcGIS and the free and open source package GRASS GIS. By ensuring that students learn to distinguish between geospatial concepts and software specifics, students become more flexible and stronger spatial thinkers when choosing solutions for their independent work in the future. We also discuss ways to continually update and improve our publicly available teaching materials for reuse by teachers, self-learners and other members of the GIS community. Only when free and open source software is fully integrated into geospatial education, we will be able to encourage a culture of openness and, thus, enable greater reproducibility in research and development applications. Full article

The aims of this study were: (i) the mapping of asbestos cement roofs in an urban area; and (ii) the development of a spectral index related to the roof weathering status. Aerial images were collected through the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) sensor, which acquires data in 102 channels from the visible to the thermal infrared spectral range. An image based supervised classification was performed using the Spectral Angle Mapper (SAM) algorithm. The SAM was trained through a set of pixels selected on roofs of different materials. The map showed an average producer’s accuracy (PA) of 86% and a user’s accuracy (UA) of 89% for the asbestos cement class. A novel spectral index, the “Index of Surface Deterioration” (ISD), was defined based on measurements collected with a portable spectroradiometer on asbestos cement roofs that were characterized by different weathering statuses. The ISD was then calculated on the MIVIS images, allowing the distinction of two weathering classes (i.e., high and low). The asbestos cement map was handled in a Geographic Information System (GIS) in order to supply the municipalities with the cadastral references of each property having an asbestos cement roof. This tool can be purposed for municipalities as an aid to prioritize asbestos removal, based on roof weathering status. Full article

Shallow coral reefs threatened by climate change must be spatio-temporally analyzed in terms of their protection of coastal human populations. This study combines Japanese spatio-temporal gradients of population/asset and coral buffering exposure to stress-inducing and stress-mitigating factors so that the socio-economic and ecological (SEE) resilience tied to coral reefscapes can be regionally mapped (1200 km) at a fine resolution (1 arcsec) over a decade (11 years). Fuzzy logic was employed to associated environmental factors based on the related population/asset/coral buffering responses, as found in the literature. Once the factors were weighted according to their resilience contributions, temporally static patterns were evident: (1) a negative correlation occurs between coral buffering resilience and latitude; (2) the least resilient islands are low-lying, deprived of wide reef barriers, and located on the eastern and southern boundaries of the Nansei archipelago; (3) the southwestern-most, middle and northeastern-most islands have the same SEE resilience; and (4) Sekisei Lagoon islands have a very high coral buffering resilience. To overcome uncertainty, future studies should focus on the socio-ecological adaptive capacity, fine-scale ecological processes (such as coral and fish functional groups) and the prediction of the flood risks in the coming decades. Full article

To elucidate a realistic traffic assignment scenario, a multi-criterion decision system is essential. A traffic assignment model designed to simulate real-life situation may therefore utilize absolute and/or relative impedance. Ideally, the decision-making process should identify a set of traffic impedances (factors working against the smooth flow of traffic) along with pertinent parameters in order for the decision system to select the most optimal or the least-impeded route. In this study, we developed geospatial algorithms that consider multiple impedances. The impedances utilized in this study included, traffic patterns, capacity and congestion. The attributes of the decision-making process also prioritize multi-traffic scenarios by adopting first-in-first-out prioritization method. We also further subdivided classical impedance into either relative impedance or absolute impedance. The main advantage of this innovative multi-attribute, impedance-based trip assignment model is that it can be implemented in a manner of algebraic approach to utilize shortest path algorithm embedded in a Geographic Information Systems (GIS)—Graphical User Interface tool. Thus, the GIS package can therefore handle the multi-attribute impedance effectively. Furthermore, the method utilized in this paper displays flexibility and better adaptation to a multi-modal transportation system. Transportation, logistics, and random events, such as terrorism, can be easily analyzed with pertinent impedance. Full article

Non-motorized transportation modes, especially cycling and walking, offer numerous benefits, including improvements in the livability of cities, healthy physical activity, efficient urban transportation systems, less traffic congestion, less noise pollution, clean air, less impact on climate change and decreases in the incidence of diseases related to vehicular emissions. Considering the substantial number of short-distance trips, the time consumed in traffic jams, the higher costs for parking vehicles and restrictions in central business districts, many commuters have found that non-motorized modes of transportation serve as viable and economical transport alternatives. Thus, local governments should encourage and stimulate non-motorized modes of transportation. In return, governments must provide safe conditions for these forms of transportation, and motorized vehicle users must respect and coexist with pedestrians and cyclists, which are the most vulnerable users of the transportation system. Although current trends in sustainable transport aim to encourage and stimulate non-motorized modes of transportation that are socially more efficient than motorized transportation, few to no safety policies have been implemented regarding vulnerable road users (VRU), mainly in large urban centers. Due to the spatial nature of the data used in transport-related studies, geospatial technologies provide a powerful analytical method for studying VRU safety frameworks through the use of spatial analysis. In this article, spatial analysis is used to determine the locations of regions that are characterized by a concentration of traffic accidents (black zones) involving VRU (injuries and casualties) in São Paulo, Brazil (developing country), and Rome, Italy (developed country). The black zones are investigated to obtain spatial patterns that can cause multiple accidents. A method based on kernel density estimation (KDE) is used to compare the two cities and show economic, social, cultural, demographic and geographic differences and/or similarities and how these factors are linked to the locations of VRU traffic accidents. Multivariate regression analyses (ordinary least squares (OLS) models and spatial regression models) are performed to investigate spatial correlations, to understand the dynamics of VRU road accidents in São Paulo and Rome and to detect factors (variables) that contribute to the occurrences of these events, such as the presence of trip generator hubs (TGH), the number of generated urban trips and demographic data. The adopted methodology presents satisfactory results for identifying and delimiting black spots and establishing a link between VRU traffic accident rates and TGH (hospitals, universities and retail shopping centers) and demographic and transport-related data. Full article

Three-dimensional (3D) maps have many potential applications, such as navigation and urban planning. In this article, we present the use of a 3D virtual world platform Meshmoon to create intelligent open data 3D maps. A processing method is developed to enable the generation of 3D virtual environments from the open data of the National Land Survey of Finland. The article combines the elements needed in contemporary smart city concepts, such as the connection between attribute information and 3D objects, and the creation of collaborative virtual worlds from open data. By using our 3D virtual world platform, it is possible to create up-to-date, collaborative 3D virtual models, which are automatically updated on all viewers. In the scenes, all users are able to interact with the model, and with each other. With the developed processing methods, the creation of virtual world scenes was partially automated for collaboration activities. Full article

This article reviews the range of delivery platforms that have been developed for the PySAL open source Python library for spatial analysis. This includes traditional desktop software (with a graphical user interface, command line or embedded in a computational notebook), open spatial analytics middleware, and web, cloud and distributed open geospatial analytics for decision support. A common thread throughout the discussion is the emphasis on openness, interoperability, and provenance management in a scientific workflow. The code base of the PySAL library provides the common computing framework underlying all delivery mechanisms. Full article

The relevance of geographic information to mobile users must be evaluated by taking into account the usage context. This paper assumes that emerging Location-based Social Networks (LBSNs) contain contextual information rich enough to be used in order to contextualize such an evaluation process. This assumption is demonstrated through an exploratory analysis of a Foursquare check-in dataset, which reveals the impacts of two contextual factors—temporal and spatial—on mobility patterns. This paper then proposes an approach that may be used to contextualize the evaluation of geographic information’s relevance. The proposed algorithm links a priori relevance to the contextualized relevance using the hidden impacts of contextual factors. Improved performance from the experiments carried out confirms the validity of the proposed approach, as well as the benefits of utilizing contextual information within the relevance evaluation process. Full article

In this paper we explore relationships between bird species richness and environmental factors in New York State, focusing particularly on how spatial scale, autocorrelation and nonstationarity affect these relationships. We used spatial statistics, Getis-Ord G_i*(d), to investigate how spatial scale affects the measurement of richness “hot-spots” and “cold-spots” (clusters of high and low species richness, respectively) and geographically weighted regression (GWR) to explore scale dependencies and nonstationarity in the relationships between richness and environmental variables such as climate and plant productivity. Finally, we introduce a geovisualization approach to show how these relationships are affected by spatial scale in order to understand the complex spatial patterns of species richness. Full article

As a consequence of increasing safety concerns, camera surveillance has been widely adopted as a way to monitor public spaces. One of the major challenges of camera surveillance is to design an optimal method for camera network placement in order to ensure the greater possible coverage. In addition, this method must consider the landscape of the monitored environment to take into account the existing objects that may influence the deployment of such a network. In this paper, a new Voronoi-based 3D GIS oriented approach named “HybVOR” is proposed for surveillance camera network placement. The “HybVOR” approach aims to achieve a coverage near 100% through three main phases. First, a Voronoi Diagram from buildings’ footprints is generated and cameras are placed on the Voronoi Edges. Second, the level of coverage is assessed by calculating a viewshed based on a raster Digital Surface Model of the region of interest. Finally, the visibility of the main buildings’ entrances is evaluated based on a 3D vector model that contains these features. The effectiveness of the “HybVOR” approach is demonstrated through a case study that corresponds to an area of interest in Jeddah Seaport in the Kingdom of Saudi Arabia. Full article

People with disabilities face many obstacles in everyday outdoor travels. One of the most notable obstacles is steep slope on sidewalk segments. Current navigation systems/services do not all support map databases with slope attributes and cannot calculate sidewalk slope in real time. In this paper, we present a technique for calculating slopes of sidewalk segments by image data and predict the most suitable route for each individual user through integration with GPS trajectory. In our technique we make use of GPS trajectory data, to identify the sidewalk segment on which the traveler will most probably pass, and images of the identified sidewalk segment. Through edge detection techniques we detect edges of objects, such as buildings, billboards, and walls, in the background. Slope of the segment is then calculated by comparing its line representation in the map with the detected edges. Our experiment result indicates effective calculation of sidewalk slopes. Full article

The house crow (Corvus splendens), a native of the Indian subcontinent, has shown a rapid expansion of habitat range across Eastern Africa, the Arabian Peninsula, Europe and Asia. It is an adaptable, gregarious commensal bird which is regarded globally as an important pest species due to its impacts on livestock, agricultural and horticultural crops and indigenous fauna and as a fecal contaminator of human environments and water resources. Two Maxent (v3.3.3k) models (A) with presence data in Australia and (B) with simulated entry data locations in New Zealand) and a third ArcGIS model (C) with environmental and social layers) are used to determine an overall suitability index and establish a niche-based model of the potential spatial distribution for C. splendens within New Zealand. The results show that New Zealand, particularly the northern regions of North Island, has suitable environments for the establishment of the house crow. In order of suitability Model B showed highest potential land area suitability (31.84%) followed by Model A (13.79%) and Model C (10.89%). The potential for further expansion of this bird’s invasive range is high and, if New Zealand is invaded, impacts are likely to be significant. Full article

In this work we present preliminary results regarding a proof-of-concept project which aims to provide tools for mapping the amount of solar radiation reaching surfaces of objects, accounting for obstructions between objects themselves. The implementation uses the NASA World Wind development platform (NASA WW) to model the different physical phenomena that participate in the process, from the calculation of the Sun’s position relative to the area that is being considered, to the interaction between atmosphere and solid obstructions, e.g., terrain or buildings. A more complete understanding of the distribution of energy from the Sun illuminating elements on the Earth’s surface adds value to applications ranging from planning the renewable energy potential of an area to ecological analyses. Full article

The advances in open data, free and open source software solutions and open access to research publications have influenced the emergence of open educational resources (OER) initiatives. These initiatives permit access to openly licensed learning resources including courses, webinars, training materials and textbooks. Thereby, an increasing number of users has the opportunity to broaden their knowledge and gain new skills. The goal of this paper is to evaluate open education initiatives in the geospatial domain and its synergies with open spatial data and software movements. The paper is focusing on the Massive Open Online Course (MOOCs) movement. The advantages and challenges of open geospatial education will be thoroughly discussed. Full article

Earth observation and monitoring of soil quality, long term changes of soil characteristics and deterioration processes such as degradation or desertification are among the most important objectives of remote sensing. The georeferenciation of such information contributes to the development and progress of the Digital Earth project in the framework of the information globalization process. Earth observation and soil quality monitoring via remote sensing are mostly based on the use of satellite spectral data. Advanced techniques are available to predict the soil or land use/cover categories from satellite imagery data. Artificial Neural Networks (ANNs) are among the most widely used tools for modeling and prediction purposes in various fields of science. The assessment of satellite image quality and suitability for analysing the soil conditions (e.g., soil classification, land use/cover estimation, etc.) is fundamental. In this paper, methodology for data screening and subsequent application of ANNs in remote sensing is presented. The first stage is achieved via: (i) elimination of outliers, (ii) data pre-processing and (iii) the determination of the number of distinguishable soil “classes” via Eigenvalues Analysis (EA) and Principal Components Analysis (PCA). The next stage of ANNs use consists of: (i) building the training database, (ii) optimization of ANN architecture and database cleaning, and (iii) training and verification of the network. Application of the proposed methodology is shown. Full article

Borderland regions are special areas and deserve more attention in global sustainable development. Reliable geo-information and effective analysis tools are requested to support borderlands studies through the integrated utilization of geospatial analysis, web service, as well as the other domain-specific expertise. This paper has reviewed the state-of-the-art of geospatial information sciences, (GIS)-based borderlands modeling, and understanding. From the perspective of GIS, integrated data modeling, comprehensive analysis, and collaborative information service are identified as the three major challenges in this filed. A research agenda is further proposed with four topics, i.e., classification and representation of borderland information, derivation of neighborhood information, development of synergetic analysis, and design and development of a geo-portal for borderlands studies. This interdisciplinary study requires a closer and in-depth collaboration of geopolitics, international relation, geography and geo-spatial information sciences. Full article

The identification of appropriate mechanisms for process sharing and reuse by means of composition is considered a key enabler for the effective uptake of a global Earth Observation infrastructure, currently pursued by the international geospatial research community. Modelers in need of running complex workflows may benefit from outsourcing process composition to a dedicated external service, according to the brokering approach. This work introduces our architecture of a process broker, as a distributed information system for creating, validating, editing, storing, publishing and executing geospatial-modeling workflows. The broker provides a service framework for adaptation, reuse and complementation of existing processing resources (including models and geospatial services in general) in the form of interoperable, executable workflows. The described solution has been experimentally applied in several use scenarios in the context of EU-funded projects and the Global Earth Observation System of Systems. Full article

This study evaluates the potential of airborne remote sensing images to detect water stress in maize. Visible and near infrared CASI (Itres Research Ltd., Calgary, AL, Canada) and thermal AHS-160 (Sensytech Inc., Beverly, MA, USA) data were acquired at three different times during the day on a maize field (Zea mays L.) grown with three different irrigation treatments. An intensive field campaign was also conducted concurrently with image acquisition to measure leaf ecophysiological parameters and the leaf area index. The analysis of the field data showed that maize plants were experiencing moderate to severe water stress in rainfed plots and a weaker stress condition in the plots with a water deficit imposed between stem elongation and flowering. Vegetation indices including the normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI) computed from the CASI images, sun-induced chlorophyll fluorescence (F₇₆₀) and canopy temperature (Tc) showed different performances in describing the water stress during the day. During the morning overpass, NDVI was the index with the highest discriminant power due to the sensitivity of NDVI to maize canopy structure, affected by the water irrigation treatment. As the day progressed, processes related to heat dissipation through plant transpiration became more and more important and at midday Tc showed the best performances. Furthermore, Tc retrieved from the midday image was the only index able to distinguish all the three classes of water status. Finally, during the afternoon, PRI and F₇₆₀ showed the best performances. These results demonstrate the feasibility to detect water stress using thermal and optical airborne data, pointing out the importance of careful planning of the airborne surveys as a function of the specific aims of the study. Full article

In an effort to reforest school sites with limited resources, communities and non-profits have implemented projects on Los Angeles Unified School District (LAUSD) school sites, often without thought for the best location, long-term maintenance, or appropriateness of the tree type. Although studies exist related to sun safety policies in schools, there has been little emphasis on the environmental public health benefits of trees in public schools. The LAUSD School Shade Tree Canopy Study was a response to this issue in which data was analyzed (a total of 33,729 trees in the LAUSD were mapped) regarding tree canopy coverage, pervious/impervious areas, and buildings for 509 elementary schools to assess urban forestry management issues and environmental injustices within communities of the district. The results of these analyses indicate that there is a wide range of school site size, tree canopy coverage as a percentage of school site size, tree canopy coverage as a percentage of play area, and percentage of unpaved surface play areas (e.g., (~20%) of the schools have both (0.0%) tree canopy coverage play areas and 100% paved surfaces). This finding alone has implications in how the LAUSD may implement sun safe polices which would aid in preventing skin cancer and other adverse health outcomes for students within the school district. Full article

By applying visual analytics techniques to vehicle traffic data, we found a way to visualize and study the relationships between the traffic intensity and movement speed on links of a spatially abstracted transportation network. We observed that the traffic intensities and speeds in an abstracted network are interrelated in the same way as they are in a detailed street network at the level of street segments. We developed interactive visual interfaces that support representing these interdependencies by mathematical models. To test the possibility of utilizing them for performing traffic simulations on the basis of abstracted transportation networks, we devised a prototypical simulation algorithm employing these dependency models. The algorithm is embedded in an interactive visual environment for defining traffic scenarios, running simulations, and exploring their results. Our research demonstrates a principal possibility of performing traffic simulations on the basis of spatially abstracted transportation networks using dependency models derived from real traffic data. This possibility needs to be comprehensively investigated and tested in collaboration with transportation domain specialists. Full article

Geographical masks are a group of location protection methods for the dissemination and publication of confidential and sensitive information, such as health- and crime-related geo-referenced data. The use of such masks ensures that privacy is protected for the individuals involved in the datasets. Nevertheless, the protection process introduces spatial error to the masked dataset. This study quantifies the spatial error of masked datasets using two approaches. First, a perceptual survey was employed where participants ranked the similarity of a diverse sample of masked and original maps. Second, a spatial statistical analysis was performed that provided quantitative results for the same pairs of maps. Spatial statistical similarity is calculated with three divergence indices that employ different spatial clustering methods. All indices are significantly correlated with the perceptual similarity. Finally, the results of the spatial analysis are used as the explanatory variable to estimate the perceptual similarity. Three prediction models are created that indicate upper boundaries for the spatial statistical results upon which the masked data are perceived differently from the original data. The results of the study aim to help potential “maskers” to quantify and evaluate the error of confidential masked visualizations. Full article

Remotely sensed images are important sources of information for a range of spatial problems. Air photo interpretation emerged as a discipline in response to the need to develop a systematic method for analysis of reconnaissance photographs during World War I. Remote sensing research has focused on the development of automated methods of image analysis, shifting focus away from human interpretation processes. However, automated methods are far from perfect and human interpretation remains an important component of image analysis. One important source of information concerning human image interpretation process is textual guides written within the discipline. These early texts put more emphasis than more recent texts, on the details of the interpretation process, the role of the human in the process, and the cognitive skills involved. In the research reported here, we use content analysis to evaluate the discussion of air photo interpretation in historical texts published between 1922 and 1960. Results indicate that texts from this period emphasized the documentation of relationships between perceptual cues and images features of common interest while reasoning skill and knowledge were discussed less so. The results of this analysis provide a framework of expert image skills needed to perform image interpretation tasks. The framework is useful for informing the design of semi-automated tools for performing analysis. Full article

OpenStreetMap (OSM) constitutes an unprecedented, free, geographical information source contributed by millions of individuals, resulting in a database of great volume and heterogeneity. In this study, we characterize the heterogeneity of the entire OSM database and historical archive in the context of big data. We consider all users, geographic elements and user contributions from an eight-year data archive, at a size of 692 GB. We rely on some nonlinear methods such as power law statistics and head/tail breaks to uncover and illustrate the underlying scaling properties. All three aspects (users, elements, and contributions) demonstrate striking power laws or heavy-tailed distributions. The heavy-tailed distributions imply that there are far more small elements than large ones, far more inactive users than active ones, and far more lightly edited elements than heavy-edited ones. Furthermore, about 500 users in the core group of the OSM are highly networked in terms of collaboration. Full article

To improve decision making, real-time population density must be known. However, calculating the point density of a huge dataset in real time is impractical in terms of processing time. Accordingly, a fast algorithm for estimating the distribution of the density of moving points is proposed. The algorithm, which is based on variational Bayesian estimation, takes a parametric approach to speed up the estimation process. Although the parametric approach has a drawback, that is the processes to be carried out on the server are very slow, the proposed algorithm overcomes the drawback by using the result of an estimation of an adjacent past density distribution. Full article

The visual analysis of complex geo-spatial data is a challenging task. Typically, different views are used to communicate different aspects. With changing topics of interest, however, novel views are required. This leads to dynamically changing presentations of multiple views. This paper introduces a novel approach to support such scenarios. It allows for a spontaneous incorporation of views from different sources and to automatically layout these views in a multi-display environment. Furthermore, we introduce an enhanced undo/redo mechanism for this setting, which records user interactions and, in this way, enables swift reconfigurations of displayed views. Hence, users can fluently switch the focus of visual analysis without extensive manual interactions. We demonstrate our approach by the particular use case of discussing geo-spatial climate data. Full article

Graphs have become ubiquitous structures to encode geographic knowledge online. The Semantic Web’s linked open data, folksonomies, wiki websites and open gazetteers can be seen as geo-knowledge graphs, that is labeled graphs whose vertices represent geographic concepts and whose edges encode the relations between concepts. To compute the semantic similarity of concepts in such structures, this article defines the network-lexical similarity measure (NLS). This measure estimates similarity by combining two complementary sources of information: the network similarity of vertices and the semantic similarity of the lexical definitions. NLS is evaluated on the OpenStreetMap Semantic Network, a crowdsourced geo-knowledge graph that describes geographic concepts. The hybrid approach outperforms both network and lexical measures, obtaining very strong correlation with the similarity judgments of human subjects. Full article