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1.
  • Jia, Tao, et al. (författare)
  • Exploring human activity patterns using taxicab static points
  • 2012
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 1:1, s. 89-107
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper explores the patterns of human activities within a geographical space by adopting the taxicab static points which refer to the locations with zero speed along the tracking trajectory. We report the findings from both aggregated and individual aspects. Results from the aggregated level indicate the following: (1) Human activities exhibit an obvious regularity in time, for example, there is a burst of activity during weekend nights and a lull during the week. (2) They show a remarkable spatial drifting pattern, which strengthens our understanding of the activities in any given place. (3) Activities are heterogeneous in space irrespective of their drifting with time. These aggregated results not only help in city planning, but also facilitate traffic control and management. On the other hand, investigations on an individual level suggest that (4) activities witnessed by one taxicab will have different temporal regularity to another, and (5) each regularity implies a high level of prediction with low entropy by applying the Lempel-Ziv algorithm.
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2.
  • Liu, Xintao, et al. (författare)
  • Uncovering Spatio-Temporal Cluster Patterns Using Massive Floating Car Data
  • 2013
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 2:2, s. 371-384
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper, we explore spatio-temporal clusters using massive floating car data from a complex network perspective. We analyzed over 85 million taxicab GPS points (floating car data) collected in Wuhan, Hubei, China. Low-speed and stop points were selected to generate spatio-temporal clusters, which indicated the typical stop-and-go movement pattern in real-world traffic congestion. We found that the sizes of spatio-temporal clusters exhibited a power law distribution. This implies the presence of a scaling property; i.e., they can be naturally divided into a strong hierarchical structure: long time-duration ones (a low percentage) whose values lie above the mean value and short ones (a high percentage) whose values lie below. The spatio-temporal clusters at different levels represented the degree of traffic congestions, for example the higher the level, the worse the traffic congestions. Moreover, the distribution of traffic congestions varied spatio-temporally and demonstrated a multinuclear structure in urban road networks, which suggested there is a correlation to the corresponding internal mobile regularities of an urban system.
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3.
  • Abrate, Matteo, et al. (författare)
  • Geomemories - A Platform for Visualizing Historical, Environmental and Geospatial Changes of the Italian Landscape
  • 2013
  • Ingår i: ISPRS International Journal of Geo-Information. Special issue: Geospatial Monitoring and Modelling of Environmental Change. - : MDPI - Open Access Publishing. - 2220-9964. ; 2:2, s. 432-455
  • Tidskriftsartikel (refereegranskat)abstract
    • The GeoMemories project aims at publishing on the Web and digitally preserving historical aerial photographs that are currently stored in physical form within the archives of the Aerofototeca Nazionale in Rome. We describe a system, available at http://www.geomemories.org, that lets users visualize the evolution of the Italian landscape throughout the last century. The Web portal allows comparison of recent satellite imagery with several layers of historical maps, obtained from the aerial photos through a complex workflow that merges them together. We present several case studies carried out in collaboration with geologists, historians and archaeologists, that illustrate the great potential of our system in different research fields. Experiments and advances in image processing technologies are envisaged as a key factor in solving the inherent issue of vast amounts of manual work, from georeferencing to mosaicking to analysis.
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4.
  • Adamiak, Czeslaw, et al. (författare)
  • Airbnb Offer in Spain-Spatial Analysis of the Pattern and Determinants of Its Distribution
  • 2019
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 8:3
  • Tidskriftsartikel (refereegranskat)abstract
    • The rising number of homes and apartments rented out through Airbnb and similar peer-to-peer accommodation platforms cause concerns about the impact of such activity on the tourism sector and property market. To date, spatial analysis on peer-to-peer rental activity has been usually limited in scope to individual large cities. In this study, we take into account the whole territory of Spain, with special attention given to cities and regions with high tourist activity. We use a dataset of about 250 thousand Airbnb listings in Spain obtained from the Airbnb webpage, aggregate the numbers of these offers in 8124 municipalities and 79 tourist areas/sites, measure their concentration, spatial autocorrelation, and develop regression models to find the determinants of Airbnb rentals' distribution. We conclude that apart from largest cities, Airbnb is active in holiday destinations of Spain, where it often serves as an intermediary for the rental of second or investment homes and apartments. The location of Airbnb listings is mostly determined by the supply of empty or secondary dwellings, distribution of traditional tourism accommodation, coastal location, and the level of internationalization of tourism demand.
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5.
  • Ahmed, Bayes, et al. (författare)
  • Urban Morphological Change Analysis of Dhaka City, Bangladesh, Using Space Syntax
  • 2014
  • Ingår i: ISPRS International journal of geo-information. - Basel : MDPI AG. - 2220-9964. ; 3:4, s. 1412-1444
  • Tidskriftsartikel (refereegranskat)abstract
    • This article is based on a study of the morphological changes of Dhaka City, the capital of Bangladesh. The main objective of the research is to study the transformation of urban morphology in Dhaka City from 1947 to 2007. Three sample wards (18, 19 and 72) of Dhaka City Corporation are strategically selected as the study areas. Ward 72 has an indigenous type of organic settlement, whereas ward 19 is a planned area, and ward 18 represents a mixed (both planned and informal) type of settlement. In this research, the transformation of urban settlement pattern is examined through space syntax. The results show that the organic settlements (ward 72) are highly integrated both in terms of the local and global syntactic measures (lowest standard deviation for local and global integration, with the highest intelligibility values), and are more connectivity. The scenario is opposite in the case of planned settlements. The characteristics of mixed areas (ward 18) lie in between the organic and planned settlements. Therefore, in summary, it can be stated that the integration, connectivity and intelligibility measures of Dhaka City are found to be high, medium and low for the indigenous, mixed and planned settlement types; respectively.
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6.
  • Berg, Håkan, et al. (författare)
  • A GIS Assessment of the Suitability of Tilapia and Clarias Pond Farming in Tanzania
  • 2021
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 10:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Aquaculture production in Tanzania has increased in recent years, responding to an increased demand for fish, but the scale and productivity of smallholder aquaculture remains below the level needed to support significant sector growth in Tanzania. This study assesses, through geospatial analyses, the suitability for freshwater pond farming of Oreochromis niloticus and Clarias gariepinus in Tanzania, by assessing the geographical distribution of seven criteria (water availability, water temperature, soil texture, terrain slope, availability of farm inputs, potential farm-gate sales, and access to local markets) identified as important for fish pond farming. The criteria were developed and standardized from 15 sub-criteria, which were classified into a four-level suitability scale based on physical scores. The individual weights of the different criteria in the overall GIS suitability assessment were determined through a multi-criteria evaluation. The final results were validated and compared through field observations, interviews with 89 rural and 11 urban aquaculture farmers, and a questionnaire survey with 16 regional fisheries officers. Our results indicate that there is a good potential for aquaculture in Tanzania. Almost 60% of Tanzania is assessed as being suitable and 40% as moderately suitable for small-scale subsistence pond farming, which is the dominating fish farming practice currently. The corresponding figures for medium-scale commercial farming, which many regions expect to be the dominating farming method within ten-years, were 52% and 47% respectively. The availability of water was the most limiting factor for fish pond farming, which was confirmed by both farmers and regional fisheries officers, and assessed as being suitable in only 28% of the country. The availability of farm-gate sales and local markets were moderate suitable to suitable and were seen as a constraint for commercial farms in rural areas. The availability of farm inputs (agriculture waste and manure) was overall good (26% very suitable and 32% suitable), but high-quality fish feed was seen as a constraint to aquaculture development, both by farmers and regional fisheries officers. Soil, terrain, and water temperature conditions were assessed as good, especially at low altitudes and in regions close to the sea and south of Lake Victoria.
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7.
  • Bhatt, Mehul, Professor, 1980-, et al. (författare)
  • Geospatial Narratives and Their Spatio-Temporal Dynamics : Commonsense Reasoning for High-Level Analyses in Geographic Information Systems
  • 2014
  • Ingår i: ISPRS International Journal of Geo-Information. - Basel : MDPI AG. - 2220-9964. ; 3:1, s. 166-205
  • Tidskriftsartikel (refereegranskat)abstract
    • The modeling, analysis and visualization of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about space, events, actions and change. With this as a basis and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solution techniques chiefly involving qualitative abstraction, data integration and spatial consistency and practical geospatial abduction.
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8.
  • Boloorani, Ali Darvishi, et al. (författare)
  • Post-War Urban Damage Mapping Using InSAR : The Case of Mosul City in Iraq
  • 2021
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 10:3
  • Tidskriftsartikel (refereegranskat)abstract
    •  Urban infrastructures have become imperative to human life. Any damage to these infrastructures as a result of detrimental activities would accrue huge economical costs and severe casualties. War in particular is a major anthropogenic calamity with immense collateral effects on the social and economic fabric of human nations. Therefore, damaged buildings assessment plays a prominent role in post-war resettlement and reconstruction of urban infrastructures. The data-analysis process of this assessment is essential to any post-disaster program and can be carried out via different formats. Synthetic Aperture Radar (SAR) data and Interferometric SAR (InSAR) techniques help us to establish a reliable and fast monitoring system for detecting post-war damages in urban areas. Along this thread, the present study aims to investigate the feasibility and mode of implementation of Sentinel-1 SAR data and InSAR techniques to estimate post-war damage in war-affected areas as opposed to using commercial high-resolution optical images. The study is presented in the form of a survey to identify urban areas damaged or destroyed by war (Islamic State of Iraq and the Levant, ISIL, or ISIS occupation) in the city of Mosul, Iraq, using Sentinel-1 (S1) data over the 2014–2017 period. Small BAseline Subset (SBAS), Persistent Scatterer Interferometry (PSI) and coherent-intensity-based analysis were also used to identify war-damaged buildings. Accuracy assessments for the proposed SAR-based mapping approach were conducted by comparing the destruction map to the available post-war destruction map of United Nations Institute for Training and Research (UNITAR); previously developed using optical very high-resolution images, drone imagery, and field visits. As the findings suggest, 40% of the entire city, the western sectors, especially the Old City, were affected most by ISIS war. The findings are also indicative of the efficiency of incorporating Sentinel-1 SAR data and InSAR technique to map post-war urban damages in Mosul. The proposed method could be widely used as a tool in damage assessment procedures in any post-war reconstruction programs.
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9.
  • Borg, Anton, et al. (författare)
  • All Burglaries Are Not the Same : Predicting Near-Repeat Burglaries in Cities Using Modus Operandi
  • 2022
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI. - 2220-9964. ; 11:3
  • Tidskriftsartikel (refereegranskat)abstract
    • The evidence that burglaries cluster spatio-temporally is strong. However, research is unclear on whether clustered burglaries (repeats/near-repeats) should be treated as qualitatively different crimes compared to spatio-temporally unrelated burglaries (non-repeats). This study, therefore, investigated if there were differences in modus operandi-signatures (MOs, the habits and methods employed by criminals) between near-repeat and non-repeat burglaries across 10 Swedish cities, as well as whether MO-signatures can aid in predicting if a burglary is classified as a nearrepeat or a non-repeat crime. Data consisted of 5744 residential burglaries, with 137 MO features characterizing each case. Descriptive data of repeats/non-repeats is provided together with Wilcoxon tests of MO-differences between crime pairs, while logistic regressions were used to train models to predict if a crime scene was classified as a near-repeat or a non-repeat crime. Near-repeat crimes were rather stylized, showing heterogeneity in MOs across cities, but showing homogeneity within cities at the same time, as there were significant differences between near-repeat and non-repeat burglaries, including subgroups of features, such as differences in mode of entering, target selection, types of goods stolen, as well the traces that were left at the crime scene. Furthermore, using logistic regression models, it was possible to predict near-repeat and non-repeat crimes with a mean F1-score of 0.8155 (0.0866) based on the MO. Potential policy implications are discussed in terms of how data-driven procedures can facilitate analysis of spatio-temporal phenomena based on the MO-signatures of offenders, as well as how law enforcement agencies can provide differentiated advice and response when there is suspicion that a crime is part of a series as opposed to an isolated event. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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10.
  • Cumbane, Silvino Pedro, et al. (författare)
  • Review of Big Data and Processing Frameworks for Disaster Response Applications
  • 2019
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 8:9
  • Tidskriftsartikel (refereegranskat)abstract
    • Natural hazards result in devastating losses in human life, environmental assets and personal, and regional and national economies. The availability of different big data such as satellite imageries, Global Positioning System (GPS) traces, mobile Call Detail Records (CDRs), social media posts, etc., in conjunction with advances in data analytic techniques (e.g., data mining and big data processing, machine learning and deep learning) can facilitate the extraction of geospatial information that is critical for rapid and effective disaster response. However, disaster response systems development usually requires the integration of data from different sources (streaming data sources and data sources at rest) with different characteristics and types, which consequently have different processing needs. Deciding which processing framework to use for a specific big data to perform a given task is usually a challenge for researchers from the disaster management field. Therefore, this paper contributes in four aspects. Firstly, potential big data sources are described and characterized. Secondly, the big data processing frameworks are characterized and grouped based on the sources of data they handle. Then, a short description of each big data processing framework is provided and a comparison of processing frameworks in each group is carried out considering the main aspects such as computing cluster architecture, data flow, data processing model, fault-tolerance, scalability, latency, back-pressure mechanism, programming languages, and support for machine learning libraries, which are related to specific processing needs. Finally, a link between big data and processing frameworks is established, based on the processing provisioning for essential tasks in the response phase of disaster management.
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11.
  • Cumbane, Silvino Pedro, et al. (författare)
  • Spatial Distribution of Displaced Population Estimated Using Mobile Phone Data to Support Disaster Response Activities
  • 2021
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 10:6, s. 421-
  • Tidskriftsartikel (refereegranskat)abstract
    • Under normal circumstances, people's homes and work locations are given by their addresses, and this information is used to create a disaster management plan in which there are instructions to individuals on how to evacuate. However, when a disaster strikes, some shelters are destroyed, or in some cases, distance from affected areas to the closest shelter is not reasonable, or people have no possibility to act rationally as a natural response to physical danger, and hence, the evacuation plan is not followed. In each of these situations, people tend to find alternative places to stay, and the evacuees in shelters do not represent the total number of the displaced population. Knowing the spatial distribution of total displaced people (including people in shelters and other places) is very important for the success of the response activities which, among other measures, aims to provide for the basic humanitarian needs of affected people. Traditional methods of people displacement estimation are based on population surveys in the shelters. However, conducting a survey is infeasible to perform at scale and provides low coverage, i.e., can only cover the numbers for the population that are at the shelters, and the information cannot be delivered in a timely fashion. Therefore, in this research, anonymized mobile Call Detail Records (CDRs) are proposed as a source of information to infer the spatial distribution of the displaced population by analyzing the variation of home cell-tower for each anonymized mobile phone subscriber before and after a disaster. The effectiveness of the proposed method is evaluated using remote-sensing-based building damage assessment data and Displacement Tracking Matrix (DTM) from an individual's questionnaire survey conducted after a severe cyclone in Beira city, central Mozambique, in March 2019. The results show an encouraging correlation coefficient (over 70%) between the number of arrivals in each neighborhood estimated using CDRs and from DTM. In addition to this, CDRs derive spatial distribution of displaced populations with high coverage of people, i.e., including not only people in the shelter but everyone who used a mobile phone before and after the disaster. Moreover, results suggest that if CDRs data are available right after a disaster, population displacement can be estimated, and this information can be used for response activities and hence contribute to reducing waterborne diseases (e.g., diarrheal disease) and diseases associated with crowding (e.g., acute respiratory infections) in shelters and host communities.
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12.
  • Ding, Linfang, et al. (författare)
  • A Framework Uniting Ontology-Based Geodata Integration and Geovisual Analytics
  • 2020
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI. - 2220-9964. ; 9:8
  • Tidskriftsartikel (refereegranskat)abstract
    • In a variety of applications relying on geospatial data, getting insights into heterogeneous geodata sources is crucial for decision making, but often challenging. The reason is that it typically requires combining information coming from different sources via data integration techniques, and then making sense out of the combined data via sophisticated analysis methods. To address this challenge we rely on two well-established research areas: data integration and geovisual analytics, and propose to adopt an ontology-based approach to decouple the challenges of data access and analytics. Our framework consists of two modules centered around an ontology: (1) an ontology-based data integration (OBDI) module, in which mappings specify the relationship between the underlying data and a domain ontology; (2) a geovisual analytics (GeoVA) module, designed for the exploration of the integrated data, by explicitly making use of standard ontologies. In this framework, ontologies play a central role by providing a coherent view over the heterogeneous data, and by acting as a mediator for visual analysis tasks. We test our framework in a scenario for the investigation of the spatiotemporal patterns of meteorological and traffic data from several open data sources. Initial studies show that our approach is feasible for the exploration and understanding of heterogeneous geospatial data.
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13.
  • El-Mekawy, Mohamed, et al. (författare)
  • A Unified Building Model for 3D Urban GIS
  • 2012
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 1:2, s. 120-145
  • Tidskriftsartikel (refereegranskat)abstract
    • Several tasks in urban and architectural design are today undertaken in a geospatial context. Building Information Models (BIM) and geospatial technologies offer 3D data models that provide information about buildings and the surrounding environment. The Industry Foundation Classes (IFC) and CityGML are today the two most prominent semantic models for representation of BIM and geospatial models respectively. CityGML has emerged as a standard for modeling city models while IFC has been developed as a reference model for building objects and sites. Current CAD and geospatial software provide tools that allow the conversion of information from one format to the other. These tools are however fairly limited in their capabilities, often resulting in data and information losses in the transformations. This paper describes a new approach for data integration based on a unified building model (UBM) which encapsulates both the CityGML and IFC models, thus avoiding translations between the models and loss of information. To build the UBM, all classes and related concepts were initially collected from both models, overlapping concepts were merged, new objects were created to ensure the capturing of both indoor and outdoor objects, and finally, spatial relationships between the objects were redefined. Unified Modeling Language (UML) notations were used for representing its objects and relationships between them. There are two use-case scenarios, both set in a hospital: evacuation and allocating spaces for patient wards were developed to validate and test the proposed UBM data model. Based on these two scenarios, four validation queries were defined in order to validate the appropriateness of the proposed unified building model. It has been validated, through the case scenarios and four queries, that the UBM being developed is able to integrate CityGML data as well as IFC data in an apparently seamless way. Constraints and enrichment functions are used for populating empty database tables and fields. The motivation scenarios also show the needs and benefits of having an integrated approach to the modeling of indoor and outdoor spatial features.
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14.
  • Eriksson, Helen, et al. (författare)
  • Versioning of 3D city models for municipality applications : Needs, obstacles and recommendations
  • 2021
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 10:2
  • Tidskriftsartikel (refereegranskat)abstract
    • The use of 3D city models is changing from visualization to complex use cases where they act as 3D base maps. This requires links to registers and continuous updating of the city models. Still, most models never change or are recreated instead of updated. This study identifies obstacles to version management of 3D city models and proposes recommendations to overcome them, with a main focus on the municipality perspective, foremost in the planning and building processes. As part of this study, we investigate whether national building registers can control the version management of 3D city models. A case study based on investigations of standards, interviews and a review of tools is presented. The study uses an architectural model divided into four layers: data collection, building theme, city model and application. All layers require changes when implementing a new versioning method: the data collection layer requires restructuring of technical solutions and work processes, storage of the national building register requires restructuring, versioning capabilities must be propagated to the city model layer, and tools at the application layer must handle temporal information better. Strong incentives for including versioning in 3D city models are essential, as substantial investment is required to implement versioning in all the layers. Only capabilities required by applications should be implemented, as the complexity grows with the number of versioning functionalities. One outcome of the study is a recommendation to link 3D city models more closely to building registers. This enables more complex use in, e.g., building permits and 3D cadastres, and authorities can fetch required (versioning) information directly from the city model layer.
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15.
  • Farnaghi, Mahdi, et al. (författare)
  • Multi-Agent Planning for Automatic Geospatial Web Service Composition in Geoportals
  • 2018
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 7:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Automatic composition of geospatial web services increases the possibility of taking full advantage of spatial data and processing capabilities that have been published over the internet. In this paper, a multi-agent artificial intelligence (AI) planning solution was proposed, which works within the geoportal architecture and enables the geoportal to compose semantically annotated Open Geospatial Consortium (OGC) Web Services based on users’ requirements. In this solution, the registered Catalogue Service for Web (CSW) services in the geoportal along with a composition coordinator component interact together to synthesize Open Geospatial Consortium Web Services (OWSs) and generate the composition workflow. A prototype geoportal was developed, a case study of evacuation sheltering was implemented to illustrate the functionality of the algorithm, and a simulation environment, including one hundred simulated OWSs and five CSW services, was used to test the performance of the solution in a more complex circumstance. The prototype geoportal was able to generate the composite web service, based on the requested goals of the user. Additionally, in the simulation environment, while the execution time of the composition with two CSW service nodes was 20 s, the addition of new CSW nodes reduced the composition time exponentially, so that with five CSW nodes the execution time reduced to 0.3 s. Results showed that due to the utilization of the computational power of CSW services, the solution was fast, horizontally scalable, and less vulnerable to the exponential growth in the search space of the AI planning problem.
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16.
  • Ghaemi, Zeinab, et al. (författare)
  • A Varied Density-based Clustering Approach for Event Detection from Heterogeneous Twitter Data
  • 2019
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 8:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Extracting the latent knowledge from Twitter by applying spatial clustering on geotagged tweets provides the ability to discover events and their locations. DBSCAN (density-based spatial clustering of applications with noise), which has been widely used to retrieve events from geotagged tweets, cannot efficiently detect clusters when there is significant spatial heterogeneity in the dataset, as it is the case for Twitter data where the distribution of users, as well as the intensity of publishing tweets, varies over the study areas. This study proposes VDCT (Varied Density-based spatial Clustering for Twitter data) algorithm that extracts clusters from geotagged tweets by considering spatial heterogeneity. The algorithm employs exponential spline interpolation to determine different search radiuses for cluster detection. Moreover, in addition to spatial proximity, textual similarities among tweets are also taken into account by the algorithm. In order to examine the efficiency of the algorithm, geotagged tweets collected during a hurricane in the United States were used for event detection. The output clusters of VDCT have been compared to those of DBSCAN. Visual and quantitative comparison of the results proved the feasibility of the proposed method. View Full-Text
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17.
  • Guldåker, Nicklas, et al. (författare)
  • Crime Prevention Based on the Strategic Mapping of Living Conditions
  • 2021
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 10 (11):719, s. 1-16
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents a theoretically and methodologically grounded GIS-based model for the measurement and mapping of an index of living conditions in urban residential areas across Sweden. Further, the model is compared and evaluated using the Swedish Police’s assessment of crime-exposed areas. The results indicate that the geographically measured vulnerable living conditions overlap to a large extent with the areas assessed to be crime-exposed by the Swedish Police. Over 61% of the police-defined crime-exposed areas are characterized by vulnerable living conditions. The results also show that this overlap is not perfect and that there are vulnerable areas that are not included in the police’s assessment of crime-exposed areas, but which are nonetheless characterized by vulnerable living conditions that could negatively affect the development of crime. It is also proposed that the model and the mapped index of living conditions can provide a more well-grounded scientific basis for the police’s assessment work. As a first step, the Swedish police have implemented the model and the mapped index in the work process employed in their annual identification of crime-exposed or at-risk areas. In addition to assisting the police, the model and the mapped index could also be used to support other societal actors working with vulnerable areas.
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18.
  • Guldåker, Nicklas (författare)
  • Geovisualization and Geographical Analysis for Fire Prevention
  • 2020
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 9:6, s. 1-19
  • Tidskriftsartikel (refereegranskat)abstract
    • Swedish emergency services still have relatively limited resources and time for proactive fire prevention. Because of this, there is an extensive need for strategic working methods and knowledge to take advantage of spatial analyses. In addition, decision-making based on visualizations and analyses of their own collected data has the potential to increase the validity of strategic decisions. The objective of this paper is to critically examine how some different geovisualization techniques — point data, kernel density and choropleth mapping— actively can complement each other and be applied in fire preventive work. The results show that each technique itself has limitations, but that, in combination, they increase the scope for interpretation and the possibilities of targeting different forms of preventive measures. The investigated geovisualization techniques facilitate various forms of fire prevention such as identifying which areas to prioritize for outreach, home visits, identification and targeting of different risk groups, and customized information campaigns about certain types of fires in risk-prone areas. Furthermore, fairly simple mapping techniques can be utilized directly to evaluate incident reports and increase the quality of geocoded fire incidents. The study also shows how some of these techniques can be applied when analyzing residential fire incidents and their relation to underlying structural and socio-economic factors as well as spatio-temporal dimensions of fire incident data. The spatial analyses and supporting maps can help find and predict risk areas for residential fires or be used directly to formulate hypotheses on fire patterns. The generic functionality of the visualization methods makes them also useful for visual analysis of other types of incidents, such as reported crimes and accidents. Finally, the results are applicable to a work process adapted to the Swedish legislation on confidential data.
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19.
  • Guo, Zijian, et al. (författare)
  • A Vector Field Approach to Estimating Environmental Exposure Using Human Activity Data
  • 2022
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 11:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Environmental exposure of people plays an important role in assessing the quality of human life. The most existing methods that estimate the environmental exposure either focus on the individual level or do not consider human mobility. This paper adopts a vector field generated from the observed locations of human activities to model the environmental exposure at the population level. An improved vector-field-generation method was developed by considering people’s decision-making factors, and we proposed two indicators, i.e., the total exposure indicator (TEI) and the average exposure indicator (AEI), to assess various social groups’ environmental exposure. A case study about the risky environmental exposure of coronavirus disease 2019 (COVID-19) was conducted in Guangzhou, China. Over 900 participants with various socioeconomic backgrounds were involved in the questionnaire, and the survey-based activity locations were extracted to generate the vector field using the improved method. COVID-19 pandemic exposure (or risk) was estimated for different social groups. The findings show that people in the low-income group have an 8% to 10% higher risk than those in the high-income group. This new method of vector field may benefit geographers and urban researchers, as it provides opportunities to integrate human activities into the metrics of pandemic risk, spatial justice, and other environmental exposures.
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20.
  • Hall, Ola, et al. (författare)
  • How Data-Poor Countries Remain Data Poor: Underestimation of Human Settlements in Burkina Faso as Observed from Nighttime Light Data
  • 2019
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 8:11
  • Tidskriftsartikel (refereegranskat)abstract
    • The traditional ways of measuring global sustainable development and economic development schemes and their progress suffer from a number of serious shortcomings. Remote sensing and specifically nighttime light has become a popular supplement to official statistics by providing an objective measure of human settlement that can be used as a proxy for population and economic development measures. With the increased availability and use of the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and data in social science, it has played an important role in data collection, including measuring human development and economic growth. Numerous studies are using nighttime light data to analyze dynamic regions such as expansions of urban areas and rapid industrialization often highlight the problem of saturation in urban centers with high light intensity. However, the quality of nighttime light data and its appropriateness for analyzing areas and regions with low and fluctuating levels of light have rarely been questioned or studied. This study examines the accuracy of DMSP-OLS and VIIRS-DNB by analyzing 147 communities in Burkina Faso to provide insights about problems related to the study of areas with a low intensity of nighttime light during the studied period from 1992 to 2012. It found that up to 57% of the communities studied were undetectable throughout the period, and only 9% of communities studied had a 100% detection rate. Unsurprisingly, the result provides evidence that detection rates in both datasets are particularly low (3%) for settlements with 0–9999 inhabitants, as well as for larger settlements with population of 10,000–24,999 (28%). Cross-checking with VIIRS-DNB for the year 2012 shows similar results. These findings suggest that careful consideration must be given to the use of nighttime light data in research and global comparisons to monitor the progress of the United Nation’s Sustainable Development Goals, especially when including developing countries with areas containing low electrification rates and low population density.
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21.
  • Harrie, Lars, et al. (författare)
  • Analytical Estimation of Map Readability
  • 2015
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 4:2, s. 418-446
  • Tidskriftsartikel (refereegranskat)abstract
    • Readability is a major issue with all maps. In this study, we evaluated whether we can predict map readability using analytical measures, both single measures and composites of measures. A user test was conducted regarding the perceived readability of a number of test map samples. Evaluations were then performed to determine how well single measures and composites of measures could describe the map readability. The evaluation of single measures showed that the amount of information was most important, followed by the spatial distribution of information. The measures of object complexity and graphical resolution were not useful for explaining the map readability of our test data. The evaluations of composites of measures included three methods: threshold evaluation, multiple linear regression and support vector machine. We found that the use of composites of measures was better for describing map readability than single measures, but we could not identify any major differences in the results of the three composite methods. The results of this study can be used to recommend readability measures for triggering and controlling the map generalization process of online maps.
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22.
  • Huang, Weiming, et al. (författare)
  • Assessment and benchmarking of spatially enabled RDF stores for the next generation of spatial data infrastructure
  • 2019
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 8:7
  • Tidskriftsartikel (refereegranskat)abstract
    • Geospatial information is indispensable for various real-world applications and is thus a prominent part of today’s data science landscape. Geospatial data is primarily maintained and disseminated through spatial data infrastructures (SDIs). However, current SDIs are facing challenges in terms of data integration and semantic heterogeneity because of their partially siloed data organization. In this context, linked data provides a promising means to unravel these challenges, and it is seen as one of the key factors moving SDIs toward the next generation. In this study, we investigate the technical environment of the support for geospatial linked data by assessing and benchmarking some popular and well-known spatially enabled RDF stores (RDF4J, GeoSPARQL-Jena, Virtuoso, Stardog, and GraphDB), with a focus on GeoSPARQL compliance and query performance. The tests were performed in two different scenarios. In the first scenario, geospatial data forms a part of a large-scale data infrastructure and is integrated with other types of data. In this scenario, we used ICOS Carbon Portal’s metadata—a real-world Earth Science linked data infrastructure. In the second scenario, we benchmarked the RDF stores in a dedicated SDI environment that contains purely geospatial data, and we used geospatial datasets with both crowd-sourced and authoritative data (the same test data used in a previous benchmark study, the Geographica benchmark). The assessment and benchmarking results demonstrate that the GeoSPARQL compliance of the RDF stores has encouragingly advanced in the last several years. The query performances are generally acceptable, and spatial indexing is imperative when handling a large number of geospatial objects. Nevertheless, query correctness remains a challenge for cross-database interoperability. In conclusion, the results indicate that the spatial capacity of the RDF stores has become increasingly mature, which could benefit the development of future SDIs.
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23.
  • Jiang, Bin, 1965-, et al. (författare)
  • A Fractal Perspective on Scale in Geography
  • 2016
  • Ingår i: ISPRS International Journal of Geo-information. - : MDPI AG. - 2220-9964. ; 5:6
  • Tidskriftsartikel (refereegranskat)abstract
    • Scale is a fundamental concept that has attracted persistent attention in geography literature over the past several decades. However, it creates enormous confusion and frustration, particularly in the context of geographic information science, because of scale-related issues such as image resolution and the modifiable areal unit problem (MAUP). This paper argues that the confusion and frustration arise from traditional Euclidean geometric thinking, in which locations, directions, and sizes are considered absolute, and it is now time to revise this conventional thinking. Hence, we review fractal geometry, together with its underlying way of thinking, and compare it to Euclidean geometry. Under the paradigm of Euclidean geometry, everything is measurable, no matter how big or small. However, most geographic features, due to their fractal nature, are essentially unmeasurable or their sizes depend on scale. For example, the length of a coastline, the area of a lake, and the slope of a topographic surface are all scale-dependent. Seen from the perspective of fractal geometry, many scale issues, such as the MAUP, are inevitable. They appear unsolvable, but can be dealt with. To effectively deal with scale-related issues, we present topological and scaling analyses illustrated by street-related concepts such as natural streets, street blocks, and natural cities. We further contend that one of the two spatial properties, spatial heterogeneity, is de facto the fractal nature of geographic features, and it should be considered the first effect among the two, because it is global and universal across all scales, which should receive more attention from practitioners of geography.
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24.
  • Jiang, Bin, Professor, 1965-, et al. (författare)
  • A map is a living structure with the recurring notion of far more smalls than larges
  • 2020
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI. - 2220-9964. ; 9:6
  • Tidskriftsartikel (refereegranskat)abstract
    • The Earth’s surface or any territory is a coherent whole or subwhole, in which the notion of “far more small things than large ones” recurs at different levels of scale ranging from the smallest of a couple of meters to the largest of the Earth’s surface or that of the territory. The coherent whole has the underlying character called wholeness or living structure, which is a physical phenomenon pervasively existing in our environment and can be defined mathematically under the new third view of space conceived and advocated by Christopher Alexander: space is neither lifeless nor neutral, but a living structure capable of being more alive or less alive. This paper argues that both the map and the territory are a living structure, and that it is the inherent hierarchy of “far more smalls than larges” that constitutes the foundation of maps and mapping. It is the underlying living structure of geographic space or geographic features that makes maps or mapping possible, i.e., larges to be retained, while smalls to be omitted in a recursive manner (Note: larges and smalls should be understood broadly and wisely, in terms of not only sizes, but also topological connectivity and semantic meaning). Thus, map making is largely an objective undertaking governed by the underlying living structure, and maps portray the truth of the living structure. Based on the notion of living structure, a map can be considered to be an iterative system, which means that the map is the map of the map of the map, and so on endlessly. The word endlessly means continuous map scales between two discrete ones, just as there are endless real numbers between 1 and 2. The iterated map system implies that each of the subsequent small-scale maps is a subset of the single large-scale map, not a simple subset but with various constraints to make all geographic features topologically correct.
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25.
  • Jiang, Bin, Professor, 1965- (författare)
  • Spatial heterogeneity, scale, data character and sustainable transport in the big data era
  • 2018
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 7:5 (SI)
  • Tidskriftsartikel (refereegranskat)abstract
    • I have advocated and argued for a paradigm shift from Tobler’s law to scaling law, from Euclidean geometry to fractal geometry, from Gaussian statistics to Paretian statistics, and – more importantly – from Descartes’ mechanistic thinking to Alexander’s organic thinking. Fractal geometry falls under the third definition of fractal given by Bin Jiang – that is, a set or pattern is fractal if the scaling of far more small things than large ones recurs multiple times – rather than under the second definition of fractal by Benoit Mandelbrot, which requires a power law between scales and details. The new fractal geometry is more towards Christopher Alexander’s living geometry, not only for understanding complexity, but also for creating complex or living structure. This short paper attempts to clarify why the paradigm shift is essential and to elaborate on several concepts, including spatial heterogeneity (scaling law), scale (or the fourth meaning of scale), data character (in contrast to data quality), and sustainable transport in the big data era.
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26.
  • Karydas, Christos, et al. (författare)
  • Scale optimization in topographic and hydrographic feature mapping using fractal analysis
  • 2020
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI. - 2220-9964. ; 9:11
  • Tidskriftsartikel (refereegranskat)abstract
    • A new method for selecting optimal scales when mapping topographic or hydrographic features is introduced. The method employs rank-size partition of heavy-tailed distributions to detect nodes of rescaling invariance in the underlying hierarchy of the dataset. These nodes, known as head/tail breaks, can be used to indicate optimal scales. Then, the Fractal Net Evolution Assessment (FNEA) segmentation algorithm is applied with the topographic or hydrographic surfaces to produce optimally scaled objects. A topological transformation allows linking the two processes (partition and segmentation), while fractal dimension of the rescaling process is employed as an optimality metric. The new method is experimented with the two biggest river basins in Greece, namely Pinios and Acheloos river basins, using a digital elevation model as the only input dataset. The method proved successful in identifying a set of optimal scales for mapping elevation, slope, and flow accumulation. Deviation from the ideal conditions for implementing head/tail breaks are discussed. Implementation of the method requires an object-based analysis program and few common geospatial functions embedded in most GIS programs. The new method will assist in revealing underlying environmental processes in a variety of earth science fields and, thus, assist in land management decision-making and mapping generalization. 
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27.
  • Kovacs-Gyoeri, Anna, et al. (författare)
  • Opportunities and Challenges of Geospatial Analysis for Promoting Urban Livability in the Era of Big Data and Machine Learning
  • 2020
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 9:12
  • Tidskriftsartikel (refereegranskat)abstract
    • Urban systems involve a multitude of closely intertwined components, which are more measurable than before due to new sensors, data collection, and spatio-temporal analysis methods. Turning these data into knowledge to facilitate planning efforts in addressing current challenges of urban complex systems requires advanced interdisciplinary analysis methods, such as urban informatics or urban data science. Yet, by applying a purely data-driven approach, it is too easy to get lost in the 'forest' of data, and to miss the 'trees' of successful, livable cities that are the ultimate aim of urban planning. This paper assesses how geospatial data, and urban analysis, using a mixed methods approach, can help to better understand urban dynamics and human behavior, and how it can assist planning efforts to improve livability. Based on reviewing state-of-the-art research the paper goes one step further and also addresses the potential as well as limitations of new data sources in urban analytics to get a better overview of the whole 'forest' of these new data sources and analysis methods. The main discussion revolves around the reliability of using big data from social media platforms or sensors, and how information can be extracted from massive amounts of data through novel analysis methods, such as machine learning, for better-informed decision making aiming at urban livability improvement.
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28.
  • Kumar, Praveen, et al. (författare)
  • Rapid Evaluation and Validation Method of Above Ground Forest Biomass Estimation Using Optical Remote Sensing in Tundi Reserved Forest Area, India
  • 2021
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI. - 2220-9964. ; 10:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Optical remote sensing data are freely available on a global scale. However, the satellite image processing and analysis for quick, accurate, and precise forest above ground biomass (AGB) evaluation are still challenging and difficult. This paper is aimed to develop a novel method for precise, accurate, and quick evaluation of the forest AGB from optical remote sensing data. Typically, the ground forest AGB was calculated using an empirical model from ground data for biophysical parameters such as tree density, height, and diameter at breast height (DBH) collected from the field at different elevation strata. The ground fraction of vegetation cover (FVC) in each ground sample location was calculated. Then, the fraction of vegetation cover (FVC) from optical remote sensing imagery was calculated. In the first stage of method implementation, the relation model between the ground FVC and ground forest AGB was developed. In the second stage, the relational model was established between image FVC and ground FVC. Finally, both models were fused to derive the relational model between image FVC and forest AGB. The validation of the developed method was demonstrated utilizing Sentinel-2 imagery as test data and the Tundi reserved forest area located in the Dhanbad district of Jharkhand state in eastern India was used as the test site. The result from the developed model was ground validated and also compared with the result from a previously developed crown projected area (CPA)-based forest AGB estimation approach. The results from the developed approach demonstrated superior capabilities in precision compared to the CPA-based method. The average forest AGB estimation of the test site obtained by this approach revealed 463 tons per hectare, which matches the previous estimate from this test site.
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29.
  • Landré, Martin (författare)
  • Geoprocessing journey-to-work data : delineating commuting regions in Dalarna, Sweden
  • 2012
  • Ingår i: ISPRS International Journal of Geo-information. - Basel, Switzerland : MDPI. - 2220-9964. ; :1, s. 294-314
  • Tidskriftsartikel (refereegranskat)abstract
    • Delineation of commuting regions has always been based on statistical units, often municipalities or wards. However, using these units has certain disadvantages as their land areas differ considerably. Much information is lost in the larger spatial base units and distortions in self-containment values, the main criterion in rule-based delineation procedures, occur. Alternatively, one can start from relatively small standard size units such as hexagons. In this way, much greater detail in spatial patterns is obtained. In this paper, regions are built by means of intrazonal maximization (Intramax) on the basis of hexagons. The use of geoprocessing tools, specifically developed for the processing ofcommuting data, speeds up processing time considerably. The results of the Intramax analysis are evaluated with travel-to-work area constraints, and comparisons are made with commuting fields, accessibility to employment, commuting flow density and network commuting flow size. From selected steps in the regionalization process, a hierarchy of nested commuting regions emerges, revealing the complexity of commuting patterns.
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30.
  • Lin, Jingyi, et al. (författare)
  • Comparative Analysis on Topological Structures of Urban Street Networks
  • 2017
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 6:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Street systems are the backbone of cities. With global urbanization and economic development, street systems have undergone significant development along with the growth of cities. In this paper, the authors select three cities with varying sizes, histories, locations, and growth dynamics: Stockholm, Toronto, and Nanjing. We analyze topological structures of their public street systems based on GIS and complex network theory. Considering the planarity of street systems, we first calculate various topological measures, including , , and indices, and density. This is followed by comparing three centrality measures, i.e., degree, betweenness, and closeness in complex network theory. In this part, we investigate these characteristics of nodes and edges in a primal representation, and discuss their relations with urban growth mechanisms.
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31.
  • Liu, Fei, et al. (författare)
  • Evaluation of augmented reality-based building diagnostics using third person perspective
  • 2020
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI. - 2220-9964. ; 9:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Comprehensive user evaluations of outdoor augmented reality (AR) applications in the architecture, engineering, construction and facilities management (AEC/FM) industry are rarely reported in the literature. This paper presents an AR prototype system for infrared thermographic façade inspection and its evaluation. The system employs markerless tracking based on image registration using natural features and a third person perspective (TPP) augmented view displayed on a hand-held smart device. We focus on evaluating the system in user experiments with the task of designating positions of heat spots on an actual façade as if acquired through thermographic inspection. User and system performance were both assessed with respect to target designation errors. The main findings of this study show that positioning accuracy using this system is adequate for objects of the size of one decimeter. After ruling out the system inherent errors, which mainly stem from our application-specific image registration procedure, we find that errors due to a human’s limited visual-motoric and cognitive performance, which have a more general implication for using TPP AR for target designation, are only a few centimeters.
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32.
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33.
  • Ma, Ding, et al. (författare)
  • Characterizing the Heterogeneity of the OpenStreetMap Data and Community
  • 2015
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 4:2, s. 535-550
  • Tidskriftsartikel (refereegranskat)abstract
    • 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.
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34.
  • Mao, Bo, et al. (författare)
  • Methodology for the efficient progressive distribution and visualization of 3D building objects
  • 2016
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 5:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Three-dimensional (3D), city models have been applied in a variety of fields. One of the main problems in 3D city model utilization, however, is the large volume of data. In this paper, a method is proposed to generalize the 3D building objects in 3D city models at different levels of detail, and to combine multiple Levels of Detail (LODs) for a progressive distribution and visualization of the city models. First, an extended structure for multiple LODs of building objects, BuildingTree, is introduced that supports both single buildings and building groups; second, constructive solid geometry (CSG) representations of buildings are created and generalized. Finally, the BuildingTree is stored in the NoSQL database MongoDB for dynamic visualization requests. The experimental results indicate that the proposed progressive method can efficiently visualize 3D city models, especially for large areas.
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35.
  • Milutinovic, Goran, et al. (författare)
  • Geospatial Decision-Making Framework Based on the Concept of Satisficing
  • 2021
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI. - 2220-9964. ; 10:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Decision-making methods used in geospatial decision making are computationally complex prescriptive methods, the details of which are rarely transparent to the decision maker. However, having a deep understanding of the details and mechanisms of the applied method is a prerequisite for the efficient use thereof. In this paper, we present a novel decision-making framework that emanates from the need for intuitive and easy-to-use decision support systems for geospatial multi-criteria decision making. The framework consists of two parts: the decision-making model Even Swaps on Reduced Data Sets (ESRDS), and the interactive visualization framework. The decision-making model is based on the concept of satisficing, and as such, it is intuitive and easy to understand and apply. It integrates even swaps, a prescriptive decision-making method, with the findings of behavioural decision-making theories. Providing visual feedback and interaction opportunities throughout the decision-making process, the interactive visualization part of the framework helps the decision maker gain better insight into the decision space and attribute dependencies. Furthermore, it provides the means to analyse and compare the outcomes of different scenarios and decision paths.
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36.
  • Nhu, Viet-Ha, et al. (författare)
  • Daily Water Level Prediction of Zrebar Lake (Iran) : A Comparison between M5P, Random Forest, Random Tree and Reduced Error Pruning Trees Algorithms
  • 2020
  • Ingår i: ISPRS International Journal of Geo-Information. - Switzerland : MDPI. - 2220-9964. ; 9:8
  • Tidskriftsartikel (refereegranskat)abstract
    • Zrebar Lake is one of the largest freshwater lakes in Iran and it plays an important role in the ecosystem of the environment, while its desiccation has a negative impact on the surrounded ecosystem. Despite this, this lake provides an interesting recreation setting in terms of ecotourism. The prediction and forecasting of the water level of the lake through simple but practical methods can provide a reliable tool for future lake water resource management. In the present study, we predict the daily water level of Zrebar Lake in Iran through well-known decision tree-based algorithms, including the M5 pruned (M5P), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). We used five different water input combinations to find the most effective one. For our modeling, we chose 70% of the dataset for training (from 2011 to 2015) and 30% for model evaluation (from 2015 to 2017). We evaluated the models’ performances using different quantitative (root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), percent bias (PBIAS) and ratio of the root mean square error to the standard deviation of measured data (RSR)) and visual frameworks (Taylor diagram and box plot). Our results showed that water level with a one-day lag time had the highest effect on the result and, by increasing the lag time, its effect on the result was decreased. This result indicated that all the developed models had a good prediction capability, but the M5P model outperformed the others, followed by RF and RT equally and then REPT. Our results showed that these algorithms can predict water level accurately only with a one-day lag time in water level as an input and they are cost-effective tools for future predictions.
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37.
  • Niyomubyeyi, Olive, et al. (författare)
  • Evacuation planning optimization based on a multi-objective artificial bee colony algorithm
  • 2019
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 8:3
  • Tidskriftsartikel (refereegranskat)abstract
    • Evacuation is an important activity for reducing the number of casualties and amount of damage in disaster management. Evacuation planning is tackled as a spatial optimization problem. The decision-making process for evacuation involves high uncertainty, conflicting objectives, and spatial constraints. This study presents a Multi-Objective Artificial Bee Colony (MOABC) algorithm, modified to provide a better solution to the evacuation problem. The new approach combines random swap and random insertion methods for neighborhood search, the two-point crossover operator, and the Pareto-based method. For evacuation planning, two objective functions were considered to minimize the total traveling distance from an affected area to shelters and to minimize the overload capacity of shelters. The developed model was tested on real data from the city of Kigali, Rwanda. From computational results, the proposed model obtained a minimum fitness value of 5.80 for capacity function and 8.72 × 10 8 for distance function, within 161 s of execution time. Additionally, in this research we compare the proposed algorithm with Non-Dominated Sorting Genetic Algorithm II and the existing Multi-Objective Artificial Bee Colony algorithm. The experimental results show that the proposed MOABC outperforms the current methods both in terms of computational time and better solutions with minimum fitness values. Therefore, developing MOABC is recommended for applications such as evacuation planning, where a fast-running and efficient model is needed.
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38.
  • Noardo, Francesca, et al. (författare)
  • Tools for BIM-GIS Integration (IFC Georeferencing and Conversions): Results from the GeoBIM Benchmark 2019
  • 2020
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 9:9
  • Tidskriftsartikel (refereegranskat)abstract
    • The integration of 3D city models with Building Information Models (BIM), coined as GeoBIM, facilitates improved data support to several applications, e.g., 3D map updates, building permits issuing, detailed city analysis, infrastructure design, context-based building design, to name a few. To solve the integration, several issues need to be tackled and solved, i.e., harmonization of features, interoperability, format conversions, integration of procedures. The GeoBIM benchmark 2019, funded by ISPRS and EuroSDR, evaluated the state of implementation of tools addressing some of those issues. In particular, in the part of the benchmark described in this paper, the application of georeferencing to Industry Foundation Classes (IFC) models and making consistent conversions between 3D city models and BIM are investigated, considering the OGC CityGML and buildingSMART IFC as reference standards. In the benchmark, sample datasets in the two reference standards were provided. External volunteers were asked to describe and test georeferencing procedures for IFC models and conversion tools between CityGML and IFC. From the analysis of the delivered answers and processed datasets, it was possible to notice that while there are tools and procedures available to support georeferencing and data conversion, comprehensive definition of the requirements, clear rules to perform such two tasks, as well as solid technological solutions implementing them, are still lacking in functionalities. Those specific issues can be a sensible starting point for planning the next GeoBIM integration agendas.
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39.
  • Olsson, Per Ola, et al. (författare)
  • Automation of building permission by integration of BIM and geospatial data
  • 2018
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 7:8
  • Tidskriftsartikel (refereegranskat)abstract
    • The building permission process is to a large extent an analogue process where much information is handled in paper format or as pdf files. With the ongoing digitalisation in society, there is a potential to automate this process by integrating Building Information Models (BIM) of planned buildings and geospatial data to check if a building conforms to the building permission regulations. In this study, an inventory of which regulations in the (Swedish) detailed development plans that can be automatically checked or supported by 3D visualisation was conducted. Then, two of these regulations, the building height and the building footprint area, were studied in detail to find to which extent they can be automatically checked by integration of BIM and geospatial data. In addition, a feasibility study of one visual criterion was conducted. One concern when automating the building permission process is the variability of content within the Industry Foundation Classes (IFC) data model. Variations in modelling methods and model content leads to differences in IFC models' content and structure; these differences complicate automated processes. To facilitate automated processes, requirements on the production of IFC models for building permission applications could be defined in the form of model view definitions or delivery specifications.
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40.
  • Omidipoor, Morteza, et al. (författare)
  • Knowledge discoveryweb service for spatial data infrastructures
  • 2021
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 10:1
  • Tidskriftsartikel (refereegranskat)abstract
    • The size, volume, variety, and velocity of geospatial data collected by geo-sensors, people, and organizations are increasing rapidly. Spatial Data Infrastructures (SDIs) are ongoing to facilitate the sharing of stored data in a distributed and homogeneous environment. Extracting high-level information and knowledge from such datasets to support decision making undoubtedly requires a relatively sophisticated methodology to achieve the desired results. A variety of spatial data mining techniques have been developed to extract knowledge from spatial data, which work well on centralized systems. However, applying them to distributed data in SDI to extract knowledge has remained a challenge. This paper proposes a creative solution, based on distributed computing and geospatial web service technologies for knowledge extraction in an SDI environment. The proposed approach is called Knowledge DiscoveryWeb Service (KDWS), which can be used as a layer on top of SDIs to provide spatial data users and decision makers with the possibility of extracting knowledge from massive heterogeneous spatial data in SDIs. By proposing and testing a system architecture for KDWS, this study contributes to perform spatial data mining techniques as a service-oriented framework on top of SDIs for knowledge discovery. We implemented and tested spatial clustering, classification, and association rule mining in an interoperable environment. In addition to interface implementation, a prototype web-based system was designed for extracting knowledge from real geodemographic data in the city of Tehran. The proposed solution allows a dynamic, easier, and much faster procedure to extract knowledge from spatial data.
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41.
  • Opach, Tomasz, et al. (författare)
  • Pedestrian Routing and Perspectives : WayFinder’s Route down the Lane—Come on with the Rain
  • 2021
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI. - 2220-9964. ; 10:6
  • Tidskriftsartikel (refereegranskat)abstract
    • People living in urban areas are often exposed to heat and inundation caused by heavy rains. Therefore, pedestrian routing in areas exposed to weather-related threats can be of value to citizens. In this study, water accumulated on roads, sidewalks and footpaths after rainfall and snowmelt was used as a case of adverse environmental conditions. Pedestrian routing was implemented in the web tool WayFinder and a group of 56 participants tested the tool in Trondheim, Norway. The study aimed to gain insight into their perspectives on the implemented pedestrian routing functionality to examine to what extent pedestrians find such functionality helpful for navigating in regions that are likely to be inundated. Each participant was asked to (1) use the tool in practice; (2) when walking, report on observed inundated areas; and (3) complete three questionnaires to provide feedback on the WayFinder tool. Although most of the participants were successful in using WayFinder, they preferred the selection of routes that passed through areas likely to be inundated and obtaining information about the risks than selecting a single route suggestion that already avoided exposed areas.
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42.
  • Padmanaban, Rajchandar, et al. (författare)
  • A Remote Sensing Approach to Environmental Monitoring in a Reclaimed Mine Area
  • 2017
  • Ingår i: ISPRS international journal of geo-information. - : MDPI AG. - 2220-9964. ; 6:12
  • Tidskriftsartikel (refereegranskat)abstract
    • Mining for resources extraction may lead to geological and associated environmental changes due to ground movements, collision with mining cavities, and deformation of aquifers. Geological changes may continue in a reclaimed mine area, and the deformed aquifers may entail a breakdown of substrates and an increase in ground water tables, which may cause surface area inundation. Consequently, a reclaimed mine area may experience surface area collapse, i.e., subsidence, and degradation of vegetation productivity. Thus, monitoring short-term landscape dynamics in a reclaimed mine area may provide important information on the long-term geological and environmental impacts of mining activities. We studied landscape dynamics in Kirchheller Heide, Germany, which experienced extensive soil movement due to longwall mining without stowing, using Landsat imageries between 2013 and 2016. A Random Forest image classification technique was applied to analyze land-use and landcover dynamics, and the growth of wetland areas was assessed using a Spectral Mixture Analysis (SMA). We also analyzed the changes in vegetation productivity using a Normalized Difference Vegetation Index (NDVI). We observed a 19.9% growth of wetland area within four years, with 87.2% growth in the coverage of two major waterbodies in the reclaimed mine area. NDVI values indicate that the productivity of 66.5% of vegetation of the Kirchheller Heide was degraded due to changes in ground water tables and surface flooding. Our results inform environmental management and mining reclamation authorities about the subsidence spots and priority mitigation areas from land surface and vegetation degradation in Kirchheller Heide.
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43.
  • Ren, Zheng, et al. (författare)
  • Capturing and characterizing human activities using building locations in America
  • 2019
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI. - 2220-9964. ; 8:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Capturing and characterizing collective human activities in a geographic space have become much easier than ever before in the big era. In the past few decades it has been difficult to acquire the spatiotemporal information of human beings. Thanks to the boom in the use of mobile devices integrated with positioning systems and location-based social media data, we can easily acquire the spatial and temporal information of social media users. Previous studies have successfully used street nodes and geo-tagged social media such as Twitter to predict users’ activities. However, whether human activities can be well represented by social media data remains uncertain. On the other hand, buildings or architectures are permanent and reliable representations of human activities collectively through historical footprints. This study aims to use the big data of US building footprints to investigate the reliability of social media users for human activity prediction. We created spatial clusters from 125 million buildings and 1.48 million Twitter points in the US. We further examined and compared the spatial and statistical distribution of clusters at both country and city levels. The result of this study shows that both building and Twitter data spatial clusters show the scaling pattern measured by the scale of spatial clusters, respectively, characterized by the number points inside clusters and the area of clusters. More specifically, at the country level, the statistical distribution of the building spatial clusters fits power law distribution. Inside the four largest cities, the hotspots are power-law-distributed with the power law exponent around 2.0, meaning that they also follow the Zipf’s law. The correlations between the number of buildings and the number of tweets are very plausible, with the r square ranging from 0.53 to 0.74. The high correlation and the similarity of two datasets in terms of spatial and statistical distribution suggest that, although social media users are only a proportion of the entire population, the spatial clusters from geographical big data is a good and accurate representation of overall human activities. This study also indicates that using an improved method for spatial clustering is more suitable for big data analysis than the conventional clustering methods based on Euclidean geometry.
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44.
  • See, Linda, et al. (författare)
  • Crowdsourcing, citizen science or volunteered geographic information? : The current state of crowdsourced geographic information
  • 2016
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 5:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Citizens are increasingly becoming an important source of geographic information, sometimes entering domains that had until recently been the exclusive realm of authoritative agencies. This activity has a very diverse character as it can, amongst other things, be active or passive, involve spatial or aspatial data and the data provided can be variable in terms of key attributes such as format, description and quality. Unsurprisingly, therefore, there are a variety of terms used to describe data arising from citizens. In this article, the expressions used to describe citizen sensing of geographic information are reviewed and their use over time explored, prior to categorizing them and highlighting key issues in the current state of the subject. The latter involved a review of 100 Internet sites with particular focus on their thematic topic, the nature of the data and issues such as incentives for contributors. This review suggests that most sites involve active rather than passive contribution, with citizens typically motivated by the desire to aid a worthy cause, often receiving little training. As such, this article provides a snapshot of the role of citizens in crowdsourcing geographic information and a guide to the current status of this rapidly emerging and evolving subject.
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45.
  • Sun, Jing, et al. (författare)
  • Utilizing BIM and GIS for Representation and Visualization of 3D Cadastre
  • 2019
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI. - 2220-9964. ; 8:11
  • Tidskriftsartikel (refereegranskat)abstract
    • The current three-dimensionally (3D) delimited property units are in most countries registered using two-dimensional (2D) documentation and textual descriptions. This approach has limitations if used for representing the actual extent of complicated 3D property units, in particular in city centers. 3D digital models such as building information model (BIM) and 3D geographic information system (GIS) could be utilized for accurate identification of property units, better representation of cadastral boundaries, and detailed visualization of complex buildings. To facilitate this, several requirements need to be identified considering organizational, legal, and technical aspects. In this study, we formulate these requirements and then develop a framework for integration of 3D cadastre and 3D digital models. The aim of this paper is that cadastral information stored based on the land administration domain model (LADM) are integrated with BIM on building level for accurate representation of legal boundaries and with GIS on city level for visualization of 3D cadastre in urban environments. The framework is implemented and evaluated against the requirements in a practical case study in Sweden. The conclusion is that the integration of the cadastral information and BIM/GIS is possible on both conceptual level and data level which will facilitate that organizations dealing with cadastral information (cadastral units), BIM models (architecture, engineering, and construction companies), and GIS (surveying units on e.g., municipality level) can exchange information; this facilitates better representation and visualization of 3D cadastral boundaries.
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46.
  • van den Homberg, Marc, et al. (författare)
  • Characterizing Data Ecosystems to Support Official Statistics with Open Mapping Data for Reporting on Sustainable Development Goals
  • 2018
  • Ingår i: ISPRS International Journal of Geo-Information. - Basel, Switzerland : MDPI. - 2220-9964. ; 7:12
  • Tidskriftsartikel (refereegranskat)abstract
    • Reporting on the Sustainable Development Goals (SDGs) is complex given the wide variety of governmental and NGO actors involved in development projects as well as the increased number of targets and indicators. However, data on the wide variety of indicators must be collected regularly, in a robust manner, comparable across but also within countries and at different administrative and disaggregated levels for adequate decision making to take place. Traditional census and household survey data is not enough. The increase in Small and Big Data streams have the potential to complement official statistics. The purpose of this research is to develop and evaluate a framework to characterize a data ecosystem in a developing country in its totality and to show how this can be used to identify data, outside the official statistics realm, that enriches the reporting on SDG indicators. Our method consisted of a literature study and an interpretative case study (two workshops with 60 and 35 participants and including two questionnaires, over 20 consultations and desk research). We focused on SDG 6.1.1. (Proportion of population using safely managed drinking water services) in rural Malawi. We propose a framework with five dimensions (actors, data supply, data infrastructure, data demand and data ecosystem governance). Results showed that many governmental and NGO actors are involved in water supply projects with different funding sources and little overall governance. There is a large variety of geospatial data sharing platforms and online accessible information management systems with however a low adoption due to limited internet connectivity and low data literacy. Lots of data is still not open. All this results in an immature data ecosystem. The characterization of the data ecosystem using the framework proves useful as it unveils gaps in data at geographical level and in terms of dimensionality (attributes per water point) as well as collaboration gaps. The data supply dimension of the framework allows identification of those datasets that have the right quality and lowest cost of data extraction to enrich official statistics. Overall, our analysis of the Malawian case study illustrated the complexities involved in achieving self-regulation through interaction, feedback and networked relationships. Additional complexities, typical for developing countries, include fragmentation, divide between governmental and non-governmental data activities, complex funding relationships and a data poor context.
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47.
  • Wang, Zhenwu, et al. (författare)
  • A Three-Dimensional Visualization Framework forUnderground Geohazard Recognition on UrbanRoad-Facing GPR Data
  • 2020
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 9:11
  • Tidskriftsartikel (refereegranskat)abstract
    • The identification of underground geohazards is always a difficult issue in the field of underground public safety. This study proposes an interactive visualization framework for underground geohazard recognition on urban roads, which constructs a whole recognition workflow by incorporating data collection, preprocessing, modeling, rendering and analyzing. In this framework, two proposed sampling point selection methods have been adopted to enhance the interpolated accuracy for the Kriging algorithm based on ground penetrating radar (GPR) technology. An improved Kriging algorithm was put forward, which applies a particle swarm optimization (PSO) algorithm to optimize the Kriging parameters and adopts in parallel the Compute Unified Device Architecture (CUDA) to run the PSO algorithm on the GPU side in order to raise the interpolated efficiency. Furthermore, a layer-constrained triangulated irregular network algorithm was proposed to construct the 3D geohazard bodies and the space geometry method was used to compute their volume information. The study also presents an implementation system to demonstrate the application of the framework and its related algorithms. This system makes a significant contribution to the demonstration and understanding of underground geohazard recognition in a three-dimensional environment.
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48.
  • Österbring, Magnus, 1986, et al. (författare)
  • Stakeholder Specific Multi-Scale Spatial Representation of Urban Building-Stocks
  • 2018
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 7:5, s. 173-
  • Tidskriftsartikel (refereegranskat)abstract
    • Urban building-stocks use a significant amount of resources and energy. At the same time, theyhave a large potential for energy efficiency measures (EEM). To support decision-making and planning, spatial building-stock models are used to examine the current state and future development of urbanbuilding-stocks. While these models normally focus on specific cities, generic and broad stakeholder groups such as planners and policy makers are often targeted. Consequently, the visualization and communication of results are not tailored to these stakeholders. The aim of this paper is to explore the possibilities of mapping and representing energy use of urban building-stocks at different levels of aggregation and spatial distributions, to communicate with specific stakeholders involved in the urban development process. This paper uses a differentiated building-stock description based on building-specific data andmeasured energy use fromenergy performance certificates formulti-family buildings (MFB) in the city of Gothenburg. The building-stock description treats every building as unique, allowing results to be provided at any level of aggregation to suit the needs of the specific stakeholders involved. Calculated energy use of the existing stock is within 10% of the measured energy use. The potential for EEM in the existing stock is negated by the increased energy use due to new construction until 2035, using a development scenario based on current renovation rates and planned developments. Visualizations of the current energy use of the stock as well as the impact of renovation and new construction are provided, targeting specific local stakeholders.
  •  
49.
  • Aturinde, Augustus, et al. (författare)
  • Space–Time Surveillance of COVID-19 Seasonal Clusters : A Case of Sweden
  • 2022
  • Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 11:5
  • Tidskriftsartikel (refereegranskat)abstract
    • While COVID-19 is a global pandemic, different countries have experienced different morbidity and mortality patterns. We employ retrospective and prospective space–time permutation analysis on COVID-19 positive records across different municipalities in Sweden from March 2020 to February 2021, using data provided by the Swedish Public Health Agency. To the best of our knowledge, this is the first study analyzing nationwide COVID-19 space–time clustering in Sweden, on a season-to-season basis. Our results show that different municipalities within Sweden experienced varying extents of season-dependent COVID-19 clustering in both the spatial and temporal dimensions. The reasons for the observed differences could be related to the differences in the earlier exposures to the virus, the strictness of the social restrictions, testing capabilities and preparedness. By profiling COVID-19 space–time clusters before the introduction of vaccines, this study contributes to public health efforts aimed at containing the virus by providing plausible evidence in evaluating which epidemiologic interventions in the different regions could have worked and what could have not worked.
  •  
50.
  • Boldt, Martin, et al. (författare)
  • Evaluating Temporal Analysis Methods UsingResidential Burglary Data
  • 2016
  • Ingår i: ISPRS International Journal of Geo-Information, Special Issue on Frontiers in Spatial and Spatiotemporal Crime Analytics. - : MDPI. - 2220-9964. ; 5:9, s. 1-22
  • Tidskriftsartikel (refereegranskat)abstract
    • Law enforcement agencies, as well as researchers rely on temporal analysis methods in many crime analyses, e.g., spatio-temporal analyses. A number of temporal analysis methods are being used, but a structured comparison in different configurations is yet to be done. This study aims to fill this research gap by comparing the accuracy of five existing, and one novel, temporal analysis methods in approximating offense times for residential burglaries that often lack precise time information. The temporal analysis methods are evaluated in eight different configurations with varying temporal resolution, as well as the amount of data (number of crimes) available during analysis. A dataset of all Swedish residential burglaries reported between 2010 and 2014 is used (N = 103,029). From that dataset, a subset of burglaries with known precise offense times is used for evaluation. The accuracy of the temporal analysis methods in approximating the distribution of burglaries with known precise offense times is investigated. The aoristic and the novel aoristic_ext method perform significantly better than three of the traditional methods. Experiments show that the novel aoristic_ext method was most suitable for estimating crime frequencies in the day-of-the-year temporal resolution when reduced numbers of crimes were available during analysis. In the other configurations investigated, the aoristic method showed the best results. The results also show the potential from temporal analysis methods in approximating the temporal distributions of residential burglaries in situations when limited data are available.
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