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ISPRS Int. J. Geo-Inf., Volume 5, Issue 9 (September 2016)

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Open AccessArticle
Evaluation of Multiple Classifier Systems for Landslide Identification in LANDSAT Thematic Mapper (TM) Images
ISPRS Int. J. Geo-Inf. 2016, 5(9), 164; https://doi.org/10.3390/ijgi5090164 - 13 Sep 2016
Cited by 2 | Viewed by 1896
Abstract
Landslide scar location is fundamental for the risk management process, e.g., it allows mitigation of these areas, decreasing the associated hazards for the population. Remote sensing data usage is an essential tool for landslide identification, mapping, and monitoring. Despite its potential use for [...] Read more.
Landslide scar location is fundamental for the risk management process, e.g., it allows mitigation of these areas, decreasing the associated hazards for the population. Remote sensing data usage is an essential tool for landslide identification, mapping, and monitoring. Despite its potential use for landslide risk management, remote sensing usage does have a few drawbacks. The aforementioned events commonly occur at high steep slope regions, frequently associated with shadow occurrence in satellite images, which impairs the identification process and results in low accuracy classifications. In this sense, this paper aims to evaluate the accuracy of different ensembles of multiple classifier systems (MCSs) for landslide scar identification. A severe landslide event on a steep slope with a high rainfall rate area in the southeast region of Brazil was chosen. Ten supervised classifiers were used to identify this severe event and other possible features for the LANDSAT thematic mapper (TM) from June of 2000. The results were evaluated, and nine MCSs were constructed based on the accuracy of the classifiers. Voting was applied through the ensemble method, coupled with contextual analysis and random selection tie-breaker methods. Accuracy was evaluated for each classification ensemble, and a progressive enhancement in the ensemble accuracy was noted as the least accurate classifiers were removed. The best accuracy for landslide identification emerged from the ensemble of the three most accurate classification results. In summary, MCS application generally improved the classification quality and led to fewer omission errors, coupled with a better classification percentage for the ‘landslide’ class. However, the MCS ensemble algorithm selection must be customized to the purpose of the classification. It is crucial to assess single accuracy indicators of each algorithm to ascertain those with the most consistent performance regarding the final results. Full article
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Open AccessArticle
A Subdivision Method to Unify the Existing Latitude and Longitude Grids
ISPRS Int. J. Geo-Inf. 2016, 5(9), 161; https://doi.org/10.3390/ijgi5090161 - 13 Sep 2016
Cited by 12 | Viewed by 1923
Abstract
As research on large regions of earth progresses, many geographical subdivision grids have been established for various spatial applications by different industries and disciplines. However, there is no clear relationship between the different grids and no consistent spatial reference grid that allows for [...] Read more.
As research on large regions of earth progresses, many geographical subdivision grids have been established for various spatial applications by different industries and disciplines. However, there is no clear relationship between the different grids and no consistent spatial reference grid that allows for information exchange and comprehensive application. Sharing and exchange of data across departments and applications are still at a bottleneck. It would represent a significant step forward to build a new grid model that is inclusive of or compatible with most of the existing geodesic grids and that could support consolidation and exchange within existing data services. This study designs a new geographical coordinate global subdividing grid with one dimension integer coding on a 2n tree (GeoSOT) that has 2n coordinate subdivision characteristics (global longitude and latitude subdivision) and can form integer hierarchies at degree, minute, and second levels. This grid has the multi-dimensional quadtree hierarchical characteristics of a digital earth grid, but also provides good consistency with applied grids, such as those used in mapping, meteorology, oceanography and national geographical, and three-dimensional digital earth grids. No other existing grid codes possess these characteristics. Full article
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Open AccessArticle
Improving Seasonal Land Cover Maps of Poyang Lake Area in China by Taking into Account Logical Transitions
ISPRS Int. J. Geo-Inf. 2016, 5(9), 165; https://doi.org/10.3390/ijgi5090165 - 12 Sep 2016
Cited by 1 | Viewed by 1707
Abstract
Land cover maps are fundamental materials for resource management and change detection. Remote sensing technology is crucial for fast mapping with low cost. However, besides the inherent classification errors in the land cover products, numerous illogical transitions exist between the neighboring time points. [...] Read more.
Land cover maps are fundamental materials for resource management and change detection. Remote sensing technology is crucial for fast mapping with low cost. However, besides the inherent classification errors in the land cover products, numerous illogical transitions exist between the neighboring time points. In this study, we introduce a series of logical codes for all the land cover types according to the ecological rules in the study area. The codes represent the transformational logicality of species between different seasons. The classification performance and the codes for all the seasons are imposed on the initial land cover maps which have been produced independently by the conventional hierarchical strategy. We exploit the proposed modified hierarchical mapping strategy to map the land cover of Poyang Lake Basin area, Middle China. The illogical transitions between neighboring seasons and the accuracies based on the labeled samples are calculated for both the initial and modified strategies. The number of illogical pixels have been reduced by 13%–35% for different seasons and the average accuracy has been improved by 9.7% for the specific land cover maps. The accuracy of land cover changes has also presented great improvement of the proposed strategy. The experimental results have suggested the scheme is effective. Full article
(This article belongs to the Special Issue Advances and Innovations in Land Use/Cover Mapping)
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Open AccessArticle
Updating Road Networks by Local Renewal from GPS Trajectories
ISPRS Int. J. Geo-Inf. 2016, 5(9), 163; https://doi.org/10.3390/ijgi5090163 - 12 Sep 2016
Cited by 4 | Viewed by 2390
Abstract
The long production cycle and huge cost of collecting road network data often leave the data lagging behind the latest real conditions. However, this situation is rapidly changing as the positioning techniques ubiquitously used in mobile devices are gradually being implemented in road [...] Read more.
The long production cycle and huge cost of collecting road network data often leave the data lagging behind the latest real conditions. However, this situation is rapidly changing as the positioning techniques ubiquitously used in mobile devices are gradually being implemented in road network research and applications. Currently, the predominant approaches infer road networks from mobile location information (e.g., GPS trajectory data) directly using various extracting algorithms, which leads to expensive consumption of computational resources in the case of large-scale areas. For this reason, we propose an alternative that renews road networks with a novel spiral strategy, including a hidden Markov model (HMM) for detecting potential problems in existing road network data and a method to update the data, on the local scale, by generating new road segments from trajectory data. The proposed approach reduces computation costs on roads with completed or updated information by updating problem road segments in the minimum range of the road network. We evaluated the performance of our proposals using GPS traces collected from taxies and OpenStreetMap (OSM) road networks covering urban areas of Wuhan City. Full article
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Open AccessArticle
Analyzing Local Spatio-Temporal Patterns of Police Calls-for-Service Using Bayesian Integrated Nested Laplace Approximation
ISPRS Int. J. Geo-Inf. 2016, 5(9), 162; https://doi.org/10.3390/ijgi5090162 - 09 Sep 2016
Cited by 5 | Viewed by 2173
Abstract
This research investigates spatio-temporal patterns of police calls-for-service in the Region of Waterloo, Canada, at a fine spatial and temporal resolution. Modeling was implemented via Bayesian Integrated Nested Laplace Approximation (INLA). Temporal patterns for two-hour time periods, spatial patterns at the small-area scale, [...] Read more.
This research investigates spatio-temporal patterns of police calls-for-service in the Region of Waterloo, Canada, at a fine spatial and temporal resolution. Modeling was implemented via Bayesian Integrated Nested Laplace Approximation (INLA). Temporal patterns for two-hour time periods, spatial patterns at the small-area scale, and space-time interaction (i.e., unusual departures from overall spatial and temporal patterns) were estimated. Temporally, calls-for-service were found to be lowest in the early morning (02:00–03:59) and highest in the evening (20:00–21:59), while high levels of calls-for-service were spatially located in central business areas and in areas characterized by major roadways, universities, and shopping centres. Space-time interaction was observed to be geographically dispersed during daytime hours but concentrated in central business areas during evening hours. Interpreted through the routine activity theory, results are discussed with respect to law enforcement resource demand and allocation, and the advantages of modeling spatio-temporal datasets with Bayesian INLA methods are highlighted. Full article
(This article belongs to the Special Issue Frontiers in Spatial and Spatiotemporal Crime Analytics)
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Open AccessArticle
A Combination of Stop-and-Go and Electro-Tricycle Laser Scanning Systems for Rural Cadastral Surveys
ISPRS Int. J. Geo-Inf. 2016, 5(9), 160; https://doi.org/10.3390/ijgi5090160 - 06 Sep 2016
Cited by 2 | Viewed by 1728
Abstract
Over the past decade, land-based laser scanning technologies have been actively studied and implemented, in response to the need for detailed three-dimensional (3D) data about our rural and urban environment for topographic mapping, cadastral mapping, and other street-level features, which are difficult and [...] Read more.
Over the past decade, land-based laser scanning technologies have been actively studied and implemented, in response to the need for detailed three-dimensional (3D) data about our rural and urban environment for topographic mapping, cadastral mapping, and other street-level features, which are difficult and time consuming to measure by other instruments. For rural areas in China, the complex terrain and poor planning limit the applicability of this advanced technology. To improve the efficiency of rural surveys, we present two SSW (Shoushi and SiWei) laser scanning systems for rapid topographic mapping: stop-and-go and electro-tricycle laser scanning systems. The objective of this paper is to evaluate whether laser scanning data collected by the developed SSW systems meet the accuracy requirements for rural homestead mapping. We investigated the performance of the two laser scanning systems on Ma’anshan Village, a small, typical village in Hubei Province, China. To obtain full coverage of the village, we fused the stop-and-go and electro-tricycle laser scanning data. The performance of the developed SSW systems is described by the results of building contours extracted from the fused data against the established building vector map. Full article
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Open AccessArticle
Assessing Land Degradation Dynamics and Distinguishing Human-Induced Changes from Climate Factors in the Three-North Shelter Forest Region of China
ISPRS Int. J. Geo-Inf. 2016, 5(9), 158; https://doi.org/10.3390/ijgi5090158 - 02 Sep 2016
Cited by 8 | Viewed by 2279
Abstract
Land degradation is a major threat to the sustainability of human habitation, and it is essential to assess it quantitatively. Assessment of the human-induced aspect is especially important for planning appropriate prevention measures. This paper used the Three-North Shelter Forest Program region as [...] Read more.
Land degradation is a major threat to the sustainability of human habitation, and it is essential to assess it quantitatively. Assessment of the human-induced aspect is especially important for planning appropriate prevention measures. This paper used the Three-North Shelter Forest Program region as the study area, and assessed the land degradation dynamic using a time series of summed normalized difference vegetation index (NDVI) based on a trend analysis of the Theil-Sen slope and Mann-Kendall test. The human-induced land degradation was separated from degradation driven by climate using the meteorological dataset through the residual trend (RESTREND) method for the period 1982–2006. The results showed that (1) the NDVI in the study area mainly exhibited an increasing trend, approximately 13.00% of the study area experienced significantly positive NDVI trends and 6.20% showed decline. Furthermore, (2) the correlation between the summed NDVI and precipitation was higher than the correlation between NDVI and temperature, suggesting that precipitation was the most essential factor that impacted NDVI dynamic in the study area; (3) The significant trends of vegetation by anthropogenic disturbances were detected, which were significant positive and negative trends of 11.93% and 6.19%, respectively. All of these findings enrich our knowledge of human activities that impact land degradation in arid or semi-arid regions and provide a scientific basis for the management of ecological restoration programs. Full article
(This article belongs to the Special Issue Spatiotemporal Computing for Sustainable Ecosystem)
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Open AccessArticle
A Labeling Model Based on the Region of Movability for Point-Feature Label Placement
ISPRS Int. J. Geo-Inf. 2016, 5(9), 159; https://doi.org/10.3390/ijgi5090159 - 01 Sep 2016
Cited by 6 | Viewed by 1555
Abstract
Automatic point-feature label placement (PFLP) is a fundamental task for map visualization. As the dominant solutions to the PFLP problem, fixed-position and slider models have been widely studied in previous research. However, the candidate labels generated with these models are set to certain [...] Read more.
Automatic point-feature label placement (PFLP) is a fundamental task for map visualization. As the dominant solutions to the PFLP problem, fixed-position and slider models have been widely studied in previous research. However, the candidate labels generated with these models are set to certain fixed positions or a specified track line for sliding. Thus, the whole surrounding space of a point feature is not sufficiently used for labeling. Hence, this paper proposes a novel label model based on the region of movability, which comes from plane collision detection theory. The model defines a complete conflict-free search space for label placement. On the premise of no conflict with the point, line, and area features, the proposed model utilizes the surrounding zone of the point feature to generate candidate label positions. By combining with heuristic search method, the model achieves high-quality label placement. In addition, the flexibility of the proposed model enables placing arbitrarily shaped labels. Full article
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Open AccessArticle
Assessing Patient bypass Behavior Using Taxi Trip Origin–Destination (OD) Data
ISPRS Int. J. Geo-Inf. 2016, 5(9), 157; https://doi.org/10.3390/ijgi5090157 - 01 Sep 2016
Cited by 5 | Viewed by 1858
Abstract
Many patients prefer to use the best hospitals even if there are one or more other hospitals closer to their homes; this behavior is called “hospital bypass behavior”. Because this behavior can be problematic in urban areas, it is important that it be [...] Read more.
Many patients prefer to use the best hospitals even if there are one or more other hospitals closer to their homes; this behavior is called “hospital bypass behavior”. Because this behavior can be problematic in urban areas, it is important that it be reduced. In this paper, the taxi GPS data of Beijing and Suzhou were used to measure hospital bypass behavior. The “bypass behavior index” (BBI) represents the bypass behavior for each hospital. The results indicated that the mean hospital bypass trip distance value ranges from 5.988 km to 9.754 km in Beijing and from 4.168 km to 10.283 km in Suzhou. In general, the bypass shares of both areas show a gradually increasing trend. The following hospitals exhibited significant patient bypass behavior: the 301 Hospital, Beijing Children’s Hospital, the Second Affiliated Hospital of Soochow University and the Suzhou Hospital of Traditional Chinese Medicine. The hospitals’ reputation, transport accessibility and spatial distribution were found to be the main factors affecting patient bypass behavior. Although the hospital bypass phenomena generally appeared to be more pronounced in Beijing, the bypass trip distances between hospitals were found to be more significant in Suzhou. Full article
(This article belongs to the Special Issue Big Data for Urban Informatics and Earth Observation)
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Open AccessArticle
Use of Social Media for the Detection and Analysis of Infectious Diseases in China
ISPRS Int. J. Geo-Inf. 2016, 5(9), 156; https://doi.org/10.3390/ijgi5090156 - 30 Aug 2016
Cited by 17 | Viewed by 1908
Abstract
Social media activity has become an important component of daily life for many people. Messages from Twitter (US) and Weibo (China) have shown their potential as important data sources for detecting and analyzing infectious diseases. Such emerging and dynamic new data sources allow [...] Read more.
Social media activity has become an important component of daily life for many people. Messages from Twitter (US) and Weibo (China) have shown their potential as important data sources for detecting and analyzing infectious diseases. Such emerging and dynamic new data sources allow us to predict how infectious diseases develop and evolve both spatially and temporally. We report the dynamics of dengue fever in China using messages from Weibo. We first extract and construct a list of keywords related to dengue fever in order to analyze how frequently these words appear in Weibo messages based on the Latent Dirichlet Allocation (LDA). Spatial analysis is then applied to detect how dengue fever cases cluster spatially and spread over time. Full article
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Open AccessReview
Review of Forty Years of Technological Changes in Geomatics toward the Big Data Paradigm
ISPRS Int. J. Geo-Inf. 2016, 5(9), 155; https://doi.org/10.3390/ijgi5090155 - 29 Aug 2016
Cited by 10 | Viewed by 2155
Abstract
Looking back at the last four decades, the technologies that have been developed for Earth observation and mapping can shed a light on the technologies that are trending today and on their challenges. Forty years ago, the first digital pictures decided the fate [...] Read more.
Looking back at the last four decades, the technologies that have been developed for Earth observation and mapping can shed a light on the technologies that are trending today and on their challenges. Forty years ago, the first digital pictures decided the fate of remote sensing, photogrammetric engineering, GIS, or, for short: of geomatics. This sudden wave of volumes of data triggered the research in fields that Big Data is plowing today: this paper will examine this transition. First, a rapid survey of the technology through the succession of selected terms, will help identify two main periods in the last four decades. Spatial information appears in 1970 with the preparation of Landsat, and Big Data appears in 2010. The method for exploring geomatics’ contribution to Big Data, is to examine each of the “Vs” that are used today to characterize the latter: volume, velocity, variety, visualization, value, veracity, validity, and variability. Geomatics has been confronted to each of these facets during the period. The discussion compares the answers offered early by geomatics, with the situation in Big Data today. Over a very large range of issues, from signal processing to the semantics of information, geomatics has made contributions to many data models and algorithms. Big Data now enables geographic information to be disseminated much more widely, and to benefit from new information sources, expanding through the Internet of Things towards a future Digital Earth. Some of the lessons learned during the four decades of geomatics can also be lessons for Big Data today, and for the future of geomatics. Full article
(This article belongs to the Special Issue Big Data for Urban Informatics and Earth Observation)
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Open AccessArticle
A New Simplification Approach Based on the Oblique-Dividing-Curve Method for Contour Lines
ISPRS Int. J. Geo-Inf. 2016, 5(9), 153; https://doi.org/10.3390/ijgi5090153 - 27 Aug 2016
Cited by 7 | Viewed by 1855
Abstract
As one of the key operators of automated map generalization, algorithms for the line simplification have been widely researched in the past decades. Although many of the currently available algorithms have revealed satisfactory simplification performances with certain data types and selected test areas, [...] Read more.
As one of the key operators of automated map generalization, algorithms for the line simplification have been widely researched in the past decades. Although many of the currently available algorithms have revealed satisfactory simplification performances with certain data types and selected test areas, it still remains a challenging task to solve the problems of (a) how to properly divide a cartographic line when it is too long to be dealt with directly; and (b) how to make adaptable parameterizations for various geo-data in different areas. In order to solve these two problems, a new line-simplification approach based on the Oblique-Dividing-Curve (ODC) method has been proposed in this paper. In this proposed model, one cartographic line is divided into a series of monotonic curves by the ODC method. Then, the curves are categorized into different groups according to their shapes, sizes and other geometric characteristics. The curves in different groups will trigger different strategies as well as the associated criteria for line simplification. Whenever a curve is simplified, the whole simplified cartographic line will be re-divided and the simplification process restarts again, i.e., the proposed simplification approach is iteratively operated until the final simplification result is achieved. Experiment evidence demonstrates that the proposed approach is able to handle the holistic bend-trend of the whole cartographic line during the simplification process and thereby provides considerably improved simplification performance with respect to maintaining the essential shape/salient characteristics and keeping the topological consistency. Moreover, the produced simplification results are not sensitive to the parameterizations of the proposed approach. Full article
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Open AccessArticle
Algebraic and Geometric Characterizations of Double-Cross Matrices of Polylines
ISPRS Int. J. Geo-Inf. 2016, 5(9), 152; https://doi.org/10.3390/ijgi5090152 - 27 Aug 2016
Cited by 1 | Viewed by 1649
Abstract
We study the double-cross matrix descriptions of polylines in the two-dimensional plane. The double-cross matrix is a qualitative description of polylines in which exact, quantitative information is given up in favour of directional information. First, we give an algebraic characterization of the double-cross [...] Read more.
We study the double-cross matrix descriptions of polylines in the two-dimensional plane. The double-cross matrix is a qualitative description of polylines in which exact, quantitative information is given up in favour of directional information. First, we give an algebraic characterization of the double-cross matrix of a polyline and derive some properties of double-cross matrices from this characterisation. Next, we give a geometric characterization of double-cross similarity of two polylines, using the technique of local carrier orders of polylines. We also identify the transformations of the plane that leave the double-cross matrix of all polylines in the two-dimensional plane invariant. Full article
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Open AccessArticle
A Spectral Signature Shape-Based Algorithm for Landsat Image Classification
ISPRS Int. J. Geo-Inf. 2016, 5(9), 154; https://doi.org/10.3390/ijgi5090154 - 26 Aug 2016
Cited by 1 | Viewed by 2047
Abstract
Land-cover datasets are crucial for earth system modeling and human-nature interaction research at local, regional and global scales. They can be obtained from remotely sensed data using image classification methods. However, in processes of image classification, spectral values have received considerable attention for [...] Read more.
Land-cover datasets are crucial for earth system modeling and human-nature interaction research at local, regional and global scales. They can be obtained from remotely sensed data using image classification methods. However, in processes of image classification, spectral values have received considerable attention for most classification methods, while the spectral curve shape has seldom been used because it is difficult to be quantified. This study presents a classification method based on the observation that the spectral curve is composed of segments and certain extreme values. The presented classification method quantifies the spectral curve shape and takes full use of the spectral shape differences among land covers to classify remotely sensed images. Using this method, classification maps from TM (Thematic mapper) data were obtained with an overall accuracy of 0.834 and 0.854 for two respective test areas. The approach presented in this paper, which differs from previous image classification methods that were mostly concerned with spectral “value” similarity characteristics, emphasizes the "shape" similarity characteristics of the spectral curve. Moreover, this study will be helpful for classification research on hyperspectral and multi-temporal images. Full article
(This article belongs to the Special Issue Recent Advances in Geodesy & Its Applications)
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Open AccessArticle
Method for Determining Appropriate Clustering Criteria of Location-Sensing Data
ISPRS Int. J. Geo-Inf. 2016, 5(9), 151; https://doi.org/10.3390/ijgi5090151 - 25 Aug 2016
Cited by 3 | Viewed by 1755
Abstract
Large quantities of location-sensing data are generated from location-based social network services. These data are provided as point properties with location coordinates acquired from a global positioning system or Wi-Fi signal. To show the point data on multi-scale map services, the data should [...] Read more.
Large quantities of location-sensing data are generated from location-based social network services. These data are provided as point properties with location coordinates acquired from a global positioning system or Wi-Fi signal. To show the point data on multi-scale map services, the data should be represented by clusters following a grid-based clustering method, in which an appropriate grid size should be determined. Currently, there are no criteria for determining the proper grid size, and the modifiable areal unit problem has been formulated for the purpose of addressing this issue. The method proposed in this paper is applies a hexagonal grid to geotagged Twitter point data, considering the grid size in terms of both quantity and quality to minimize the limitations associated with the modifiable areal unit problem. Quantitatively, we reduced the original Twitter point data by an appropriate amount using Töpfer’s radical law. Qualitatively, we maintained the original distribution characteristics using Moran’s I. Finally, we determined the appropriate sizes of clusters from zoom levels 9–13 by analyzing the distribution of data on the graphs. Based on the visualized clustering results, we confirm that the original distribution pattern is effectively maintained using the proposed method. Full article
(This article belongs to the Special Issue Location-Based Services)
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Open AccessArticle
The Socio-Spatial Distribution of Leisure Venues: A Case Study of Karaoke Bars in Nanjing, China
ISPRS Int. J. Geo-Inf. 2016, 5(9), 150; https://doi.org/10.3390/ijgi5090150 - 25 Aug 2016
Cited by 5 | Viewed by 2512
Abstract
With the development of service industry and cultural industry, urban leisure and entertainment services have become an important symbol of the city and the driving force of economic and social development. Karaoke, a typical form of urban entertainment, is immensely popular throughout China, [...] Read more.
With the development of service industry and cultural industry, urban leisure and entertainment services have become an important symbol of the city and the driving force of economic and social development. Karaoke, a typical form of urban entertainment, is immensely popular throughout China, and the number of karaoke bars is expected to keep growing in the future. However, little is known about their spatial distribution in the urban space and their association with other location-specific factors. Based on the geospatial entity data and business statistics data, we demonstrate a clustered pattern of 530 karaoke bars in Nanjing by means of point pattern analysis and cluster analysis in GIS. Furthermore, we identify the distribution of population, transportation network, and commercial centers as the three determinants underlying the formation of the pattern. Full article
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Open AccessArticle
Evaluating Temporal Analysis Methods Using Residential Burglary Data
ISPRS Int. J. Geo-Inf. 2016, 5(9), 148; https://doi.org/10.3390/ijgi5090148 - 25 Aug 2016
Cited by 5 | Viewed by 2445
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 [...] Read more.
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 e x t method perform significantly better than three of the traditional methods. Experiments show that the novel aoristic e x t 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. Full article
(This article belongs to the Special Issue Frontiers in Spatial and Spatiotemporal Crime Analytics)
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Open AccessCommunication
Defining Fitness-for-Use for Crowdsourced Points of Interest (POI)
ISPRS Int. J. Geo-Inf. 2016, 5(9), 149; https://doi.org/10.3390/ijgi5090149 - 24 Aug 2016
Cited by 9 | Viewed by 2249
Abstract
(1) Background: Due to the advent of Volunteered Geographic Information (VGI), large datasets of user-generated Points of Interest (POI) are now available. As with all VGI, however, there is uncertainty concerning data quality and fitness-for-use. Currently, the task of evaluating fitness-for-use of POI [...] Read more.
(1) Background: Due to the advent of Volunteered Geographic Information (VGI), large datasets of user-generated Points of Interest (POI) are now available. As with all VGI, however, there is uncertainty concerning data quality and fitness-for-use. Currently, the task of evaluating fitness-for-use of POI is left to the data user, with no guidance framework being available which is why this research proposes a generic approach to choose appropriate measures for assessing fitness-for-use of crowdsourced POI for different tasks. (2) Methods: POI are related to the higher-level concept of geo-atoms in order to identify and distinguish their two basic functions, geo-referencing and object-referencing. Then, for each of these functions, suitable measures of positional and thematic quality are developed based on existing quality indicators. (3) Results: Typical use cases of POI are evaluated with regards to their use of the two basic functions of POI, and allocated appropriate measures for fitness-for-use. The general procedure is illustrated on a brief practical example. (4) Conclusion: This research addresses the issue of fitness-for-use of POI on a higher conceptual level by relating it to more fundamental notions of geographical information representation. The results are expected to assist users of crowdsourced POI datasets in determining an appropriate method to evaluate fitness-for-use. Full article
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