Open AccessArticle
Closing the Skill Gap of Cloud CRM Application Services in Cloud Computing for Evaluating Big Data Solutions
ISPRS Int. J. Geo-Inf. 2016, 5(12), 227; doi:10.3390/ijgi5120227 (registering DOI) -
Abstract
Information systems (IS) continually motivate various improvements in the state-of-the-art of issues and solutions for advanced geo-information technologies in cloud computing. Reducing IS project risks and improving organizational performance has become an important issue. This study proposes a research framework, constructed from the
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Information systems (IS) continually motivate various improvements in the state-of-the-art of issues and solutions for advanced geo-information technologies in cloud computing. Reducing IS project risks and improving organizational performance has become an important issue. This study proposes a research framework, constructed from the Stimulus-Organism-Response (S-O-R) framework, in order to address the issues comprising the stimulus of project risk, the organism of project management, and the response of organizational performance for cloud service solutions. Cloud customer relationship management (cloud CRM) experts, based on cloud computing, with many years of project management experience, were selected for the interview sample in this study. Decision Making Trial and Evaluation Laboratory–based analytical network process (DEMATEL based-ANP, DANP) is a multiple-criteria decision-making (MCDM) analysis tool that does not have prior assumptions and it was used to experience the dynamic relationships among project risk, project management, and organizational performance. The study results include three directions: (a) Improving the internal business process performance can improve the efficiency of cloud CRM project processes and activities; (b) The emphasis on financial performance management can reduce the cost of a cloud CRM project so that the project can be completed within the approved budget; (c) Meeting user needs can improve user risk and reduce negative cloud CRM user experience. The scientific value of this study can be extended in order to study different projects, through research methods and frameworks, in order to explore project risk management and corporate performance improvements. Full article
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Open AccessArticle
Retrieval of Remote Sensing Images with Pattern Spectra Descriptors
ISPRS Int. J. Geo-Inf. 2016, 5(12), 228; doi:10.3390/ijgi5120228 (registering DOI) -
Abstract
The rapidly increasing volume of visual Earth Observation data calls for effective content based image retrieval solutions, specifically tailored for their high spatial resolution and heterogeneous content. In this paper, we address this issue with a novel local implementation of the well-known morphological
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The rapidly increasing volume of visual Earth Observation data calls for effective content based image retrieval solutions, specifically tailored for their high spatial resolution and heterogeneous content. In this paper, we address this issue with a novel local implementation of the well-known morphological descriptors called pattern spectra. They are computationally efficient histogram-like structures describing the global distribution of arbitrarily defined attributes of connected image components. Besides employing pattern spectra for the first time in this context, our main contribution lies in their dense calculation, at a local scale, thus enabling their combination with sophisticated visual vocabulary strategies. The Merced Landuse/Landcover dataset has been used for comparing the proposed strategy against alternative global and local content description methods, where the introduced approach is shown to yield promising performances. Full article
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Open AccessArticle
Describing Geospatial Assets in the Web of Data: A Metadata Management Scenario
ISPRS Int. J. Geo-Inf. 2016, 5(12), 229; doi:10.3390/ijgi5120229 (registering DOI) -
Abstract
Metadata management is an essential enabling factor for geospatial assets because discovery, retrieval, and actual usage of the latter are tightly bound to the quality of these descriptions. Unfortunately, the multi-faceted landscape of metadata formats, requirements, and conventions makes it difficult to identify
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Metadata management is an essential enabling factor for geospatial assets because discovery, retrieval, and actual usage of the latter are tightly bound to the quality of these descriptions. Unfortunately, the multi-faceted landscape of metadata formats, requirements, and conventions makes it difficult to identify editing tools that can be easily tailored to the specificities of a given project, workgroup, and Community of Practice. Our solution is a template-driven metadata editing tool that can be customised to any XML-based schema. Its output is constituted by standards-compliant metadata records that also have a semantics-aware counterpart eliciting novel exploitation techniques. Moreover, external data sources can easily be plugged in to provide autocompletion functionalities on the basis of the data structures made available on the Web of Data. Beside presenting the essentials on customisation of the editor by means of two use cases, we extend the methodology to the whole life cycle of geospatial metadata. We demonstrate the novel capabilities enabled by RDF-based metadata representation with respect to traditional metadata management in the geospatial domain. Full article
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Open AccessCorrection
Correction: Yin, J., et al. Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics Approach. ISPRS International Journal of Geo-Information 2016, 5, 187
ISPRS Int. J. Geo-Inf. 2016, 5(12), 226; doi:10.3390/ijgi5120226 (registering DOI) -
Open AccessArticle
An Improved WiFi/PDR Integrated System Using an Adaptive and Robust Filter for Indoor Localization
ISPRS Int. J. Geo-Inf. 2016, 5(12), 224; doi:10.3390/ijgi5120224 -
Abstract
Location-based services (LBS) are services offered through a mobile device that take into account a device’s geographical location. To provide position information for these services, location is a key process. GNSS (Global Navigation Satellite System) can provide sub-meter accuracy in open-sky areas using
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Location-based services (LBS) are services offered through a mobile device that take into account a device’s geographical location. To provide position information for these services, location is a key process. GNSS (Global Navigation Satellite System) can provide sub-meter accuracy in open-sky areas using satellite signals. However, for indoor and dense urban environments, the accuracy deteriorates significantly because of weak signals and dense multipaths. The situation becomes worse in indoor environments where the GNSS signals are unreliable or totally blocked. To improve the accuracy of indoor positioning for location-based services, an improved WiFi/Pedestrian Dead Reckoning (PDR) integrated positioning and navigation system using an adaptive and robust filter is presented. The adaptive filter is based on scenario and motion state recognition and the robust filter is based on the Mahalanobis distance. They are combined and used in the WiFi/PDR integrated system to weaken the effect of gross errors on the dynamic and observation models. To validate their performance in the WiFi/PDR integrated system, a real indoor localization experiment is conducted. The results indicate that the adaptive filter is better able to adapt to the circumstances of the dynamic model by adjusting the covariance of the process noise and the robust Kalman filter is able to mitigate the harmful effect of gross errors from the WiFi positioning. Full article
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Open AccessArticle
A Biophysical Image Compositing Technique for the Global-Scale Extraction and Mapping of Barren Lands
ISPRS Int. J. Geo-Inf. 2016, 5(12), 225; doi:10.3390/ijgi5120225 -
Abstract
As the barren lands play a key role in the interaction between land cover dynamics and climate system, an efficient methodology for the global-scale extraction and mapping of the barren lands is important. The discriminative potential of the existing soil/bareness indexes was assessed
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As the barren lands play a key role in the interaction between land cover dynamics and climate system, an efficient methodology for the global-scale extraction and mapping of the barren lands is important. The discriminative potential of the existing soil/bareness indexes was assessed by collecting globally distributed reference data belonging to major land cover types. The existing soil/bareness indexes parameterized at the local scale did not work satisfactorily everywhere at the global level. A new technique called the Biophysical Image Composite (BIC) is proposed in the research by exploiting time-series of the multi-spectral data to capture global-scale barren land attributes effectively. The BIC is a false color composite image made up of Normalized Difference Vegetation Index (NDVI), short wave infrared reflectance, and green reflectance, which were specially selected from the highest vegetation activity period by avoiding signals from the seasonal snowfall. The drastic contrast between the barren lands and vegetation as exhibited by the BIC provides a robust extraction and mapping of the barren lands, and facilitates its visual interpretation. Random Forests based supervised classification approach was applied on the BIC for the mapping of global barren lands. A new global barren land cover map of year 2013 was produced with high accuracy. The comparison of the resulted map with an existing map of the same year showed a substantial discrepancy between two maps due to methodological variation. To cope with this problem, the BIC based mapping methodology, with a special account of the land surface phenological changes, is suggested to standardize the global-scale estimates and mapping of the barren lands. Full article
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Open AccessArticle
Spatiotemporal Information Extraction from a Historic Expedition Gazetteer
ISPRS Int. J. Geo-Inf. 2016, 5(12), 221; doi:10.3390/ijgi5120221 (registering DOI) -
Abstract
Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions
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Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions involve movements in space that can be represented by triplet features (location, time and description). However, such features are implicit and innate parts of textual documents. Extracting the geospatial information from these documents requires understanding the contextualized entities in the text. To this end, we developed a semi-automated framework that has multiple Information Retrieval and Natural Language Processing components to extract the spatiotemporal information from a two-volume historic expedition gazetteer. Our framework has three basic components, namely, the Text Preprocessor, the Gazetteer Processing Machine and the JAPE (Java Annotation Pattern Engine) Transducer. We used the Brazilian Ornithological Gazetteer as an experimental dataset and extracted the spatial and temporal entities from entries that refer to three expeditioners’ site visits (which took place between 1910 and 1926) and mapped the trajectory of each expedition using the extracted information. Finally, one of the mapped trajectories was manually compared with a historical reference map of that expedition to assess the reliability of our framework. Full article
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Open AccessArticle
Indoor Multi-Dimensional Location GML and Its Application for Ubiquitous Indoor Location Services
ISPRS Int. J. Geo-Inf. 2016, 5(12), 220; doi:10.3390/ijgi5120220 (registering DOI) -
Abstract
The Open Geospatial Consortium (OGC) Geography Markup Language (GML) standard provides basic types and a framework for defining geo-informational data models such as CityGML and IndoorGML, which provide standard information models for 3D city modelling and lightweight indoor network navigation. Location information, which
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The Open Geospatial Consortium (OGC) Geography Markup Language (GML) standard provides basic types and a framework for defining geo-informational data models such as CityGML and IndoorGML, which provide standard information models for 3D city modelling and lightweight indoor network navigation. Location information, which is the semantic engine that fuses big geo-information data, is however, discarded in these standards. The Chinese national standard of Indoor Multi-Dimensional Location GML (IndoorLocationGML) presented in this study can be used in ubiquitous indoor location intelligent applications for people and robots. IndoorLocationGML is intended as an indoor multi-dimensional location information model and exchange data format standard, mainly for indoor positioning and navigation. This paper introduces the standard’s main features: (1) terminology; (2) indoor location information model using a Unified Modeling Language (UML) class diagram; (3) indoor location information markup language based on GML; and (4) use cases. A typical application of the standard is then discussed. This standard is applicable to the expression, storage, and distribution of indoor multi-dimensional location information, and to the seamless integration of indoor–outdoor location information. The reference and basis are therefore relevant to publishers, managers, users, and developers of indoor navigation and location-based services (LBS). Full article
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Open AccessArticle
Adjustment and Assessment of the Measurements of Low and High Sampling Frequencies of GPS Real-Time Monitoring of Structural Movement
ISPRS Int. J. Geo-Inf. 2016, 5(12), 222; doi:10.3390/ijgi5120222 (registering DOI) -
Abstract
Global Positioning System (GPS) structural health monitoring data collection is one of the important systems in structure movement monitoring. However, GPS measurement error and noise limit the application of such systems. Many attempts have been made to adjust GPS measurements and eliminate their
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Global Positioning System (GPS) structural health monitoring data collection is one of the important systems in structure movement monitoring. However, GPS measurement error and noise limit the application of such systems. Many attempts have been made to adjust GPS measurements and eliminate their errors. Comparing common nonlinear methods used in the adjustment of GPS positioning for the monitoring of structures is the main objective of this study. Nonlinear Adaptive-Recursive Least Square (RLS), extended Kalman filter (EKF), and wavelet principal component analysis (WPCA) are presented and applied to improve the quality of GPS time series observations. Two real monitoring observation systems for the Mansoura railway and long-span Yonghe bridges are utilized to examine suitable methods used to assess bridge behavior under different load conditions. From the analysis of the results, it is concluded that the wavelet principal component is the best method to smooth low and high GPS sampling frequency observations. The evaluation of the bridges reveals the ability of the GPS systems to detect the behavior and damage of structures in both the time and frequency domains. Full article
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Open AccessArticle
A Novel Evaluation Approach for Line Simplification Algorithms towards Vector Map Visualization
ISPRS Int. J. Geo-Inf. 2016, 5(12), 223; doi:10.3390/ijgi5120223 (registering DOI) -
Abstract
Line simplification is an important method in the context of cartographic generalization, which is helpful for improving the visualization of digital vector maps. The evaluation method for the simplification algorithms is still an open issue when facing applications of vector data, including progressive
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Line simplification is an important method in the context of cartographic generalization, which is helpful for improving the visualization of digital vector maps. The evaluation method for the simplification algorithms is still an open issue when facing applications of vector data, including progressive transmission, web mapping, and so on. This paper proposes a novel evaluation approach for line simplification algorithms based on several factors towards vector map visualization, including the features of displays, map scales, and the ability of the human eye to distinguish pixels. In order to ensure the evaluation of the line simplification algorithms is conducted under the consistent strength of simplification, a measurement approach for the difference between an original line and its simplified one is proposed in this study, and the method of solving the appropriate simplification threshold is presented. With this method, four simplification algorithms are evaluated at five map scales using three evaluation indicators: standard deviation, compression ratio, and simplification time. The experiment and results show the evaluation approach in this study is feasible, and represents a good means in which to facilitate the application of line simplification towards progressive transmission and visualization of vector maps. Full article
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Open AccessFeature PaperArticle
Geospatial Analysis of the Building Heat Demand and Distribution Losses in a District Heating Network
ISPRS Int. J. Geo-Inf. 2016, 5(12), 219; doi:10.3390/ijgi5120219 -
Abstract
The district heating (DH) demand of various systems has been simulated in several studies. Most studies focus on the temporal aspects rather than the spatial component. In this study, the DH demand for a medium-sized DH network in a city in southern Germany
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The district heating (DH) demand of various systems has been simulated in several studies. Most studies focus on the temporal aspects rather than the spatial component. In this study, the DH demand for a medium-sized DH network in a city in southern Germany is simulated and analyzed in a spatially explicit approach. Initially, buildings are geo-located and attributes obtained from various sources including building type, ground area, and number of stories are merged. Thereafter, the annual primary energy demand for heating and domestic hot water is calculated for individual buildings. Subsequently, the energy demand is aggregated on the segment level of an existing DH network and the water flow is routed through the system. The simulation results show that the distribution losses are overall the highest at the end segments (given in percentage terms). However, centrally located pipes with a low throughflow are also simulated to have high losses. The spatial analyses are not only useful when addressing the current demand. Based on a scenario taking into account the refurbishment of buildings and a decentralization of energy production, the future demand was also addressed. Due to lower demand, the distribution losses given in percentage increase under such conditions. Full article
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Open AccessArticle
Assessing Essential Qualities of Urban Space with Emotional and Visual Data Based on GIS Technique
ISPRS Int. J. Geo-Inf. 2016, 5(11), 218; doi:10.3390/ijgi5110218 -
Abstract
Finding a method to evaluate people’s emotional responses to urban spaces in a valid and objective way is fundamentally important for urban design practices and related policy making. Analysis of the essential qualities of urban space could be made both more effective and
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Finding a method to evaluate people’s emotional responses to urban spaces in a valid and objective way is fundamentally important for urban design practices and related policy making. Analysis of the essential qualities of urban space could be made both more effective and more accurate using innovative information techniques that have become available in the era of big data. This study introduces an integrated method based on geographical information systems (GIS) and an emotion-tracking technique to quantify the relationship between people’s emotional responses and urban space. This method can evaluate the degree to which people’s emotional responses are influenced by multiple urban characteristics such as building shapes and textures, isovist parameters, visual entropy, and visual fractals. The results indicate that urban spaces may influence people’s emotional responses through both spatial sequence arrangements and shifting scenario sequences. Emotional data were collected with body sensors and GPS devices. Spatial clustering was detected to target effective sampling locations; then, isovists were generated to extract building textures. Logistic regression and a receiver operating characteristic analysis were used to determine the key isovist parameters and the probabilities that they influenced people’s emotion. Finally, based on the results, we make some suggestions for design professionals in the field of urban space optimization. Full article
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Open AccessArticle
Towards a Protocol for the Collection of VGI Vector Data
ISPRS Int. J. Geo-Inf. 2016, 5(11), 217; doi:10.3390/ijgi5110217 -
Abstract
A protocol for the collection of vector data in Volunteered Geographic Information (VGI) projects is proposed. VGI is a source of crowdsourced geographic data and information which is comparable, and in some cases better, than equivalent data from National Mapping Agencies (NMAs) and
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A protocol for the collection of vector data in Volunteered Geographic Information (VGI) projects is proposed. VGI is a source of crowdsourced geographic data and information which is comparable, and in some cases better, than equivalent data from National Mapping Agencies (NMAs) and Commercial Surveying Companies (CSC). However, there are many differences in how NMAs and CSC collect, analyse, manage and distribute geographic information to that of VGI projects. NMAs and CSC make use of robust and standardised data collection protocols whilst VGI projects often provide guidelines rather than rigorous data collection specifications. The proposed protocol addresses formalising the collection and creation of vector data in VGI projects in three principal ways: by manual vectorisation; field survey; and reuse of existing data sources. This protocol is intended to be generic rather than being linked to any specific VGI project. We believe that this is the first protocol for VGI vector data collection that has been formally described in the literature. Consequently, this paper shall serve as a starting point for on-going development and refinement of the protocol. Full article
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Open AccessArticle
Belgium through the Lens of Rail Travel Requests: Does Geography Still Matter?
ISPRS Int. J. Geo-Inf. 2016, 5(11), 216; doi:10.3390/ijgi5110216 -
Abstract
This paper uses on-line railway travel requests from the iRail schedule-finder application for assessing the suitability of that kind of big data for transportation planning and to examine the temporal and regional variations of the travel demand by train in Belgium. Travel requests
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This paper uses on-line railway travel requests from the iRail schedule-finder application for assessing the suitability of that kind of big data for transportation planning and to examine the temporal and regional variations of the travel demand by train in Belgium. Travel requests are collected over a two-month period and consist of origin-destination flows between stations operated by the Belgian national railway company in 2016. The Louvain method is applied to detect communities of tightly-connected stations. Results show the influence of both the urban and network structures on the spatial organization of the clusters. We also further discuss the implications of the observed temporal and regional variations of these clusters for transportation travel demand and planning. Full article
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Open AccessArticle
Morphological PDEs on Graphs for Image Processing on Surfaces and Point Clouds
ISPRS Int. J. Geo-Inf. 2016, 5(11), 213; doi:10.3390/ijgi5110213 -
Abstract
Partial Differential Equations (PDEs)-based morphology offers a wide range of continuous operators to address various image processing problems. Most of these operators are formulated as Hamilton–Jacobi equations or curve evolution level set and morphological flows. In our previous works, we have proposed a
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Partial Differential Equations (PDEs)-based morphology offers a wide range of continuous operators to address various image processing problems. Most of these operators are formulated as Hamilton–Jacobi equations or curve evolution level set and morphological flows. In our previous works, we have proposed a simple method to solve PDEs on point clouds using the framework of PdEs (Partial difference Equations) on graphs. In this paper, we propose to apply a large class of morphological-based operators on graphs for processing raw 3D point clouds and extend their applications for the processing of colored point clouds of geo-informatics 3D data. Through illustrations, we show that this simple framework can be used in the resolution of many applications for geo-informatics purposes. Full article
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Open AccessArticle
Efficient Geo-Computational Algorithms for Constructing Space-Time Prisms in Road Networks
ISPRS Int. J. Geo-Inf. 2016, 5(11), 214; doi:10.3390/ijgi5110214 -
Abstract
The Space-time prism (STP) is a key concept in time geography for analyzing human activity-travel behavior under various Space-time constraints. Most existing time-geographic studies use a straightforward algorithm to construct STPs in road networks by using two one-to-all shortest path searches. However, this
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The Space-time prism (STP) is a key concept in time geography for analyzing human activity-travel behavior under various Space-time constraints. Most existing time-geographic studies use a straightforward algorithm to construct STPs in road networks by using two one-to-all shortest path searches. However, this straightforward algorithm can introduce considerable computational overhead, given the fact that accessible links in a STP are generally a small portion of the whole network. To address this issue, an efficient geo-computational algorithm, called NTP-A*, is proposed. The proposed NTP-A* algorithm employs the A* and branch-and-bound techniques to discard inaccessible links during two shortest path searches, and thereby improves the STP construction performance. Comprehensive computational experiments are carried out to demonstrate the computational advantage of the proposed algorithm. Several implementation techniques, including the label-correcting technique and the hybrid link-node labeling technique, are discussed and analyzed. Experimental results show that the proposed NTP-A* algorithm can significantly improve STP construction performance in large-scale road networks by a factor of 100, compared with existing algorithms. Full article
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Open AccessArticle
An Effective NoSQL-Based Vector Map Tile Management Approach
ISPRS Int. J. Geo-Inf. 2016, 5(11), 215; doi:10.3390/ijgi5110215 -
Abstract
Within a digital map service environment, the rapid growth of Spatial Big-Data is driving new requirements for effective mechanisms for massive online vector map tile processing. The emergence of Not Only SQL (NoSQL) databases has resulted in a new data storage and management
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Within a digital map service environment, the rapid growth of Spatial Big-Data is driving new requirements for effective mechanisms for massive online vector map tile processing. The emergence of Not Only SQL (NoSQL) databases has resulted in a new data storage and management model for scalable spatial data deployments and fast tracking. They better suit the scenario of high-volume, low-latency network map services than traditional standalone high-performance computer (HPC) or relational databases. In this paper, we propose a flexible storage framework that provides feasible methods for tiled map data parallel clipping and retrieval operations within a distributed NoSQL database environment. We illustrate the parallel vector tile generation and querying algorithms with the MapReduce programming model. Three different processing approaches, including local caching, distributed file storage, and the NoSQL-based method, are compared by analyzing the concurrent load and calculation time. An online geological vector tile map service prototype was developed to embed our processing framework in the China Geological Survey Information Grid. Experimental results show that our NoSQL-based parallel tile management framework can support applications that process huge volumes of vector tile data and improve performance of the tiled map service. Full article
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Open AccessArticle
Generating Orthorectified Multi-Perspective 2.5D Maps to Facilitate Web GIS-Based Visualization and Exploitation of Massive 3D City Models
ISPRS Int. J. Geo-Inf. 2016, 5(11), 212; doi:10.3390/ijgi5110212 -
Abstract
2.5D map is a convenient and efficient approach to exploiting a massive three-dimensional (3D) city model in web GIS. With the rapid development of oblique airborne photogrammetry and photo-based 3D reconstruction, 3D city models are becoming more and more accessible. 3D Geographic Information
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2.5D map is a convenient and efficient approach to exploiting a massive three-dimensional (3D) city model in web GIS. With the rapid development of oblique airborne photogrammetry and photo-based 3D reconstruction, 3D city models are becoming more and more accessible. 3D Geographic Information System (GIS) can support the interactive visualization of massive 3D city models on various platforms and devices. However, the value and accessibility of existing 3D city models can be augmented by integrating them into web-based two-dimensional (2D) GIS applications. In this paper, we present a step-by-step workflow for generating orthorectified oblique images (2.5D maps) from massive 3D city models. The proposed framework can produce 2.5D maps from an arbitrary perspective, defined by the elevation angle and azimuth angle of a virtual orthographic camera. We demonstrate how 2.5D maps can benefit web-based visualization and exploitation of massive 3D city models. We conclude that a 2.5D map is a compact data representation optimized for web data streaming of 3D city models and that geometric analysis of buildings can be effectively conducted on 2.5D maps. Full article
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Open AccessArticle
Spatial Air Index Based on Largest Empty Rectangles for Non-Flat Wireless Broadcast in Pervasive Computing
ISPRS Int. J. Geo-Inf. 2016, 5(11), 211; doi:10.3390/ijgi5110211 -
Abstract
In pervasive computing, location-based services (LBSs) are valuable for mobile clients based on their current locations. LBSs use spatial window queries to enable useful applications for mobile clients. Based on skewed access patterns of mobile clients, non-flat wireless broadcast has been shown to
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In pervasive computing, location-based services (LBSs) are valuable for mobile clients based on their current locations. LBSs use spatial window queries to enable useful applications for mobile clients. Based on skewed access patterns of mobile clients, non-flat wireless broadcast has been shown to efficiently disseminate spatial objects to mobile clients. In this paper, we consider a scenario in which spatial objects are broadcast to mobile clients over a wireless channel in a non-flat broadcast manner to process window queries. For such a scenario, we propose an efficient spatial air index method to handle window query access in non-flat wireless broadcast environments. The concept of largest empty rectangles is used to avoid unnecessary examination of the broadcast content, thus reducing the processing time for window queries. Simulation results show that the proposed spatial air index method outperforms the existing methods under various settings. Full article
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Open AccessArticle
Analysis of Attraction Features of Tourism Destinations in a Mega-City Based on Check-in Data Mining—A Case Study of Shenzhen, China
ISPRS Int. J. Geo-Inf. 2016, 5(11), 210; doi:10.3390/ijgi5110210 -
Abstract
Location-based service information, provided by social networks, provides new data sources and perspectives to research tourism activities, especially in highly populated mega-cities. Based on three years (2012–2014) of approximately 340,000 check-in records collected from Sina micro-blog at 86 tourist attractions in Shenzhen, a
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Location-based service information, provided by social networks, provides new data sources and perspectives to research tourism activities, especially in highly populated mega-cities. Based on three years (2012–2014) of approximately 340,000 check-in records collected from Sina micro-blog at 86 tourist attractions in Shenzhen, a first-tier city in southern China, we conducted a comprehensive study of the attraction features involving different aspects, such as tourist source, duration of stay, check-in activity index, and attraction correlation degree. The results showed that (1) theme parks established in the early 1990s were the most popular tourist attractions in Shenzhen, but a negative trend was detected in the check-in population; (2) compared with check-in times from surrounding activities and the kernel density of tourists, most destinations in Shenzhen showed a lack of attraction, failing to make the most of their geographic accessibility; and (3) the homogeneity and inconvenient traffic conditions of major tourist destinations leading to the construction of a tourism tour chain has become a challenge. The results of this study demonstrate the potential of big-data mining and provide valuable insights into tourism market design and management in mega-cities. Full article
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