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ISPRS Int. J. Geo-Inf., Volume 4, Issue 3 (September 2015) , Pages 1033-1773

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Open AccessEditorial
Spatial Analysis as a Transformative Technology for Decision-Making in Environmental Domains
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1770-1773; https://doi.org/10.3390/ijgi4031770 - 16 Sep 2015
Viewed by 1643
Abstract
Mankind is faced with many ongoing environmental challenges including climate change, losses in biodiversity, deforestation, increased soil erosion, and air and water pollution, to name but a few. [...] Full article
(This article belongs to the Special Issue Spatial Analysis for Environmental Applications)
Open AccessArticle
Land Cover Mapping Analysis and Urban Growth Modelling Using Remote Sensing Techniques in Greater Cairo Region—Egypt
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1750-1769; https://doi.org/10.3390/ijgi4031750 - 14 Sep 2015
Cited by 36 | Viewed by 3681
Abstract
This study modeled the urban growth in the Greater Cairo Region (GCR), one of the fastest growing mega cities in the world, using remote sensing data and ancillary data. Three land use land cover (LULC) maps (1984, 2003 and 2014) were produced from [...] Read more.
This study modeled the urban growth in the Greater Cairo Region (GCR), one of the fastest growing mega cities in the world, using remote sensing data and ancillary data. Three land use land cover (LULC) maps (1984, 2003 and 2014) were produced from satellite images by using Support Vector Machines (SVM). Then, land cover changes were detected by applying a high level mapping technique that combines binary maps (change/no-change) and post classification comparison technique. The spatial and temporal urban growth patterns were analyzed using selected statistical metrics developed in the FRAGSTATS software. Major transitions to urban were modeled to predict the future scenarios for year 2025 using Land Change Modeler (LCM) embedded in the IDRISI software. The model results, after validation, indicated that 14% of the vegetation and 4% of the desert in 2014 will be urbanized in 2025. The urban areas within a 5-km buffer around: the Great Pyramids, Islamic Cairo and Al-Baron Palace were calculated, highlighting an intense urbanization especially around the Pyramids; 28% in 2014 up to 40% in 2025. Knowing the current and estimated urbanization situation in GCR will help decision makers to adjust and develop new plans to achieve a sustainable development of urban areas and to protect the historical locations. Full article
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Open AccessCommunication
Rethinking Engagement: Innovations in How Humanitarians Explore Geoinformation
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1729-1749; https://doi.org/10.3390/ijgi4031729 - 11 Sep 2015
Cited by 3 | Viewed by 2451
Abstract
When humanitarian workers embark on learning and dialogue for linking geoinformation to disaster management, the activities they confront are usually more difficult than interesting. How to accelerate the acquisition and deployment of skills and tools for spatial data collection and analysis, given the [...] Read more.
When humanitarian workers embark on learning and dialogue for linking geoinformation to disaster management, the activities they confront are usually more difficult than interesting. How to accelerate the acquisition and deployment of skills and tools for spatial data collection and analysis, given the increasingly unmanageable workload of humanitarians? How to engage practitioners in experiencing the value and limitations of newly available tools? This paper offers an innovative approach to immerse disaster managers in geoinformation: participatory games that enable stakeholders to experience playable system dynamic models linking geoinformation, decisions and consequences in a way that is both serious and fun. A conceptual framework outlines the foundations of experiential learning through gameplay, with clear connections to a well-established risk management framework. Two case studies illustrate this approach: one involving flood management in the Zambezi river in southern Africa through the game UpRiver (in both physical and digital versions), and another pertaining to World Bank training on open data for resilience that combines applied improvisation activities with the need to understand and deploy software tools like Open Street Map and InaSAFE to manage school investments and schoolchildren evacuation in a simulated flood scenario for the city of La Plata, Argentina. Full article
(This article belongs to the Special Issue Geoinformation for Disaster Risk Management)
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Open AccessArticle
Dynamically Integrating OSM Data into a Borderland Database
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1707-1728; https://doi.org/10.3390/ijgi4031707 - 08 Sep 2015
Cited by 6 | Viewed by 2038
Abstract
Spatial data are fundamental for borderland analyses of geography, natural resources, demography, politics, economy, and culture. As the spatial data used in borderland research usually cover the borderland regions of several neighboring countries, it is difficult for anyone research institution of government to [...] Read more.
Spatial data are fundamental for borderland analyses of geography, natural resources, demography, politics, economy, and culture. As the spatial data used in borderland research usually cover the borderland regions of several neighboring countries, it is difficult for anyone research institution of government to collect them. Volunteered Geographic Information (VGI) is a highly successful method for acquiring timely and detailed global spatial data at a very low cost. Therefore, VGI is a reasonable source of borderland spatial data. OpenStreetMap (OSM) is known as the most successful VGI resource. However, OSM's data model is far different from the traditional geographic information model. Thus, the OSM data must be converted in the scientist’s customized data model. Because the real world changes rapidly, the converted data must be updated incrementally. Therefore, this paper presents a method used to dynamically integrate OSM data into the borderland database. In this method, a basic transformation rule base is formed by comparing the OSM Map Feature description document and the destination model definitions. Using the basic rules, the main features can be automatically converted to the destination model. A human-computer interaction model transformation and a rule/automatic-remember mechanism are developed to interactively transfer the unusual features that cannot be transferred by the basic rules to the target model and to remember the reusable rules automatically. To keep the borderland database current, the global OsmChange daily diff file is used to extract the change-only information for the research region. To extract the changed objects in the region under study, the relationship between the changed object and the research region is analyzed considering the evolution of the involved objects. In addition, five rules are determined to select the objects and integrate the changed objects with multi-versions over time. The objects’ change-type evolution is analyzed, and seven rules are used to determine the change-type of the changed objects. Based on these rules and algorithms, we programmed an automatic (or semi-automatic) integrating and updating prototype system for the borderland database. The developed system was intensively tested using OSM data for Vietnam and Pakistan as the experimental data. Full article
(This article belongs to the Special Issue Borderlands Modeling and Analysis)
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Open AccessArticle
OGC Consensus: How Successful Standards Are Made
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1693-1706; https://doi.org/10.3390/ijgi4031693 - 07 Sep 2015
Cited by 5 | Viewed by 2168
Abstract
This paper describes the history, background, and current status of the Open Geospatial Consortium (OGC) standards development consensus process. The roots of the formation of the OGC lie in the early 1990s when a very strong market requirement for exchanging GIS data content [...] Read more.
This paper describes the history, background, and current status of the Open Geospatial Consortium (OGC) standards development consensus process. The roots of the formation of the OGC lie in the early 1990s when a very strong market requirement for exchanging GIS data content was clearly stated. At that time, each GIS vendor had their own formats for publishing and/or exchanging their GIS data. There was no mechanism or organization that provided a forum for the GIS vendors and GIS data users to collaborate and agree on how to share GIS data. That requirement, along with the vision of a few individuals, led to the formation of the OGC. This paper describes the early development of the consensus process in the OGC, how this process has evolved over time, why consensus is so important for defining open standards that are implemented in the marketplace, and the future of the OGC consensus process. Full article
(This article belongs to the Special Issue 20 Years of OGC: Open Geo-Data, Software, and Standards)
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Open AccessArticle
Towards Measuring and Visualizing Sustainable National Power—A Case Study of China and Neighboring Countries
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1672-1692; https://doi.org/10.3390/ijgi4031672 - 02 Sep 2015
Cited by 1 | Viewed by 2501
Abstract
This paper presents a new perspective of national power—sustainable national power (SNP)—emphasizing both the traditional comprehensive national power (CNP) and social and environmental sustainability. We propose a measurement to quantify the SNP based on the measurement of comprehensive national power [...] Read more.
This paper presents a new perspective of national power—sustainable national power (SNP)—emphasizing both the traditional comprehensive national power (CNP) and social and environmental sustainability. We propose a measurement to quantify the SNP based on the measurement of comprehensive national power and a sustainable adjusted index. In addition, density-equalizing maps are adopted to visualize the sustainable national power of countries in order to gain a better understanding for its current state and future development from a cartographic perspective. China and its neighboring countries are selected as a case study area. The results show that China outperforms other countries in most of the CNP dimensions but performs poorly in various SNP-adjusted dimensions within the study area. The composite score shows that China is with the highest regional SNP, followed by Japan, Russia, South Korea and India. Furthermore, time series of cartograms reveal evidence showing power transitions among countries. In addition, the effectiveness of cartograms for cartographic communication is discussed. Full article
(This article belongs to the Special Issue Borderlands Modeling and Analysis)
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Open AccessArticle
Quality Evaluation of VGI Using Authoritative Data—A Comparison with Land Use Data in Southern Germany
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1657-1671; https://doi.org/10.3390/ijgi4031657 - 02 Sep 2015
Cited by 40 | Viewed by 3771
Abstract
Volunteered Geographic Information (VGI) such as data derived from the OpenStreetMap (OSM) project is a popular data source for freely available geographic data. Normally, untrained contributors gather these data. This fact is frequently a cause of concern regarding the quality and usability of [...] Read more.
Volunteered Geographic Information (VGI) such as data derived from the OpenStreetMap (OSM) project is a popular data source for freely available geographic data. Normally, untrained contributors gather these data. This fact is frequently a cause of concern regarding the quality and usability of such data. In this study, the quality of OSM land use and land cover (LULC) data is investigated for an area in southern Germany. Two spatial data quality elements, thematic accuracy and completeness are addressed by comparing the OSM data with an authoritative German reference dataset. The results show that the kappa value indicates a substantial agreement between the OSM and the authoritative dataset. Nonetheless, for our study region, there are clear variations between the LULC classes. Forest covers a large area and shows both a high OSM completeness (97.6%) and correctness (95.1%). In contrast, farmland also covers a large area, but for this class OSM shows a low completeness value (45.9%) due to unmapped areas. Additionally, the results indicate that a high population density, as present in urbanized areas, seems to denote a higher strength of agreement between OSM and the DLM (Digital Landscape Model). However, a low population density does not necessarily imply a low strength of agreement. Full article
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Open AccessArticle
Walk This Way: Improving Pedestrian Agent-Based Models through Scene Activity Analysis
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1627-1656; https://doi.org/10.3390/ijgi4031627 - 02 Sep 2015
Cited by 8 | Viewed by 2333
Abstract
Pedestrian movement is woven into the fabric of urban regions. With more people living in cities than ever before, there is an increased need to understand and model how pedestrians utilize and move through space for a variety of applications, ranging from urban [...] Read more.
Pedestrian movement is woven into the fabric of urban regions. With more people living in cities than ever before, there is an increased need to understand and model how pedestrians utilize and move through space for a variety of applications, ranging from urban planning and architecture to security. Pedestrian modeling has been traditionally faced with the challenge of collecting data to calibrate and validate such models of pedestrian movement. With the increased availability of mobility datasets from video surveillance and enhanced geolocation capabilities in consumer mobile devices we are now presented with the opportunity to change the way we build pedestrian models. Within this paper we explore the potential that such information offers for the improvement of agent-based pedestrian models. We introduce a Scene- and Activity-Aware Agent-Based Model (SA2-ABM), a method for harvesting scene activity information in the form of spatiotemporal trajectories, and incorporate this information into our models. In order to assess and evaluate the improvement offered by such information, we carry out a range of experiments using real-world datasets. We demonstrate that the use of real scene information allows us to better inform our model and enhance its predictive capabilities. Full article
(This article belongs to the Special Issue Advances in Spatio-Temporal Data Analysis and Mining)
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Open AccessArticle
Movement Pattern Analysis Based on Sequence Signatures
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1605-1626; https://doi.org/10.3390/ijgi4031605 - 02 Sep 2015
Cited by 2 | Viewed by 2540
Abstract
Increased affordability and deployment of advanced tracking technologies have led researchers from various domains to analyze the resulting spatio-temporal movement data sets for the purpose of knowledge discovery. Two different approaches can be considered in the analysis of moving objects: quantitative analysis and [...] Read more.
Increased affordability and deployment of advanced tracking technologies have led researchers from various domains to analyze the resulting spatio-temporal movement data sets for the purpose of knowledge discovery. Two different approaches can be considered in the analysis of moving objects: quantitative analysis and qualitative analysis. This research focuses on the latter and uses the qualitative trajectory calculus (QTC), a type of calculus that represents qualitative data on moving point objects (MPOs), and establishes a framework to analyze the relative movement of multiple MPOs. A visualization technique called sequence signature (SESI) is used, which enables to map QTC patterns in a 2D indexed rasterized space in order to evaluate the similarity of relative movement patterns of multiple MPOs. The applicability of the proposed methodology is illustrated by means of two practical examples of interacting MPOs: cars on a highway and body parts of a samba dancer. The results show that the proposed method can be effectively used to analyze interactions of multiple MPOs in different domains. Full article
(This article belongs to the Special Issue Multi-Dimensional Spatial Data Modeling)
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Open AccessArticle
Spatio-Temporal Analysis of Spatial Accessibility to Primary Health Care in Bhutan
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1584-1604; https://doi.org/10.3390/ijgi4031584 - 01 Sep 2015
Cited by 15 | Viewed by 2846
Abstract
Geographic information systems (GIS) can be effectively utilized to carry out spatio-temporal analysis of spatial accessibility to primary healthcare services. Spatial accessibility to primary healthcare services is commonly measured using floating catchment area models which are generally defined with three variables; namely, an [...] Read more.
Geographic information systems (GIS) can be effectively utilized to carry out spatio-temporal analysis of spatial accessibility to primary healthcare services. Spatial accessibility to primary healthcare services is commonly measured using floating catchment area models which are generally defined with three variables; namely, an attractiveness component of the service centre, travel time or distance between the locations of the service centre and the population, and population demand for healthcare services. The nearest-neighbour modified two-step floating catchment area (NN-M2SFCA) model is proposed for computing spatial accessibility indices for the entire country. Accessibility values from 2010 to 2013 for Bhutan were analysed both spatially and temporally by producing accessibility ranking maps, plotting Lorenz curves, and conducting spatial clustering analysis. The spatial accessibility indices of the 205 sub-districts show great disparities in healthcare accessibility in the country. The mean- and median-based classification results indicate that, in 2013, 24 percent of Bhutan’s population have poor access to primary healthcare services, 66 percent of the population have medium-level access, and 10 percent have good access. Full article
(This article belongs to the Special Issue Bridging the Gap between Geospatial Theory and Technology)
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Open AccessArticle
Space for Climate
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1569-1583; https://doi.org/10.3390/ijgi4031569 - 01 Sep 2015
Viewed by 1761
Abstract
This paper describes how Earth Observation (EO) data—in particular from satellites—can support climate science, monitoring, and services by delivering global, repetitive, consistent, and timely information on the state of the environment and its evolution. Some examples are presented of EO demonstration pilot projects [...] Read more.
This paper describes how Earth Observation (EO) data—in particular from satellites—can support climate science, monitoring, and services by delivering global, repetitive, consistent, and timely information on the state of the environment and its evolution. Some examples are presented of EO demonstration pilot projects performed in partnership with scientists, industry, and development practitioners to support climate science, adaptation, mitigation, and disaster risk management. In particular, the paper highlights the challenge of gathering observations and generating long-term climate data records, which provide the foundation of risk management. The paper calls for a science-based integrated approach to climate risk management supported by data and knowledge, providing decision-makers with a unique analytical lens to develop a safety net to risk and maximize opportunities related to climate change and variability. Full article
(This article belongs to the Special Issue Geoinformation for Disaster Risk Management)
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Open AccessArticle
Geographic Situational Awareness: Mining Tweets for Disaster Preparedness, Emergency Response, Impact, and Recovery
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1549-1568; https://doi.org/10.3390/ijgi4031549 - 24 Aug 2015
Cited by 54 | Viewed by 3694
Abstract
Social media data have emerged as a new source for detecting and monitoring disaster events. A number of recent studies have suggested that social media data streams can be used to mine actionable data for emergency response and relief operation. However, no effort [...] Read more.
Social media data have emerged as a new source for detecting and monitoring disaster events. A number of recent studies have suggested that social media data streams can be used to mine actionable data for emergency response and relief operation. However, no effort has been made to classify social media data into stages of disaster management (mitigation, preparedness, emergency response, and recovery), which has been used as a common reference for disaster researchers and emergency managers for decades to organize information and streamline priorities and activities during the course of a disaster. This paper makes an initial effort in coding social media messages into different themes within different disaster phases during a time-critical crisis by manually examining more than 10,000 tweets generated during a natural disaster and referencing the findings from the relevant literature and official government procedures involving different disaster stages. Moreover, a classifier based on logistic regression is trained and used for automatically mining and classifying the social media messages into various topic categories during various disaster phases. The classification results are necessary and useful for emergency managers to identify the transition between phases of disaster management, the timing of which is usually unknown and varies across disaster events, so that they can take action quickly and efficiently in the impacted communities. Information generated from the classification can also be used by the social science research communities to study various aspects of preparedness, response, impact and recovery. Full article
(This article belongs to the Special Issue Geoinformation for Disaster Risk Management)
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Open AccessArticle
A Geoweb-Based Tagging System for Borderlands Data Acquisition
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1530-1548; https://doi.org/10.3390/ijgi4031530 - 21 Aug 2015
Cited by 5 | Viewed by 2291
Abstract
Borderlands modeling and understanding depend on both spatial and non-spatial data, which were difficult to obtain in the past. This has limited the progress of borderland-related research. In recent years, data collection technologies have developed greatly, especially geospatial Web 2.0 technologies including blogs, [...] Read more.
Borderlands modeling and understanding depend on both spatial and non-spatial data, which were difficult to obtain in the past. This has limited the progress of borderland-related research. In recent years, data collection technologies have developed greatly, especially geospatial Web 2.0 technologies including blogs, publish/subscribe, mashups, and GeoRSS, which provide opportunities for data acquisition in borderland areas. This paper introduces the design and development of a Geoweb-based tagging system that enables users to tag and edit geographical information. We first establish the GeoBlog model, which consists of a set of geospatial components, posts, indicators, and comments, as the foundation of the tagging system. GeoBlog is implemented such that blogs are mashed up with OpenStreetMap. Moreover, we present an improvement to existing publish/subscribe systems with support for spatio-temporal events and subscriptions, called Spatial Publish/Subscribe, as well as the event agency network for routing messages from the publishers to the subscribers. A prototype system based on this approach is implemented in experiments. The results of this study provide an approach for asynchronous interaction and message-ordered transfer in the tagging system. Full article
(This article belongs to the Special Issue Borderlands Modeling and Analysis)
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Open AccessArticle
Investigation of Travel and Activity Patterns Using Location-based Social Network Data: A Case Study of Active Mobile Social Media Users
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1512-1529; https://doi.org/10.3390/ijgi4031512 - 20 Aug 2015
Cited by 13 | Viewed by 2866
Abstract
Due to its relatively high availability and low cost, location-based social network (LBSN) (e.g., Foursquare) data (a popular type of volunteered geographic information) seem to be an alternative or complement to survey data in the study of travel behavior and activity analysis. Illustrating [...] Read more.
Due to its relatively high availability and low cost, location-based social network (LBSN) (e.g., Foursquare) data (a popular type of volunteered geographic information) seem to be an alternative or complement to survey data in the study of travel behavior and activity analysis. Illustrating this situation, recently, a number of studies attempted to use LBSN data (e.g., Foursquare check-ins) to investigate patterns of human travel and activity. Of particular note is that compared to other individual-level characteristics of users, such as age, profession, education, income and so forth, gender is relatively highly available in the profiles of Foursquare users. Moreover, considering gender differences in travel and activity analysis is a popular research topic and is helpful in better understanding the changes in women’s roles in family, labor force participation, society and so forth. Therefore, this paper empirically investigates how gender influences the travel and activity patterns of active local Foursquare users in New York City. Empirical investigations of gender differences in travel and activity patterns are conducted at both the individual and aggregate level. The empirical results reveal that there are gender differences in the travel and activity patterns of active local users in New York City at both the individual and aggregate level. Finally, the results of the empirical study and the extent to which LBSN data can be exploited to produce travel diary data are discussed. Full article
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Open AccessArticle
Historical Urban Land Use Transformation in Virtual Geo-Library
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1500-1511; https://doi.org/10.3390/ijgi4031500 - 19 Aug 2015
Cited by 2 | Viewed by 2723
Abstract
As countries become increasingly urbanized, understanding how urban areas are changing within the landscape becomes increasingly important. Urbanized areas are often the strongest indicators of human interaction with the environment, and understanding how urban areas develop through remotely sensed data allows for more [...] Read more.
As countries become increasingly urbanized, understanding how urban areas are changing within the landscape becomes increasingly important. Urbanized areas are often the strongest indicators of human interaction with the environment, and understanding how urban areas develop through remotely sensed data allows for more sustainable practices. A Landsat satellite sensor which is a remote sensing platform, with its ability to analyze global data, rapidly present itself as being an invaluable tool for studying the growth of urban areas. In this study, we present the virtual geo-library as the geovisualization tools to provide the analytical studies of the urbanization process in Malang City, East Java, Indonesia, using images derived from Landsat sensor family (1989 to 2014). We provide a dynamic geovisualization through virtual geo-library, where users could understand and get valuable scientific information (e.g., urban area changes and land use transformation in higher land). This system is also equipped with the tools to enable users to create automatic cartographic maps and print the results out as a digital pdf format file. Full article
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Open AccessArticle
Point Cluster Analysis Using a 3D Voronoi Diagram with Applications in Point Cloud Segmentation
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1480-1499; https://doi.org/10.3390/ijgi4031480 - 18 Aug 2015
Cited by 3 | Viewed by 4069
Abstract
Three-dimensional (3D) point analysis and visualization is one of the most effective methods of point cluster detection and segmentation in geospatial datasets. However, serious scattering and clotting characteristics interfere with the visual detection of 3D point clusters. To overcome this problem, this study [...] Read more.
Three-dimensional (3D) point analysis and visualization is one of the most effective methods of point cluster detection and segmentation in geospatial datasets. However, serious scattering and clotting characteristics interfere with the visual detection of 3D point clusters. To overcome this problem, this study proposes the use of 3D Voronoi diagrams to analyze and visualize 3D points instead of the original data item. The proposed algorithm computes the cluster of 3D points by applying a set of 3D Voronoi cells to describe and quantify 3D points. The decompositions of point cloud of 3D models are guided by the 3D Voronoi cell parameters. The parameter values are mapped from the Voronoi cells to 3D points to show the spatial pattern and relationships; thus, a 3D point cluster pattern can be highlighted and easily recognized. To capture different cluster patterns, continuous progressive clusters and segmentations are tested. The 3D spatial relationship is shown to facilitate cluster detection. Furthermore, the generated segmentations of real 3D data cases are exploited to demonstrate the feasibility of our approach in detecting different spatial clusters for continuous point cloud segmentation. Full article
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Open AccessArticle
Integrating Legal and Physical Dimensions of Urban Environments
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1442-1479; https://doi.org/10.3390/ijgi4031442 - 17 Aug 2015
Cited by 12 | Viewed by 2803
Abstract
Building Information Models (e.g., IFC) and virtual 3D city models (e.g., CityGML) are revolutionising the way we manage information about our cities. However, the main focus of these models is on the physical and functional characteristics of urban properties and facilities, which neglects [...] Read more.
Building Information Models (e.g., IFC) and virtual 3D city models (e.g., CityGML) are revolutionising the way we manage information about our cities. However, the main focus of these models is on the physical and functional characteristics of urban properties and facilities, which neglects the legal and ownership aspects. In contrast, cadastral data models, such as the Land Administration Domain Model (LADM), have been developed for legal information management purposes and model legal objects such as ownership boundaries without providing correspondence to the object’s physical attributes. Integration of legal and physical objects in the virtual 3D city and cadastral models would maximise their utility and flexibility to support different applications that require an integrated resource of both legal and physical information, such as urban space management and land development processes. The aim of this paper is to propose a data model that supports both legal and physical information of urban environments. The methodology to develop this data model is to extend the core cadastral data model and integrate urban features into the data model. The outcome of the research can be utilised to extend the current data models to increases their usability for different applications that require both legal and physical information. Full article
(This article belongs to the Special Issue Multi-Dimensional Spatial Data Modeling)
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Open AccessArticle
Comparative Analysis on Two Schemes for Synthesizing the High Temporal Landsat-like NDVI Dataset Based on the STARFM Algorithm
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1423-1441; https://doi.org/10.3390/ijgi4031423 - 17 Aug 2015
Cited by 1 | Viewed by 1892
Abstract
The NDVI dataset with high temporal and spatial resolution (HTSN) is significant for extracting information about the phenological change of vegetation in regions with a complex earth surface. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) has been successfully applied to synthesize [...] Read more.
The NDVI dataset with high temporal and spatial resolution (HTSN) is significant for extracting information about the phenological change of vegetation in regions with a complex earth surface. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) has been successfully applied to synthesize the HTSN by fusing the data with different characteristics. Based on the model, there are two different schemes for synthesizing the HTSN. One scheme is that red reflectance and near-infrared (NIR) reflectance are synthesized, respectively, and the HTSN is then obtained through algebraic operation (Scheme 1); the other scheme is that the red and NIR reflectance are used to calculate NDVI, which is directly taken as input data to synthesize the HTSN (Scheme 2). In this paper, taking the hill areas in eastern Sichuan China as a case, the two schemes were compared with each other. Seven Landsat images and time-series MOD13Q1 datasets spanning from October 2001 to February 2003 were used as the test data. The results showed the prediction accuracies of both derived HTSNs by the two different schemes were generally in good agreement, and Scheme 2 was slightly superior to Scheme 1 (R2: 0.14 < Scheme 1 < 0.53; 0.15 < Scheme 2 < 0.53). Although the two HTSNs showed high temporal and spatial consistence, the small spatiotemporal difference between them had a different influence on different applications. The coincidence rate of cropping intensity extracted from two derived HTSNs was fairly high, reaching up to 93.86%, while the coincidence rate of crop peak dates (i.e., the emerging dates of peaks in an annual time-series NDVI curve) was only 70.95%. Therefore, it is deemed that Scheme 2 can replace Scheme 1 in the application of extracting cropping intensity, so that more calculation time and memory space can be saved. For extracting more quantitative crop phenological information like crop peak dates, more tests are still needed in order to compare the absolute accuracy for both schemes. Full article
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Open AccessArticle
A Volunteered Geographic Information Framework to Enable Bottom-Up Disaster Management Platforms
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1389-1422; https://doi.org/10.3390/ijgi4031389 - 13 Aug 2015
Cited by 11 | Viewed by 2786
Abstract
Recent disasters, such as the 2010 Haiti earthquake, have drawn attention to the potential role of citizens as active information producers. By using location-aware devices such as smartphones to collect geographic information in the form of geo-tagged text, photos, or videos, and sharing [...] Read more.
Recent disasters, such as the 2010 Haiti earthquake, have drawn attention to the potential role of citizens as active information producers. By using location-aware devices such as smartphones to collect geographic information in the form of geo-tagged text, photos, or videos, and sharing this information through online social media, such as Twitter, citizens create Volunteered Geographic Information (VGI). To effectively use this information for disaster management, we developed a VGI framework for the discovery of VGI. This framework consists of four components: (i) a VGI brokering module to provide a standard service interface to retrieve VGI from multiple resources based on spatial, temporal, and semantic parameters; (ii) a VGI quality control component, which employs semantic filtering and cross-referencing techniques to evaluate VGI; (iii) a VGI publisher module, which uses a service-based delivery mechanism to disseminate VGI, and (iv) a VGI discovery component to locate, browse, and query metadata about available VGI datasets. In a case study we employed a FOSS (Free and Open Source Software) strategy, open standards/specifications, and free/open data to show the utility of the framework. We demonstrate that the framework can facilitate data discovery for disaster management. The addition of quality metrics and a single aggregated source of relevant crisis VGI will allow users to make informed policy choices that could save lives, meet basic humanitarian needs earlier, and perhaps limit environmental and economic damage. Full article
(This article belongs to the Special Issue Open Geospatial Science and Applications)
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Open AccessArticle
An Investigation into the Completeness of, and the Updates to, OpenStreetMap Data in a Heterogeneous Area in Brazil
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1366-1388; https://doi.org/10.3390/ijgi4031366 - 12 Aug 2015
Cited by 19 | Viewed by 2211
Abstract
The integration of user-generated content made in a collaborative environment is being increasingly considered a valuable input to reference maps, even from official map agencies such as USGS and Ordnance Survey. In Brazil, decades of lack of investment has resulted in a topographic [...] Read more.
The integration of user-generated content made in a collaborative environment is being increasingly considered a valuable input to reference maps, even from official map agencies such as USGS and Ordnance Survey. In Brazil, decades of lack of investment has resulted in a topographic map coverage that is both outdated and unequally distributed throughout the territory. This paper aims to analyze the spatial distribution of updates of OpenStreetMap in rural and urban areas in the country to understand the patterns of user updates and its correlation with other economic and developmental variables. This analysis will contribute to generating the knowledge needed in order to consider the use of this data as part of a reference layer of the National Spatial Database Infrastructure as well to design strategies to encourage user action in specific areas. Full article
(This article belongs to the Special Issue 20 Years of OGC: Open Geo-Data, Software, and Standards)
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Open AccessArticle
Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1346-1365; https://doi.org/10.3390/ijgi4031346 - 10 Aug 2015
Cited by 8 | Viewed by 2501
Abstract
The worldwide Sensor Web comprises observation data from diverse sources. Each data provider may process and assess datasets differently before making them available online. This information is often invisible to end users. Therefore, publishing observation data with quality descriptions is vital as it [...] Read more.
The worldwide Sensor Web comprises observation data from diverse sources. Each data provider may process and assess datasets differently before making them available online. This information is often invisible to end users. Therefore, publishing observation data with quality descriptions is vital as it helps users to assess the suitability of data for their applications. It is also important to capture contextual information concerning data quality such as provenance to trace back incorrect data to its origins. In the Open Geospatial Consortium (OGC)’s Sensor Web Enablement (SWE) framework, there is no sufficiently and practically applicable approach how these aspects can be systematically represented and made accessible. This paper presents Q-SOS—an extension of the OGC’s Sensor Observation Service (SOS) that supports retrieval of observation data together with quality descriptions. These descriptions are represented in an observation data model covering various aspects of data quality assessment. The service and the data model have been developed based on open standards and open source tools, and are productively being used to share observation data from the TERENO observatory infrastructure. We discuss the advantages of deploying the presented solutions from data provider and consumer viewpoints. Enhancements applied to the related open-source developments are also introduced. Full article
(This article belongs to the Special Issue Open Geospatial Science and Applications)
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Open AccessArticle
Large Scale Landform Mapping Using Lidar DEM
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1336-1345; https://doi.org/10.3390/ijgi4031336 - 07 Aug 2015
Cited by 4 | Viewed by 2800
Abstract
In this study, LIDAR DEM data was used to obtain a primary landform map in accordance with a well-known methodology. This primary landform map was generalized using the Focal Statistics tool (Majority), considering the minimum area condition in cartographic generalization in order to [...] Read more.
In this study, LIDAR DEM data was used to obtain a primary landform map in accordance with a well-known methodology. This primary landform map was generalized using the Focal Statistics tool (Majority), considering the minimum area condition in cartographic generalization in order to obtain landform maps at 1:1000 and 1:5000 scales. Both the primary and the generalized landform maps were verified visually with hillshaded DEM and an orthophoto. As a result, these maps provide satisfactory visuals of the landforms. In order to show the effect of generalization, the area of each landform in both the primary and the generalized maps was computed. Consequently, landform maps at large scales could be obtained with the proposed methodology, including generalization using LIDAR DEM. Full article
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Open AccessArticle
GPS-Aided Video Tracking
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1317-1335; https://doi.org/10.3390/ijgi4031317 - 06 Aug 2015
Cited by 1 | Viewed by 2190
Abstract
Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS) and video or radio data are used to obtain the trajectories of the observed objects. However, in some use cases, [...] Read more.
Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS) and video or radio data are used to obtain the trajectories of the observed objects. However, in some use cases, they fail to provide sufficiently accurate, complete and correct data at the same time. In this work we present an approach for fusing GPS- and video-based tracking in order to exploit their individual advantages. In this way we aim to combine the reliability of GPS tracking with the high geometric accuracy of camera detection. For the fusion of the movement data provided by the different devices we use a hidden Markov model (HMM) formulation and the Viterbi algorithm to extract the most probable trajectories. In three experiments, we show that our approach is able to deal with challenging situations like occlusions or objects which are temporarily outside the monitored area. The results show the desired increase in terms of accuracy, completeness and correctness. Full article
(This article belongs to the Special Issue Selected Papers from the ISPRS Tracking and Imaging Challenge 2014)
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Open AccessArticle
Tracking 3D Moving Objects Based on GPS/IMU Navigation Solution, Laser Scanner Point Cloud and GIS Data
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1301-1316; https://doi.org/10.3390/ijgi4031301 - 31 Jul 2015
Cited by 11 | Viewed by 3330
Abstract
Monitoring vehicular road traffic is a key component of any autonomous driving platform. Detecting moving objects, and tracking them, is crucial to navigating around objects and predicting their locations and trajectories. Laser sensors provide an excellent observation of the area around vehicles, but [...] Read more.
Monitoring vehicular road traffic is a key component of any autonomous driving platform. Detecting moving objects, and tracking them, is crucial to navigating around objects and predicting their locations and trajectories. Laser sensors provide an excellent observation of the area around vehicles, but the point cloud of objects may be noisy, occluded, and prone to different errors. Consequently, object tracking is an open problem, especially for low-quality point clouds. This paper describes a pipeline to integrate various sensor data and prior information, such as a Geospatial Information System (GIS) map, to segment and track moving objects in a scene. We show that even a low-quality GIS map, such as OpenStreetMap (OSM), can improve the tracking accuracy, as well as decrease processing time. A bank of Kalman filters is used to track moving objects in a scene. In addition, we apply non-holonomic constraint to provide a better orientation estimation of moving objects. The results show that moving objects can be correctly detected, and accurately tracked, over time, based on modest quality Light Detection And Ranging (LiDAR) data, a coarse GIS map, and a fairly accurate Global Positioning System (GPS) and Inertial Measurement Unit (IMU) navigation solution. Full article
(This article belongs to the Special Issue Selected Papers from the ISPRS Tracking and Imaging Challenge 2014)
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Open AccessArticle
Enhancing Disaster Management: Development of a Spatial Database of Day Care Centers in the USA
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1290-1300; https://doi.org/10.3390/ijgi4031290 - 30 Jul 2015
Cited by 1 | Viewed by 2371
Abstract
Children under the age of five constitute around 7% of the total U.S. population, and represent a segment of the population that is totally dependent on others for day-to-day activities. A significant proportion of this population spends time in some form of day [...] Read more.
Children under the age of five constitute around 7% of the total U.S. population, and represent a segment of the population that is totally dependent on others for day-to-day activities. A significant proportion of this population spends time in some form of day care arrangement while their parents are away from home. Accounting for those children during emergencies is of high priority, which requires a broad understanding of the locations of such day care centers. As concentrations of at risk population, the spatial location of day care centers is critical for any type of emergency preparedness and response (EPR). However, until recently, the U.S. emergency preparedness and response community did not have access to a comprehensive spatial database of day care centers at the national scale. This paper describes an approach for the development of the first comprehensive spatial database of day care center locations throughout the U.S. utilizing a variety of data harvesting techniques to integrate information from widely disparate data sources followed by geolocating for spatial precision. In the context of disaster management, such spatially refined demographic databases hold tremendous potential for improving high-resolution population distribution and dynamics models and databases. Full article
(This article belongs to the Special Issue Geoinformation for Disaster Risk Management)
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Open AccessArticle
Application of Geo-Information Techniques in Land Use and Land Cover Change Analysis in a Peri-Urban District of Ghana
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1265-1289; https://doi.org/10.3390/ijgi4031265 - 28 Jul 2015
Cited by 12 | Viewed by 3255
Abstract
Using Satellite Remote Sensing and Geographic Information System, this paper analyzes the land use and land cover change dynamics in the Bosomtwe District of Ghana, for 1986, 2010 thematic mapper and enhanced thematic Mapper+ (TM/ETM+) images, and 2014 Landsat 8 Operational Land Imager [...] Read more.
Using Satellite Remote Sensing and Geographic Information System, this paper analyzes the land use and land cover change dynamics in the Bosomtwe District of Ghana, for 1986, 2010 thematic mapper and enhanced thematic Mapper+ (TM/ETM+) images, and 2014 Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIS) image. The three images were geo-referenced and processed for classification, using the maximum likelihood classifier algorithm. A Jeffries-Matusita’s separability check was used in confirming the degree of spectral separation acceptability of the bands used for each of the land use and land cover classes. The best Kappa hat statistic of classification accuracy was 83%. Land Use and Land Cover (LULC) transition analysis in Environmental Systems Research Institute ESRI’s ArcMap was performed. The results of the classification over the three periods showed that built up, bare land and concrete surfaces increased from 1201 in 1986 to 5454 ha in 2010. Dense forest decreased by 2253 ha over the same period and increased by 873 ha by the 2014. Low forest also decreased by 1043 ha in 2010; however, it increased by 13% in 2014. Our findings showed some of the important changes in the land use and land cover patterns in the District. After the urbanization process, coupled with farmland abandonment, between 1986 and 2010, substantial increments in urban land and clear increments in farmland coverage between 1986 and 2014were found to be the reason for vegetation cover decreases. This suggests that major changes in the socio-ecological driving forces affecting landscape dynamics have occurred in the last few decades. Full article
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Open AccessArticle
A Progressive Buffering Method for Road Map Update Using OpenStreetMap Data
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1246-1264; https://doi.org/10.3390/ijgi4031246 - 27 Jul 2015
Cited by 8 | Viewed by 2290
Abstract
Web 2.0 enables a two-way interaction between servers and clients. GPS receivers become available to more citizens and are commonly found in vehicles and smart phones, enabling individuals to record and share their trajectory data on the Internet and edit them online. OpenStreetMap [...] Read more.
Web 2.0 enables a two-way interaction between servers and clients. GPS receivers become available to more citizens and are commonly found in vehicles and smart phones, enabling individuals to record and share their trajectory data on the Internet and edit them online. OpenStreetMap (OSM) makes it possible for citizens to contribute to the acquisition of geographic information. This paper studies the use of OSM data to find newly mapped or built roads that do not exist in a reference road map and create its updated version. For this purpose, we propose a progressive buffering method for determining an optimal buffer radius to detect the new roads in the OSM data. In the next step, the detected new roads are merged into the reference road maps geometrically, topologically, and semantically. Experiments with OSM data and reference road maps over an area of 8494 km2 in the city of Wuhan, China and five of its 5 km × 5 km areas are conducted to demonstrate the feasibility and effectiveness of the method. It is shown that the OSM data can add 11.96% or a total of 2008.6 km of new roads to the reference road maps with an average precision of 96.49% and an average recall of 97.63%. Full article
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Open AccessArticle
MAARGHA: A Prototype System for Road Condition and Surface Type Estimation by Fusing Multi-Sensor Data
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1225-1245; https://doi.org/10.3390/ijgi4031225 - 22 Jul 2015
Cited by 9 | Viewed by 2459
Abstract
Road infrastructure in countries like India is expanding at a rapid pace and is becoming increasingly difficult for authorities to identify and fix the bad roads in time. Current Geographical Information Systems (GIS) lack information about on-road features like road surface type, speed [...] Read more.
Road infrastructure in countries like India is expanding at a rapid pace and is becoming increasingly difficult for authorities to identify and fix the bad roads in time. Current Geographical Information Systems (GIS) lack information about on-road features like road surface type, speed breakers and dynamic attribute data like the road quality. Hence there is a need to build road monitoring systems capable of collecting such information periodically. Limitations of satellite imagery with respect to the resolution and availability, makes road monitoring primarily an on-field activity. Monitoring is currently performed using special vehicles that are fitted with expensive laser scanners and need skilled resource besides providing only very low coverage. Hence such systems are not suitable for continuous road monitoring. Cheaper alternative systems using sensors like accelerometer and GPS (Global Positioning System) exists but they are not equipped to achieve higher information levels. This paper presents a prototype system MAARGHA (MAARGHA in Sanskrit language means an eternal path to solution), which demonstrates that it can overcome the disadvantages of the existing systems by fusing multi-sensory data like camera image, accelerometer data and GPS trajectory at an information level, apart from providing additional road information like road surface type. MAARGHA has been tested across different road conditions and sensor data characteristics to assess its potential applications in real world scenarios. The developed system achieves higher information levels when compared to state of the art road condition estimation systems like Roadroid. The system performance in road surface type classification is dependent on the local environmental conditions at the time of imaging. In our study, the road surface type classification accuracy reached 100% for datasets with near ideal environmental conditions and dropped down to 60% for datasets with shadows and obstacles. Full article
(This article belongs to the Special Issue Selected Papers from the ISPRS Tracking and Imaging Challenge 2014)
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Open AccessArticle
Prototype of a Web-based Participative Decision Support Platform in Natural Hazards and Risk Management
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1201-1224; https://doi.org/10.3390/ijgi4031201 - 14 Jul 2015
Cited by 10 | Viewed by 2594
Abstract
This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the [...] Read more.
This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo) framework and its client side software development kit (SDK). The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform. Full article
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Open AccessArticle
Housing Abandonment and Demolition: Exploring the Use of Micro-Level and Multi-Year Models
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1184-1200; https://doi.org/10.3390/ijgi4031184 - 13 Jul 2015
Cited by 11 | Viewed by 2257
Abstract
Policies focusing on enforcing property code violations and the improvement of vacant properties are argued to be more efficacious than demolition policies to fight urban blight. This study applies parcel level data to a multi-year hybrid modeling structure. A fine-grained analysis is conducted [...] Read more.
Policies focusing on enforcing property code violations and the improvement of vacant properties are argued to be more efficacious than demolition policies to fight urban blight. This study applies parcel level data to a multi-year hybrid modeling structure. A fine-grained analysis is conducted on the dynamic patterns of abandonment and demolition for a unique period of four years before and after the City of Buffalo’s stepped-up demolition efforts. Results showed that proximity to vacant and abandoned properties, sustained over the years, had the greatest impact on the possibility of a property being abandoned. The second greatest positive impact on property abandonment was small lot front size. Results also showed that neighborhood vacancy density had the greatest negative impact on surrounding housing sales prices over the years. There was no significant impact of demolition on housing sales prices. These findings suggested that the City should aim to have more incentive programs that are tailored to control the number of vacant properties, rather than focusing primarily on demolition-oriented programs. Full article
(This article belongs to the Special Issue Geo-Information Fostering Innovative Solutions for Smart Cities)
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