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ISPRS Int. J. Geo-Inf., Volume 2, Issue 2 (June 2013), Pages 256-552

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Research

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Open AccessArticle From Geoportals to Geographic Knowledge Portals
ISPRS Int. J. Geo-Inf. 2013, 2(2), 256-275; doi:10.3390/ijgi2020256
Received: 24 January 2013 / Revised: 21 March 2013 / Accepted: 21 March 2013 / Published: 28 March 2013
Cited by 6 | PDF Full-text (1086 KB) | HTML Full-text | XML Full-text
Abstract
We present the application of Latent Semantic Analysis (LSA) in combination with recommender systems, in order to enhance discovery in geoportals. As a basis for discovery, metadata of spatial data and services, as well as of non-spatial resources, such as documents and scientific
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We present the application of Latent Semantic Analysis (LSA) in combination with recommender systems, in order to enhance discovery in geoportals. As a basis for discovery, metadata of spatial data and services, as well as of non-spatial resources, such as documents and scientific papers, is created and registered in the catalogue of the geoportal (semi-)automatically. Links that are not inherent in the data itself are established based on the semantic similarity of its textual content using LSA. This leads to the transition from unstructured data to structured (metadata) information, serving as a basis for the generation of knowledge. The metadata information is integrated into a recommendation system that provides a ranked list showing (1) what other users viewed and (2) the related resources discovered by the LSA workflow as a result. Based on the assumptions that similar texts have something in common and that users are likely to be interested in what other users viewed, recommendations provide a broader, but also more precise, search result; on the one hand, the recommender engine considers additional information; on the other hand, it ranks resources based on the discovery experience of other users and the likeliness of the documents being related to each other. Full article
Open AccessArticle A Photogrammetric Approach for Assessing Positional Accuracy of OpenStreetMap© Roads
ISPRS Int. J. Geo-Inf. 2013, 2(2), 276-301; doi:10.3390/ijgi2020276
Received: 16 January 2013 / Revised: 28 February 2013 / Accepted: 18 March 2013 / Published: 2 April 2013
Cited by 7 | PDF Full-text (1844 KB) | HTML Full-text | XML Full-text
Abstract
As open source volunteered geographic information continues to gain popularity, the user community and data contributions are expected to grow, e.g., CloudMade, Apple, and Ushahidi now provide OpenStreetMap© (OSM) as a base layer for some of their mapping applications. This, coupled with
[...] Read more.
As open source volunteered geographic information continues to gain popularity, the user community and data contributions are expected to grow, e.g., CloudMade, Apple, and Ushahidi now provide OpenStreetMap© (OSM) as a base layer for some of their mapping applications. This, coupled with the lack of cartographic standards and the expectation to one day be able to use this vector data for more geopositionally sensitive applications, like GPS navigation, leaves potential users and researchers to question the accuracy of the database. This research takes a photogrammetric approach to determining the positional accuracy of OSM road features using stereo imagery and a vector adjustment model. The method applies rigorous analytical measurement principles to compute accurate real world geolocations of OSM road vectors. The proposed approach was tested on several urban gridded city streets from the OSM database with the results showing that the post adjusted shape points improved positionally by 86%. Furthermore, the vector adjustment was able to recover 95% of the actual positional displacement present in the database. To demonstrate a practical application, a head-to-head positional accuracy assessment between OSM, the USGS National Map (TNM), and United States Census Bureau’s Topologically Integrated Geographic Encoding Referencing (TIGER) 2007 roads was conducted. Full article
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Open AccessArticle Identifying Land Use/Cover Dynamics in the Koga Catchment, Ethiopia, from Multi-Scale Data, and Implications for Environmental Change
ISPRS Int. J. Geo-Inf. 2013, 2(2), 302-323; doi:10.3390/ijgi2020302
Received: 24 January 2013 / Revised: 11 March 2013 / Accepted: 13 March 2013 / Published: 2 April 2013
Cited by 8 | HTML Full-text
Abstract
This study analyzed more than 50 years of land cover and land use changes in the 260 km2 Koga catchment in North Western Ethiopia. The data used includes 1:50,000 scale aerial photographs, Landsat MSS, TM and ETM images, and ASTER images together
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This study analyzed more than 50 years of land cover and land use changes in the 260 km2 Koga catchment in North Western Ethiopia. The data used includes 1:50,000 scale aerial photographs, Landsat MSS, TM and ETM images, and ASTER images together with ground truth data collected through field surveys and community elders’ interviews. Aerial photographs have high spatial resolution but provide lower spectral resolution than satellite data. While most land use/cover change studies compare changes from different spatial scales, this study applied land use/cover classification techniques to bring the data to a relatively similar scale. The data revealed that woody vegetation decreased from 5,576 ha to 3,012 ha from the 1950s to 2010. Most of the deforestation took place between the 1970s and 1980s, but there is an increasing trend since then. No significant changes were observed in the area used for agriculture that comprises the pastures and crop fields since the 1950s, while there is an enormous increase in the area used for settlement, due to a tremendous increase in population from one point in time to another. The bare lands that used to exist in previous years were found to be totally covered with other land cover/use classes and no bare lands were observed in the study area in the year 2010. Population pressure and land use policies were found to be reasons for the changes in land use/cover while soil degradation, decrease in the indigenous woody vegetation and erosion were the observed consequences of the land use/cover changes. Full article
Open AccessArticle Using Geometric Properties to Evaluate Possible Integration of Authoritative and Volunteered Geographic Information
ISPRS Int. J. Geo-Inf. 2013, 2(2), 349-370; doi:10.3390/ijgi2020349
Received: 4 March 2013 / Revised: 15 April 2013 / Accepted: 18 April 2013 / Published: 25 April 2013
Cited by 12 | PDF Full-text (1247 KB) | HTML Full-text | XML Full-text
Abstract
The assessment of data quality from different sources can be considered as a key challenge in supporting effective geospatial data integration and promoting collaboration in mapping projects. This paper presents a methodology for assessing positional and shape quality for authoritative large-scale data, such
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The assessment of data quality from different sources can be considered as a key challenge in supporting effective geospatial data integration and promoting collaboration in mapping projects. This paper presents a methodology for assessing positional and shape quality for authoritative large-scale data, such as Ordnance Survey (OS) UK data and General Directorate for Survey (GDS) Iraq data, and Volunteered Geographic Information (VGI), such as OpenStreetMap (OSM) data, with the intention of assessing possible integration. It is based on the measurement of discrepancies among the datasets, addressing positional accuracy and shape fidelity, using standard procedures and also directional statistics. Line feature comparison has been undertaken using buffering techniques and statistics, whilst shape metrics, including moments invariant, have been applied to assess polygon matching. The analyses are presented with a user-friendly interface which eases data input, computation and output of results, and assists in interpretation of the comparison. The results show that a comparison of positional and shape characteristics of OS data or GDS data, with those of OSM data, indicates that their integration for large scale mapping applications is not viable. Full article
(This article belongs to the Special Issue Collaborative Mapping)
Open AccessArticle Uncovering Spatio-Temporal Cluster Patterns Using Massive Floating Car Data
ISPRS Int. J. Geo-Inf. 2013, 2(2), 371-384; doi:10.3390/ijgi2020371
Received: 20 March 2013 / Revised: 22 April 2013 / Accepted: 2 May 2013 / Published: 10 May 2013
Cited by 3 | HTML Full-text
Abstract
In this paper, we explore spatio-temporal clusters using massive floating car data from a complex network perspective. We analyzed over 85 million taxicab GPS points (floating car data) collected in Wuhan, Hubei, China. Low-speed and stop points were selected to generate spatio-temporal clusters,
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In this paper, we explore spatio-temporal clusters using massive floating car data from a complex network perspective. We analyzed over 85 million taxicab GPS points (floating car data) collected in Wuhan, Hubei, China. Low-speed and stop points were selected to generate spatio-temporal clusters, which indicated the typical stop-and-go movement pattern in real-world traffic congestion. We found that the sizes of spatio-temporal clusters exhibited a power law distribution. This implies the presence of a scaling property; i.e., they can be naturally divided into a strong hierarchical structure: long time-duration ones (a low percentage) whose values lie above the mean value and short ones (a high percentage) whose values lie below. The spatio-temporal clusters at different levels represented the degree of traffic congestions, for example the higher the level, the worse the traffic congestions. Moreover, the distribution of traffic congestions varied spatio-temporally and demonstrated a multinuclear structure in urban road networks, which suggested there is a correlation to the corresponding internal mobile regularities of an urban system. Full article
Open AccessArticle A Collaborative Geospatial Shoreline Inventory Tool to Guide Coastal Development and Habitat Conservation
ISPRS Int. J. Geo-Inf. 2013, 2(2), 385-404; doi:10.3390/ijgi2020385
Received: 11 March 2013 / Revised: 2 May 2013 / Accepted: 2 May 2013 / Published: 13 May 2013
Cited by 1 | PDF Full-text (1074 KB) | HTML Full-text | XML Full-text
Abstract
We are developing a geospatial inventory tool that will guide habitat conservation, restoration and coastal development and benefit several stakeholders who seek mitigation and adaptation strategies to shoreline changes resulting from erosion and sea level rise. The ESRI Geoportal Server, which is a
[...] Read more.
We are developing a geospatial inventory tool that will guide habitat conservation, restoration and coastal development and benefit several stakeholders who seek mitigation and adaptation strategies to shoreline changes resulting from erosion and sea level rise. The ESRI Geoportal Server, which is a type of web portal used to find and access geospatial information in a central repository, is customized by adding a Geoinventory tool capability that allows any shoreline related data to be searched, displayed and analyzed on a map viewer. Users will be able to select sections of the shoreline and generate statistical reports in the map viewer to allow for comparisons. The tool will also facilitate map-based discussion forums and creation of user groups to encourage citizen participation in decisions regarding shoreline stabilization and restoration, thereby promoting sustainable coastal development. Full article
(This article belongs to the Special Issue Collaborative Mapping)
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Open AccessCommunication Measuring Scale-Dependent Landscape Structure with Rao’s Quadratic Diversity
ISPRS Int. J. Geo-Inf. 2013, 2(2), 405-412; doi:10.3390/ijgi2020405
Received: 5 March 2013 / Revised: 3 May 2013 / Accepted: 6 May 2013 / Published: 14 May 2013
Cited by 3 | HTML Full-text
Abstract
In this paper, we apply a special application of the Rao quadratic diversity for multiscale analysis of land use changes in a mixed agricultural-forest landscape in Central Italy. The proposed approach is similar to a block-size analysis of compositional diversity for which a
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In this paper, we apply a special application of the Rao quadratic diversity for multiscale analysis of land use changes in a mixed agricultural-forest landscape in Central Italy. The proposed approach is similar to a block-size analysis of compositional diversity for which a given landscape is overlaid with a series of square grids composed of increasingly larger boxes. The combination of land cover classes in each box is recorded, and the Rao quadratic diversity is computed for the frequency distribution of the land cover classes at each box-size. Plotting compositional diversity versus box-size provides information on the scale-dependent pattern of the landscape. Since the proposed methodology is not severely influenced by the co-registration accuracy of the underlying data sets, it may prove to be reasonably adequate for analyzing historical data sets of varying resolution and quality, like aerial photographs or categorical maps. Full article
(This article belongs to the Special Issue Geospatial Monitoring and Modelling of Environmental Change)
Open AccessArticle A Geospatial Cyberinfrastructure for Urban Economic Analysis and Spatial Decision-Making
ISPRS Int. J. Geo-Inf. 2013, 2(2), 413-431; doi:10.3390/ijgi2020413
Received: 1 March 2013 / Revised: 26 April 2013 / Accepted: 8 May 2013 / Published: 21 May 2013
Cited by 11 | HTML Full-text
Abstract
Urban economic modeling and effective spatial planning are critical tools towards achieving urban sustainability. However, in practice, many technical obstacles, such as information islands, poor documentation of data and lack of software platforms to facilitate virtual collaboration, are challenging the effectiveness of decision-making
[...] Read more.
Urban economic modeling and effective spatial planning are critical tools towards achieving urban sustainability. However, in practice, many technical obstacles, such as information islands, poor documentation of data and lack of software platforms to facilitate virtual collaboration, are challenging the effectiveness of decision-making processes. In this paper, we report on our efforts to design and develop a geospatial cyberinfrastructure (GCI) for urban economic analysis and simulation. This GCI provides an operational graphic user interface, built upon a service-oriented architecture to allow (1) widespread sharing and seamless integration of distributed geospatial data; (2) an effective way to address the uncertainty and positional errors encountered in fusing data from diverse sources; (3) the decomposition of complex planning questions into atomic spatial analysis tasks and the generation of a web service chain to tackle such complex problems; and (4) capturing and representing provenance of geospatial data to trace its flow in the modeling task. The Greater Los Angeles Region serves as the test bed. We expect this work to contribute to effective spatial policy analysis and decision-making through the adoption of advanced GCI and to broaden the application coverage of GCI to include urban economic simulations. Full article
Open AccessArticle GeoMemories—A Platform for Visualizing Historical, Environmental and Geospatial Changes in the Italian Landscape
ISPRS Int. J. Geo-Inf. 2013, 2(2), 432-455; doi:10.3390/ijgi2020432
Received: 20 March 2013 / Revised: 25 April 2013 / Accepted: 27 April 2013 / Published: 21 May 2013
Cited by 4 | HTML Full-text
Abstract
The GeoMemories project aims at publishing on the Web and digitally preserving historical aerial photographs that are currently stored in physical form within the archives of the Aerofototeca Nazionale in Rome. We describe a system, available at http://www.geomemories.org, that lets users visualize the
[...] Read more.
The GeoMemories project aims at publishing on the Web and digitally preserving historical aerial photographs that are currently stored in physical form within the archives of the Aerofototeca Nazionale in Rome. We describe a system, available at http://www.geomemories.org, that lets users visualize the evolution of the Italian landscape throughout the last century. The Web portal allows comparison of recent satellite imagery with several layers of historical maps, obtained from the aerial photos through a complex workflow that merges them together. We present several case studies carried out in collaboration with geologists, historians and archaeologists, that illustrate the great potential of our system in different research fields. Experiments and advances in image processing technologies are envisaged as a key factor in solving the inherent issue of vast amounts of manual work, from georeferencing to mosaicking to analysis. Full article
(This article belongs to the Special Issue Geospatial Monitoring and Modelling of Environmental Change)
Open AccessArticle Multi-Temporal Time-Dependent Terrain Visualization through Localized Spatial Correspondence Parameterization
ISPRS Int. J. Geo-Inf. 2013, 2(2), 456-479; doi:10.3390/ijgi2020456
Received: 22 March 2013 / Revised: 6 May 2013 / Accepted: 6 May 2013 / Published: 24 May 2013
Cited by 1 | PDF Full-text (1478 KB) | HTML Full-text | XML Full-text
Abstract
Visualizing quantitative time-dependent changes in the topography requires relying on a series of discrete given multi-temporal topographic datasets that were acquired on a given time-line. The reality of physical phenomenon occurring during the acquisition times is complex when trying to mutually model the
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Visualizing quantitative time-dependent changes in the topography requires relying on a series of discrete given multi-temporal topographic datasets that were acquired on a given time-line. The reality of physical phenomenon occurring during the acquisition times is complex when trying to mutually model the datasets; thus, different levels of spatial inter-relations and geometric inconsistencies among the datasets exist. Any straight forward simulation will result in a truncated, ill-correct and un-smooth visualization. A desired quantitative and qualitative modelling is presumed to describe morphologic changes that occurred, so it can be utilized to carry out more precise and true-to-nature visualization tasks, while trying to best describe the reality transition as it occurred. This research paper suggests adopting a fully automatic hierarchical modelling mechanism, hence implementing several levels of spatial correspondence between the topographic datasets. This quantification is then utilized for the datasets morphing and blending tasks required for intermediate scene visualization. The establishment of a digital model that stores the local spatial transformation parameterization correspondences between the topographic datasets is realized. Along with designated interpolation concepts, this complete process ensures that the visualized transition from one topographic dataset to the other via the quantified correspondences is smooth and continuous, while maintaining morphological and topological relations. Full article
(This article belongs to the Special Issue Geovisualization and Analysis of Dynamic Phenomena)
Open AccessArticle A Spatially Intelligent Public Participation System for the Environmental Impact Assessment Process
ISPRS Int. J. Geo-Inf. 2013, 2(2), 480-506; doi:10.3390/ijgi2020480
Received: 25 March 2013 / Revised: 5 May 2013 / Accepted: 7 May 2013 / Published: 27 May 2013
Cited by 3 | HTML Full-text
Abstract
An environmental impact assessment (EIA) is a decision-making process that evaluates the possible significant effects that a proposed project may exert on the environment. The EIA scoping and reviewing stages often involve public participation. Although its importance has long been recognized, public participation
[...] Read more.
An environmental impact assessment (EIA) is a decision-making process that evaluates the possible significant effects that a proposed project may exert on the environment. The EIA scoping and reviewing stages often involve public participation. Although its importance has long been recognized, public participation in the EIA process is often regarded as ineffective, due to time, budget, resource, technical and procedural constraints, as well as the complexity of environmental information. Geographic Information System (GIS) and Volunteer Geographic Information (VGI) have the potential to contribute to data collection, sharing and presentation, utilize local user-generated content to benefit decision-making and increase public outreach. This research integrated GIS, VGI, social media tools, data mining and mobile technology to design a spatially intelligent framework that presented and shared EIA information effectively to the public. A spatially intelligent public participative system (SIPPS) was also developed as a proof-of-concept of the framework. The research selected the Tehachapi Renewable Transmission Project (TRTP) as the pilot study area. Survey questionnaires were designed to collect feedback and conduct evaluation. Results show that SIPPS was able to improve the effectiveness of public participation, promote environmental awareness and achieve good system usability. Full article
(This article belongs to the Special Issue Collaborative Mapping)
Open AccessArticle Assessing Completeness and Spatial Error of Features in Volunteered Geographic Information
ISPRS Int. J. Geo-Inf. 2013, 2(2), 507-530; doi:10.3390/ijgi2020507
Received: 28 March 2013 / Revised: 14 May 2013 / Accepted: 20 May 2013 / Published: 4 June 2013
Cited by 23 | HTML Full-text
Abstract
The assessment of the quality and accuracy of Volunteered Geographic Information (VGI) contributions, and by extension the ultimate utility of VGI data has fostered much debate within the geographic community. The limited research to date has been focused on VGI data of linear
[...] Read more.
The assessment of the quality and accuracy of Volunteered Geographic Information (VGI) contributions, and by extension the ultimate utility of VGI data has fostered much debate within the geographic community. The limited research to date has been focused on VGI data of linear features and has shown that the error in the data is heterogeneously distributed. Some have argued that data produced by numerous contributors will produce a more accurate product than an individual and some research on crowd-sourced initiatives has shown that to be true, although research on VGI is more infrequent. This paper proposes a method for quantifying the completeness and accuracy of a select subset of infrastructure-associated point datasets of volunteered geographic data within a major metropolitan area using a national geospatial dataset as the reference benchmark with two datasets from volunteers used as test datasets. The results of this study illustrate the benefits of including quality control in the collection process for volunteered data. Full article
(This article belongs to the Special Issue Collaborative Mapping)
Open AccessArticle Genetic Optimization for Associative Semantic Ranking Models of Satellite Images by Land Cover
ISPRS Int. J. Geo-Inf. 2013, 2(2), 531-552; doi:10.3390/ijgi2020531
Received: 3 April 2013 / Revised: 29 May 2013 / Accepted: 29 May 2013 / Published: 7 June 2013
Cited by 2 | HTML Full-text
Abstract
Associative methods for content-based image ranking by semantics are attractive due to the similarity of generated models to human models of understanding. Although they tend to return results that are better understood by image analysts, the induction of these models is difficult to
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Associative methods for content-based image ranking by semantics are attractive due to the similarity of generated models to human models of understanding. Although they tend to return results that are better understood by image analysts, the induction of these models is difficult to build due to factors that affect training complexity, such as coexistence of visual patterns in same images, over-fitting or under-fitting and semantic representation differences among image analysts. This article proposes a methodology to reduce the complexity of ranking satellite images for associative methods. Our approach employs genetic operations to provide faster and more accurate models for ranking by semantic using low level features. The added accuracy is provided by a reduction in the likelihood to reach local minima or to overfit. The experiments show that, using genetic optimization, associative methods perform better or at similar levels as state-of-the-art ensemble methods for ranking. The mean average precision (MAP) of ranking by semantic was improved by 14% over similar associative methods that use other optimization techniques while maintaining smaller size for each semantic model. Full article
(This article belongs to the Special Issue Spatial Analysis and Data Mining)

Review

Jump to: Research

Open AccessReview A Comparative Review of North American Tundra Delineations
ISPRS Int. J. Geo-Inf. 2013, 2(2), 324-348; doi:10.3390/ijgi2020324
Received: 29 January 2013 / Accepted: 25 March 2013 / Published: 8 April 2013
HTML Full-text
Abstract
Recent profound changes have been observed in the Arctic environment, including record low sea ice extents and high latitude greening. Studying the Arctic and how it is changing is an important element of climate change science. The Tundra, an ecoregion of the Arctic,
[...] Read more.
Recent profound changes have been observed in the Arctic environment, including record low sea ice extents and high latitude greening. Studying the Arctic and how it is changing is an important element of climate change science. The Tundra, an ecoregion of the Arctic, is directly related to climate change due to its effects on the snow ice feedback mechanism and greenhouse gas cycling. Like all ecoregions, the Tundra border is shifting, yet studies and policies require clear delineation of boundaries. There are many options for ecoregion classification systems, as well as resources for creating custom maps. To help decision makers identify the best classification system possible, we present a review of North American Tundra ecoregion delineations and further explore the methodologies, purposes, limitations, and physical properties of five common ecoregion classification systems. We quantitatively compare the corresponding maps by area using a geographic information system. Full article

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