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ISPRS Int. J. Geo-Inf., Volume 7, Issue 3 (March 2018)

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Cover Story (view full-size image) Ongoing global warming has increased the frequency and magnitude of ENSO which has affected the [...] Read more.
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Open AccessArticle Procedural Generation of Large-Scale Forests Using a Graph-Based Neutral Landscape Model
ISPRS Int. J. Geo-Inf. 2018, 7(3), 127; https://doi.org/10.3390/ijgi7030127
Received: 7 February 2018 / Revised: 15 March 2018 / Accepted: 17 March 2018 / Published: 20 March 2018
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Abstract
Specifying the positions and attributes of plants (e.g., species, size, and height) during the procedural generation of large-scale forests in virtual geographic environments is challenging, especially when reflecting the characteristics of vegetation distributions. To address this issue, a novel graph-based neutral landscape model
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Specifying the positions and attributes of plants (e.g., species, size, and height) during the procedural generation of large-scale forests in virtual geographic environments is challenging, especially when reflecting the characteristics of vegetation distributions. To address this issue, a novel graph-based neutral landscape model (NLM) is proposed to generate forest landscapes with varying compositions and configurations. Our model integrates a set of class-level landscape metrics and generates more realistic and variable landscapes compared with existing NLMs controlled by limited global-level landscape metrics. To produce patches with particular sizes and shapes, a region adjacency graph is transformed from a cluster map that is generated based upon percolation theory; subsequently, optimal neighboring nodes in the graph are merged under restricted growth conditions from a source node. The locations of seeds are randomly placed and their species are classified according to the generated forest landscapes to obtain the final tree distributions. The results demonstrate that our method can generate realistic vegetation distributions representing different spatial patterns of species with a time efficiency that satisfies the requirements for constructing large-scale virtual forests. Full article
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Open AccessArticle Mining Individual Similarity by Assessing Interactions with Personally Significant Places from GPS Trajectories
ISPRS Int. J. Geo-Inf. 2018, 7(3), 126; https://doi.org/10.3390/ijgi7030126
Received: 29 January 2018 / Revised: 16 March 2018 / Accepted: 17 March 2018 / Published: 19 March 2018
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Abstract
Human mobility is closely associated with places. Due to advancements in GPS devices and related sensor technologies, an unprecedented amount of tracking data has been generated in recent years, thus providing a new way to investigate the interactions between individuals and places, which
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Human mobility is closely associated with places. Due to advancements in GPS devices and related sensor technologies, an unprecedented amount of tracking data has been generated in recent years, thus providing a new way to investigate the interactions between individuals and places, which are vital for depicting individuals’ characteristics. In this paper, we propose a framework for mining individual similarity based on long-term trajectory data. In contrast to most existing studies, which have focused on the sequential properties of individuals’ visits to public places, this paper emphasizes the essential role of the spatio-temporal interactions between individuals and their personally significant places. Specifically, rather than merely using public geographic databases, which include only public places and lack personal meanings, we attempt to interpret the semantics of places that are significant to individuals from the perspectives of personal behavior. Next, we propose a new individual similarity measurement that incorporates both the spatio-temporal and semantic properties of individuals’ visits to significant places. By experimenting on real-world GPS datasets, we demonstrate that our approach is more capable of distinguishing individuals and characterizing individual features than the previous methods. Additionally, we show that our approach can be used to effectively measure individual similarity and to aggregate individuals into meaningful subgroups. Full article
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
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Open AccessArticle Digital Story Mapping to Advance Educational Atlas Design and Enable Student Engagement
ISPRS Int. J. Geo-Inf. 2018, 7(3), 125; https://doi.org/10.3390/ijgi7030125
Received: 15 January 2018 / Revised: 8 March 2018 / Accepted: 14 March 2018 / Published: 19 March 2018
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Abstract
Storytelling is recognized as a valid and important method of communicating information and knowledge gleaned from volumes of ever-accumulating data. Practices of data-driven storytelling in journalism and geovisual analytics have contributed to the development of geovisual stories; also called story maps. The benefits
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Storytelling is recognized as a valid and important method of communicating information and knowledge gleaned from volumes of ever-accumulating data. Practices of data-driven storytelling in journalism and geovisual analytics have contributed to the development of geovisual stories; also called story maps. The benefits of student-focused multi-thematic atlases and digital storytelling methods in education can also be realized in story maps. An online, interactive version of the original paper version of the Wyoming Student Atlas was developed using story mapping technology. Studies on best practices for data-driven storytelling and web map interaction were used to inform the transition of the atlas from a traditional paper format to a collection of story maps. Evaluation of the atlas story maps for educational purposes was conducted by observing students from multiple classrooms as they used the story maps in a lesson. The students and educators responded to a survey after using the story maps. Results of the survey show positive responses to the atlas story maps, including ease of use and preference over a traditional paper atlas. However, certain types of interaction with the map resulted in increased negative or uncertain responses from students concerning their perception of the atlas story maps. Full article
(This article belongs to the Special Issue Storytelling with Geographic Data)
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Open AccessArticle Factors Affecting the Number of Visitors in National Parks in the Czech Republic, Germany and Austria
ISPRS Int. J. Geo-Inf. 2018, 7(3), 124; https://doi.org/10.3390/ijgi7030124
Received: 22 January 2018 / Revised: 12 February 2018 / Accepted: 13 March 2018 / Published: 19 March 2018
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Abstract
In the context of national-level strategies, the importance of tourism in national parks is on the rise. The objective of this study is to investigate the relationship between the number of visitors to national parks and five variables: area, number of employees, budget,
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In the context of national-level strategies, the importance of tourism in national parks is on the rise. The objective of this study is to investigate the relationship between the number of visitors to national parks and five variables: area, number of employees, budget, average employee salary and number of researchers in 12 national parks in the Czech Republic, Germany and Austria. Analysis of factors influencing the number of visitors to national parks uses the method of retrospective analysis of the data contained in internal documents and questionnaires among managers of national parks. The number of candidate predictors is relatively high when compared with the number of observations. Due to this fact, the Gilmour method for statistical analysis is used. Statistical results represented by the parameter β2 for number of employees is −33,016 (95% CI, −50,592–−15,441) and by the parameter β3 for budget is 0.586 (95% CI, 0.295–0.878), showing that the number of visitors increases with budget, while it decreases with the number of employees. The results of this study are a useful starting point for managers in their efforts to focus on developing key areas in an appropriate way. In conclusion, results show that increasing the economic benefits accruing from national parks regional policy could aim at a qualitative upgrading of tourist services, increased marketing of the unique national park label and the promotion of a diverse regional supply base. Full article
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Open AccessArticle Storytelling in Interactive 3D Geographic Visualization Systems
ISPRS Int. J. Geo-Inf. 2018, 7(3), 123; https://doi.org/10.3390/ijgi7030123
Received: 12 January 2018 / Revised: 2 March 2018 / Accepted: 14 March 2018 / Published: 19 March 2018
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Abstract
The objective of interactive geographic maps is to provide geographic information to a large audience in a captivating and intuitive way. Storytelling helps to create exciting experiences and to explain complex or otherwise hidden relationships of geospatial data. Furthermore, interactive 3D applications offer
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The objective of interactive geographic maps is to provide geographic information to a large audience in a captivating and intuitive way. Storytelling helps to create exciting experiences and to explain complex or otherwise hidden relationships of geospatial data. Furthermore, interactive 3D applications offer a wide range of attractive elements for advanced visual story creation and offer the possibility to convey the same story in many different ways. In this paper, we discuss and analyze storytelling techniques in 3D geographic visualizations so that authors and developers working with geospatial data can use these techniques to conceptualize their visualization and interaction design. Finally, we outline two examples which apply the given concepts. Full article
(This article belongs to the Special Issue Storytelling with Geographic Data)
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Open AccessArticle Single-Frequency Kinematic Performance Comparison between Galileo, GPS, and GLONASS Satellite Positioning Systems Using an MMS-Generated Trajectory as a Reference: Preliminary Results
ISPRS Int. J. Geo-Inf. 2018, 7(3), 122; https://doi.org/10.3390/ijgi7030122
Received: 24 January 2018 / Revised: 27 February 2018 / Accepted: 14 March 2018 / Published: 18 March 2018
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Abstract
The initial Galileo satellite positioning services, started on December 15, 2016, became available with a formal announcement by the European Commission. This first step toward the Galileo system Full Operational Capability (FOC) has allowed many researchers to test the new system. The aim
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The initial Galileo satellite positioning services, started on December 15, 2016, became available with a formal announcement by the European Commission. This first step toward the Galileo system Full Operational Capability (FOC) has allowed many researchers to test the new system. The aim of this paper is to illustrate the results and the conclusions of a kinematic test involving a GNSS (Global Navigation Satellite System) multi-constellation receiver able to acquire the Galileo Open Service (OS) signal. The produced outputs were compared to a reference trajectory obtained from a Mobile Mapping System (MMS) implementing integrated high-performance GPS/INS measurements. By exploiting the CUI (command user interface) of the open source library RTKLIB, a reduced operative status was simulated for GPS and GLONASS. Specifically, all the possible operative combinations were tested and, when possible, statistically assessed. This was necessary to offer a fair comparison among the tested constellations. The results, referred to the reference trajectory, show that the new European system is characterized by a better planimetric performance with respect to the other systems, whereas, from an altimetric point of view, the GPS and GLONASS systems perform better. Full article
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Open AccessArticle Efficient Method for POI/ROI Discovery Using Flickr Geotagged Photos
ISPRS Int. J. Geo-Inf. 2018, 7(3), 121; https://doi.org/10.3390/ijgi7030121
Received: 17 January 2018 / Revised: 14 February 2018 / Accepted: 12 March 2018 / Published: 16 March 2018
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Abstract
In the era of big data, ubiquitous Flickr geotagged photos have opened a considerable opportunity for discovering valuable geographic information. Point of interest (POI) and region of interest (ROI) are significant reference data that are widely used in geospatial applications. This study aims
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In the era of big data, ubiquitous Flickr geotagged photos have opened a considerable opportunity for discovering valuable geographic information. Point of interest (POI) and region of interest (ROI) are significant reference data that are widely used in geospatial applications. This study aims to develop an efficient method for POI/ROI discovery from Flickr. Attractive footprints in photos with a local maximum that is beneficial for distinguishing clusters are first exploited. Pattern discovery is combined with a novel algorithm, the spatial overlap (SO) algorithm, and the naming and merging method is conducted for attractive footprint clustering. POI and ROI, which are derived from the peak value and range of clusters, indicate the most popular location and range for appreciating attractions. The discovered ROIs have a particular spatial overlap available which means the satisfied region of ROIs can be shared for appreciating attractions. The developed method is demonstrated in two study areas in Taiwan: Tainan and Taipei, which are the oldest and densest cities, respectively. Results show that the discovered POI/ROIs nearly match the official data in Tainan, whereas more commercial POI/ROIs are discovered in Taipei by the algorithm than official data. Meanwhile, our method can address the clustering issue in a dense area. Full article
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Open AccessArticle A Co-Citation and Cluster Analysis of Scientometrics of Geographic Information Ontology
ISPRS Int. J. Geo-Inf. 2018, 7(3), 120; https://doi.org/10.3390/ijgi7030120
Received: 14 December 2017 / Revised: 11 February 2018 / Accepted: 12 March 2018 / Published: 16 March 2018
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Abstract
Geographic information ontology represents an effective means of expressing geographic concepts and relationships between them. As an emerging field of study, it has drawn the attention of increasing numbers of scholars worldwide. In this study, both co-citation and cluster analysis methods of scientometrics
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Geographic information ontology represents an effective means of expressing geographic concepts and relationships between them. As an emerging field of study, it has drawn the attention of increasing numbers of scholars worldwide. In this study, both co-citation and cluster analysis methods of scientometrics are used to perform a comprehensive analysis of the papers on the topic of geographic information ontology indexed by the Web of Science (WoS) and published between 2001 and 2016. The results show that the history of the study of geographic information ontology can be divided roughly into three periods. Computer science and mathematics play important roles in this field of study. The International Journal of Geographical Information Science is an important periodical that provides knowledge resources for the study of geographic information ontology. The papers of Gruber TR and Guarino N are referenced most frequently, as well as that of Smith B., who formally introduced information ontology to the field of geographic information science. Providing personalized and intelligent geographic information services for users is an important focus of geographic information ontology. Full article
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Open AccessArticle A Multiresolution Grid Structure Applied to Seafloor Shape Modeling
ISPRS Int. J. Geo-Inf. 2018, 7(3), 119; https://doi.org/10.3390/ijgi7030119
Received: 31 January 2018 / Revised: 27 February 2018 / Accepted: 14 March 2018 / Published: 16 March 2018
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Abstract
This paper proposes a method of creating a multiresolution depth grid containing bathymetric data describing a stretch of sea floor. The included literature review presents current solutions in the area of the creation of digital terrain models (DTMs) focusing on methods employing regular
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This paper proposes a method of creating a multiresolution depth grid containing bathymetric data describing a stretch of sea floor. The included literature review presents current solutions in the area of the creation of digital terrain models (DTMs) focusing on methods employing regular grids, with a discussion on the strong and weak points of such an approach. As a basis for the investigations, some important recommendations from the International Hydrographic Organization are provided and are related to the accuracy of created models. The authors propose a novel method of storing DTM data, involving multiresolution depth grids. The paper presents the characteristics of this method, numerical algorithms of a conversion between a regular grid and the multiresolution one, and experiments on typical seafloor surfaces. The results are discussed, focusing on the data reduction rate and the variable resolution of the grid structure. The proposed method can be applied in Geographical Information Systems, especially for the purposes of solving sea survey problems. Full article
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Open AccessShort Note Validation of Pleiades Tri-Stereo DSM in Urban Areas
ISPRS Int. J. Geo-Inf. 2018, 7(3), 118; https://doi.org/10.3390/ijgi7030118
Received: 4 January 2018 / Revised: 12 March 2018 / Accepted: 14 March 2018 / Published: 15 March 2018
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Abstract
We present an accurate digital surface model (DSM) derived from high-resolution Pleiades-1B 0.5 m panchromatic tri-stereo images, covering an area of 400 km2 over the Athens Metropolitan Area. Remote sensing and photogrammetry tools were applied, resulting in a 1 m × 1
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We present an accurate digital surface model (DSM) derived from high-resolution Pleiades-1B 0.5 m panchromatic tri-stereo images, covering an area of 400 km2 over the Athens Metropolitan Area. Remote sensing and photogrammetry tools were applied, resulting in a 1 m × 1 m posting DSM over the study area. The accuracy of the produced DSM was evaluated against measured elevations by a differential Global Positioning System (d-GPS) and a reference DSM provided by the National Cadaster and Mapping Agency S.A. Different combinations of stereo and tri-stereo images were used and tested on the quality of the produced DSM. Results revealed that the DSM produced by the tri-stereo analysis has a root mean square error (RMSE) of 1.17 m in elevation, which lies within the best reported in the literature. On the other hand, DSMs derived by standard analysis of stereo-pairs from the same sensor were found to perform worse. Line profile data showed similar patterns between the reference and produced DSM. Pleiades tri-stereo high-quality DSM products have the necessary accuracy to support applications in the domains of urban planning, including climate change mitigation and adaptation, hydrological modelling, and natural hazards, being an important input for simulation models and morphological analysis at local scales. Full article
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Open AccessArticle Graph-Based Matching of Points-of-Interest from Collaborative Geo-Datasets
ISPRS Int. J. Geo-Inf. 2018, 7(3), 117; https://doi.org/10.3390/ijgi7030117
Received: 30 November 2017 / Revised: 6 February 2018 / Accepted: 12 March 2018 / Published: 15 March 2018
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Abstract
Several geospatial studies and applications require comprehensive semantic information from points-of-interest (POIs). However, this information is frequently dispersed across different collaborative mapping platforms. Surprisingly, there is still a research gap on the conflation of POIs from this type of geo-dataset. In this paper,
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Several geospatial studies and applications require comprehensive semantic information from points-of-interest (POIs). However, this information is frequently dispersed across different collaborative mapping platforms. Surprisingly, there is still a research gap on the conflation of POIs from this type of geo-dataset. In this paper, we focus on the matching aspect of POI data conflation by proposing two matching strategies based on a graph whose nodes represent POIs and edges represent matching possibilities. We demonstrate how the graph is used for (1) dynamically defining the weights of the different POI similarity measures we consider; (2) tackling the issue that POIs should be left unmatched when they do not have a corresponding POI on the other dataset and (3) detecting multiple POIs from the same place in the same dataset and jointly matching these to the corresponding POI(s) from the other dataset. The strategies we propose do not require the collection of training samples or extensive parameter tuning. They were statistically compared with a “naive”, though commonly applied, matching approach considering POIs collected from OpenStreetMap and Foursquare from the city of London (England). In our experiments, we sequentially included each of our methodological suggestions in the matching procedure and each of them led to an increase in the accuracy in comparison to the previous results. Our best matching result achieved an overall accuracy of 91%, which is more than 10% higher than the accuracy achieved by the baseline method. Full article
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Open AccessArticle Progressive Amalgamation of Building Clusters for Map Generalization Based on Scaling Subgroups
ISPRS Int. J. Geo-Inf. 2018, 7(3), 116; https://doi.org/10.3390/ijgi7030116
Received: 7 January 2018 / Revised: 23 February 2018 / Accepted: 13 March 2018 / Published: 15 March 2018
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Abstract
Map generalization utilizes transformation operations to derive smaller-scale maps from larger-scale maps, and is a key procedure for the modelling and understanding of geographic space. Studies to date have largely applied a fixed tolerance to aggregate clustered buildings into a single object, resulting
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Map generalization utilizes transformation operations to derive smaller-scale maps from larger-scale maps, and is a key procedure for the modelling and understanding of geographic space. Studies to date have largely applied a fixed tolerance to aggregate clustered buildings into a single object, resulting in the loss of details that meet cartographic constraints and may be of importance for users. This study aims to develop a method that amalgamates clustered buildings gradually without significant modification of geometry, while preserving the map details as much as possible under cartographic constraints. The amalgamation process consists of three key steps. First, individual buildings are grouped into distinct clusters by using the graph-based spatial clustering application with random forest (GSCARF) method. Second, building clusters are decomposed into scaling subgroups according to homogeneity with regard to the mean distance of subgroups. Thus, hierarchies of building clusters can be derived based on scaling subgroups. Finally, an amalgamation operation is progressively performed from the bottom-level subgroups to the top-level subgroups using the maximum distance of each subgroup as the amalgamating tolerance instead of using a fixed tolerance. As a consequence of this step, generalized intermediate scaling results are available, which can form the multi-scale representation of buildings. The experimental results show that the proposed method can generate amalgams with correct details, statistical area balance and orthogonal shape while satisfying cartographic constraints (e.g., minimum distance and minimum area). Full article
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Open AccessArticle Spatial Transformation of Equality – Generalized Travelling Salesman Problem to Travelling Salesman Problem
ISPRS Int. J. Geo-Inf. 2018, 7(3), 115; https://doi.org/10.3390/ijgi7030115
Received: 9 February 2018 / Revised: 23 February 2018 / Accepted: 23 February 2018 / Published: 15 March 2018
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Abstract
The Equality-Generalized Travelling Salesman Problem (E-GTSP), which is an extension of the Travelling Salesman Problem (TSP), is stated as follows: given groups of points within a city, like banks, supermarkets, etc., find a minimum cost Hamiltonian cycle that visits each group exactly once.
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The Equality-Generalized Travelling Salesman Problem (E-GTSP), which is an extension of the Travelling Salesman Problem (TSP), is stated as follows: given groups of points within a city, like banks, supermarkets, etc., find a minimum cost Hamiltonian cycle that visits each group exactly once. It can model many real-life combinatorial optimization scenarios more efficiently than TSP. This study presents five spatially driven search-algorithms for possible transformation of E-GTSP to TSP by considering the spatial spread of points in a given urban city. Presented algorithms are tested over 15 different cities, classified by their street-network’s fractal-dimension. Obtained results denote that the R-Search algorithm, which selects the points from each group based on their radial separation with respect to the start–end point, is the best search criterion for any E-GTSP to TSP conversion modelled for a city street network. An 8.8% length error has been reported for this algorithm. Full article
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Open AccessArticle Accuracy Assessment of Different Digital Surface Models
ISPRS Int. J. Geo-Inf. 2018, 7(3), 114; https://doi.org/10.3390/ijgi7030114
Received: 21 January 2018 / Revised: 19 February 2018 / Accepted: 12 March 2018 / Published: 15 March 2018
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Abstract
Digital elevation models (DEMs), which can occur in the form of digital surface models (DSMs) or digital terrain models (DTMs), are widely used as important geospatial information sources for various remote sensing applications, including the precise orthorectification of high-resolution satellite images, 3D spatial
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Digital elevation models (DEMs), which can occur in the form of digital surface models (DSMs) or digital terrain models (DTMs), are widely used as important geospatial information sources for various remote sensing applications, including the precise orthorectification of high-resolution satellite images, 3D spatial analyses, multi-criteria decision support systems, and deformation monitoring. The accuracy of DEMs has direct impacts on specific calculations and process chains; therefore, it is important to select the most appropriate DEM by considering the aim, accuracy requirement, and scale of each study. In this research, DSMs obtained from a variety of satellite sensors were compared to analyze their accuracy and performance. For this purpose, freely available Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m, Shuttle Radar Topography Mission (SRTM) 30 m, and Advanced Land Observing Satellite (ALOS) 30 m resolution DSM data were obtained. Additionally, 3 m and 1 m resolution DSMs were produced from tri-stereo images from the SPOT 6 and Pleiades high-resolution (PHR) 1A satellites, respectively. Elevation reference data provided by the General Command of Mapping, the national mapping agency of Turkey—produced from 30 cm spatial resolution stereo aerial photos, with a 5 m grid spacing and ±3 m or better overall vertical accuracy at the 90% confidence interval (CI)—were used to perform accuracy assessments. Gross errors and water surfaces were removed from the reference DSM. The relative accuracies of the different DSMs were tested using a different number of checkpoints determined by different methods. In the first method, 25 checkpoints were selected from bare lands to evaluate the accuracies of the DSMs on terrain surfaces. In the second method, 1000 randomly selected checkpoints were used to evaluate the methods’ accuracies for the whole study area. In addition to the control point approach, vertical cross-sections were extracted from the DSMs to evaluate the accuracies related to land cover. The PHR and SPOT DSMs had the highest accuracies of all of the testing methods, followed by the ALOS DSM, which had very promising results. Comparatively, the SRTM and ASTER DSMs had the worst accuracies. Additionally, the PHR and SPOT DSMs captured man-made objects and above-terrain structures, which indicated the need for post-processing to attain better representations. Full article
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Open AccessArticle OSM Data Import as an Outreach Tool to Trigger Community Growth? A Case Study in Miami
ISPRS Int. J. Geo-Inf. 2018, 7(3), 113; https://doi.org/10.3390/ijgi7030113
Received: 1 January 2018 / Revised: 26 February 2018 / Accepted: 12 March 2018 / Published: 15 March 2018
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Abstract
This paper presents the results of a study that explored if and how an OpenStreetMap (OSM) data import task can contribute to OSM community growth. Different outreach techniques were used to introduce a building import task to three targeted OSM user groups. First,
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This paper presents the results of a study that explored if and how an OpenStreetMap (OSM) data import task can contribute to OSM community growth. Different outreach techniques were used to introduce a building import task to three targeted OSM user groups. First, existing OSM members were contacted and asked to join the data import project. Second, several local community events were organized with Maptime Miami to engage local mappers in OSM contribution activities. Third, the import task was introduced as an extra credit assignment in two GIS courses at the University of Florida. The paper analyzes spatio-temporal user contributions of these target groups to assess the effectiveness of the different outreach techniques for recruitment and retention of OSM contributors. Results suggest that the type of prospective users that were contacted through our outreach efforts, and their different motivations play a major role in their editing activity. Results also revealed differences in editing patterns between newly recruited users and already established mappers. More specifically, long-term engagement of newly registered OSM mappers did not succeed, whereas already established contributors continued to import and improve data. In general, we found that an OSM data import project can add valuable data to the map, but also that encouraging long-term engagement of new users, whether it be within the academic environment or outside, proved to be challenging. Full article
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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