Next Issue
Previous Issue

Table of Contents

ISPRS Int. J. Geo-Inf., Volume 6, Issue 9 (September 2017)

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Cover Story (view full-size image) We developed an approach for optimal indoor transportation of assets based on an ad-hoc suitability [...] Read more.
View options order results:
result details:
Displaying articles 1-32
Export citation of selected articles as:
Open AccessArticle Improving Destination Choice Modeling Using Location-Based Big Data
ISPRS Int. J. Geo-Inf. 2017, 6(9), 291; https://doi.org/10.3390/ijgi6090291
Received: 30 July 2017 / Revised: 15 September 2017 / Accepted: 18 September 2017 / Published: 20 September 2017
Cited by 1 | PDF Full-text (3804 KB) | HTML Full-text | XML Full-text
Abstract
Citizens are increasingly sharing their location and movements through “check-ins” on location based social networks (LBSNs). These services are collecting unprecedented amounts of big data that can be used to study how we travel and interact with our environment. This paper presents the
[...] Read more.
Citizens are increasingly sharing their location and movements through “check-ins” on location based social networks (LBSNs). These services are collecting unprecedented amounts of big data that can be used to study how we travel and interact with our environment. This paper presents the development of a long distance destination choice model for Ontario, Canada, using data from Foursquare to model destination attractiveness. A methodology to collect and process historical check-in counts has been developed, allowing the utility of each destination to be calculated based on the intensity of different activities performed at the destination. Destinations such as national parks and ski areas are very strong attractors of leisure trips, yet do not employ many people and have few residents. Trip counts to such destinations are therefore poorly predicted by models based on population and employment. Traditionally, this has been remedied by extensive manual data collection. The integration of Foursquare data offers an alternative approach to this problem. The Foursquare based destination choice model was evaluated against a traditional model estimated only with population and employment. The results demonstrate that data from LBSNs can be used to improve destination choice models, particularly for leisure travel. Full article
(This article belongs to the Special Issue Geospatial Big Data and Transport)
Figures

Figure 1

Open AccessArticle Selecting the Best Band Ratio to Estimate Chlorophyll-a Concentration in a Tropical Freshwater Lake Using Sentinel 2A Images from a Case Study of Lake Ba Be (Northern Vietnam)
ISPRS Int. J. Geo-Inf. 2017, 6(9), 290; https://doi.org/10.3390/ijgi6090290
Received: 10 August 2017 / Revised: 7 September 2017 / Accepted: 11 September 2017 / Published: 13 September 2017
Cited by 2 | PDF Full-text (5178 KB) | HTML Full-text | XML Full-text
Abstract
This study aims to develop a method to estimate chlorophyll-a concentration (Chla) in tropical freshwater lake waters using in situ data of Chla, water reflectance, and concurrent Sentinel 2A MSI imagery (S2A) over Lake Ba Be, a Ramsar site and the largest natural
[...] Read more.
This study aims to develop a method to estimate chlorophyll-a concentration (Chla) in tropical freshwater lake waters using in situ data of Chla, water reflectance, and concurrent Sentinel 2A MSI imagery (S2A) over Lake Ba Be, a Ramsar site and the largest natural freshwater lake in Vietnam. Data from 30 surveyed sampling sites over the lake water in June 2016 and May 2017 demonstrated the appropriateness of S2A green-red band ratio (band 3 versus band 4) for estimating Chla. This was shown through a strong correlation of corresponded field measured reflectance ratio with Chla by an exponential curve (r2 = 0.68; the mean standard error of the estimates corresponding to 5% of the mean value of in situ Chla). The small error between in situ Chla, and estimated Chla from S2A acquired concurrently, confirmed the S2A green-red band ratio as the most suitable option for monitoring Chla in Lake Ba Be water. Resultant Chla distribution maps over time described a partially-seasonal pattern and also displayed the spatial dynamic of Chla in the lake. This allows a better understanding of the lake’s limnological processes to be developed and provides an insight into the factors that affect lake water quality. The results also confirmed the potential of S2A to be used as a free tool for lake monitoring and research due to high spatial resolution data (10 m pixel size). Full article
Figures

Figure 1

Open AccessArticle Monitoring and Modeling of Spatiotemporal Urban Expansion and Land-Use/Land-Cover Change Using Integrated Markov Chain Cellular Automata Model
ISPRS Int. J. Geo-Inf. 2017, 6(9), 288; https://doi.org/10.3390/ijgi6090288
Received: 7 August 2017 / Revised: 1 September 2017 / Accepted: 6 September 2017 / Published: 8 September 2017
Cited by 8 | PDF Full-text (10779 KB) | HTML Full-text | XML Full-text
Abstract
Spatial–temporal analysis of land-use/land-cover (LULC) change as well as the monitoring and modeling of urban expansion are essential for the planning and management of urban environments. Such environments reflect the economic conditions and quality of life of the individual country. Urbanization is generally
[...] Read more.
Spatial–temporal analysis of land-use/land-cover (LULC) change as well as the monitoring and modeling of urban expansion are essential for the planning and management of urban environments. Such environments reflect the economic conditions and quality of life of the individual country. Urbanization is generally influenced by national laws, plans and policies and by power, politics and poor governance in many less-developed countries. Remote sensing tools play a vital role in monitoring LULC change and measuring the rate of urbanization at both the local and global levels. The current study evaluated the LULC changes and urban expansion of Jhapa district of Nepal. The spatial–temporal dynamics of LULC were identified using six time-series atmospherically-corrected surface reflectance Landsat images from 1989 to 2016. A hybrid cellular automata Markov chain (CA–Markov) model was used to simulate future urbanization by 2026 and 2036. The analysis shows that the urban area has increased markedly and is expected to continue to grow rapidly in the future, whereas the area for agriculture has decreased. Meanwhile, forest and shrub areas have remained almost constant. Seasonal rainfall and flooding routinely cause predictable transformation of sand, water bodies and cultivated land from one type to another. The results suggest that the use of Landsat time-series archive images and the CA–Markov model are the best options for long-term spatiotemporal analysis and achieving an acceptable level of prediction accuracy. Furthermore, understanding the relationship between the spatiotemporal dynamics of urbanization and LULC change and simulating future landscape change is essential, as they are closely interlinked. These scientific findings of past, present and future land-cover scenarios of the study area will assist planners/decision-makers to formulate sustainable urban development and environmental protection plans and will remain a scientific asset for future generations. Full article
Figures

Figure 1

Open AccessArticle Topographic Correction to Landsat Imagery through Slope Classification by Applying the SCS + C Method in Mountainous Forest Areas
ISPRS Int. J. Geo-Inf. 2017, 6(9), 287; https://doi.org/10.3390/ijgi6090287
Received: 5 June 2017 / Revised: 11 August 2017 / Accepted: 6 September 2017 / Published: 8 September 2017
PDF Full-text (3895 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The aim of the topographic normalization of remotely sensed imagery is to reduce reflectance variability caused by steep terrain and thus improve further processing of images. A process of topographic correction was applied to Landsat imagery in a mountainous forest area in the
[...] Read more.
The aim of the topographic normalization of remotely sensed imagery is to reduce reflectance variability caused by steep terrain and thus improve further processing of images. A process of topographic correction was applied to Landsat imagery in a mountainous forest area in the south of Mexico. The method used was the Sun Canopy Sensor + C correction (SCS + C) where the C parameter was differently determined according to a classification of the topographic slopes of the studied area in nine classes for each band, instead of using a single C parameter for each band. A comparative, visual, and numerical analysis of the normalized reflectance was performed based on the corrected images. The results showed that the correction by slope classification improves the elimination of the effect of shadows and relief, especially in steep slope areas, modifying the normalized reflectance values according to the combination of slope, aspect, and solar geometry, obtaining reflectance values more suitable than the correction by non-slope classification. The application of the proposed method can be generalized, improving its performance in forest mountainous areas. Full article
Figures

Figure 1

Open AccessArticle A New Endmember Preprocessing Method for the Hyperspectral Unmixing of Imagery Containing Marine Oil Spills
ISPRS Int. J. Geo-Inf. 2017, 6(9), 286; https://doi.org/10.3390/ijgi6090286
Received: 12 July 2017 / Revised: 17 August 2017 / Accepted: 6 September 2017 / Published: 8 September 2017
PDF Full-text (11657 KB) | HTML Full-text | XML Full-text
Abstract
The current methods that use hyperspectral remote sensing imagery to extract and monitor marine oil spills are quite popular. However, the automatic extraction of endmembers from hyperspectral imagery remains a challenge. This paper proposes a data field-spectral preprocessing (DSPP) algorithm for endmember extraction.
[...] Read more.
The current methods that use hyperspectral remote sensing imagery to extract and monitor marine oil spills are quite popular. However, the automatic extraction of endmembers from hyperspectral imagery remains a challenge. This paper proposes a data field-spectral preprocessing (DSPP) algorithm for endmember extraction. The method first derives a set of extreme points from the data field of an image. At the same time, it identifies a set of spectrally pure points in the spectral space. Finally, the preprocessing algorithm fuses the data field with the spectral calculation to generate a new subset of endmember candidates for the following endmember extraction. The processing time is greatly shortened by directly using endmember extraction algorithms. The proposed algorithm provides accurate endmember detection, including the detection of anomalous endmembers. Therefore, it has a greater accuracy, stronger noise resistance, and is less time-consuming. Using both synthetic hyperspectral images and real airborne hyperspectral images, we utilized the proposed preprocessing algorithm in combination with several endmember extraction algorithms to compare the proposed algorithm with the existing endmember extraction preprocessing algorithms. The experimental results show that the proposed method can effectively extract marine oil spill data. Full article
(This article belongs to the Special Issue Oil and Gas Applications of Remote Sensing and UAV Systems)
Figures

Figure 1

Open AccessArticle GeoSpark SQL: An Effective Framework Enabling Spatial Queries on Spark
ISPRS Int. J. Geo-Inf. 2017, 6(9), 285; https://doi.org/10.3390/ijgi6090285
Received: 24 July 2017 / Revised: 1 September 2017 / Accepted: 6 September 2017 / Published: 8 September 2017
PDF Full-text (2806 KB) | HTML Full-text | XML Full-text
Abstract
In the era of big data, Internet-based geospatial information services such as various LBS apps are deployed everywhere, followed by an increasing number of queries against the massive spatial data. As a result, the traditional relational spatial database (e.g., PostgreSQL with PostGIS and
[...] Read more.
In the era of big data, Internet-based geospatial information services such as various LBS apps are deployed everywhere, followed by an increasing number of queries against the massive spatial data. As a result, the traditional relational spatial database (e.g., PostgreSQL with PostGIS and Oracle Spatial) cannot adapt well to the needs of large-scale spatial query processing. Spark is an emerging outstanding distributed computing framework in the Hadoop ecosystem. This paper aims to address the increasingly large-scale spatial query-processing requirement in the era of big data, and proposes an effective framework GeoSpark SQL, which enables spatial queries on Spark. On the one hand, GeoSpark SQL provides a convenient SQL interface; on the other hand, GeoSpark SQL achieves both efficient storage management and high-performance parallel computing through integrating Hive and Spark. In this study, the following key issues are discussed and addressed: (1) storage management methods under the GeoSpark SQL framework, (2) the spatial operator implementation approach in the Spark environment, and (3) spatial query optimization methods under Spark. Experimental evaluation is also performed and the results show that GeoSpark SQL is able to achieve real-time query processing. It should be noted that Spark is not a panacea. It is observed that the traditional spatial database PostGIS/PostgreSQL performs better than GeoSpark SQL in some query scenarios, especially for the spatial queries with high selectivity, such as the point query and the window query. In general, GeoSpark SQL performs better when dealing with compute-intensive spatial queries such as the kNN query and the spatial join query. Full article
Figures

Figure 1

Open AccessArticle Employing Search Engine Optimization (SEO) Techniques for Improving the Discovery of Geospatial Resources on the Web
ISPRS Int. J. Geo-Inf. 2017, 6(9), 284; https://doi.org/10.3390/ijgi6090284
Received: 20 July 2017 / Revised: 11 August 2017 / Accepted: 29 August 2017 / Published: 7 September 2017
PDF Full-text (4624 KB) | HTML Full-text | XML Full-text
Abstract
With the increasing use of geographical information and technology in a variety of knowledge domains and disciplines, the need to discover and access suitable geospatial data is imperative. Most spatial data infrastructures (SDI) provide geoportals as entry points to the SDI through which
[...] Read more.
With the increasing use of geographical information and technology in a variety of knowledge domains and disciplines, the need to discover and access suitable geospatial data is imperative. Most spatial data infrastructures (SDI) provide geoportals as entry points to the SDI through which geospatial data are disseminated and shared. Geoportals are often known in geoinformation communities only, and they present technological challenges for indexing by web search engines. To overcome these challenges, we identified and categorized search terms typically employed by users when looking for geospatial resources on the Web. Guided by these terms, we published metadata about geospatial sources “directly” on the Web and performed empirical tests with search engine optimization (SEO) techniques. Two sets of HTML pages were prepared and registered with Google and Bing respectively. The metadata in one set was marked up with Dublin Core, the other with Schema.org. Analysis of the results shows that Google was more effective than Bing in retrieving the pages. Pages marked up with Schema.org were more effectively retrieved than those marked up with Dublin Core. The statistical results were significant in most of the tests performed. This research confirms that pages marked up with Schema.org and Dublin Core are a novel alternative for improving the visibility and facilitating the discovery of geospatial resources on the Web. Full article
Figures

Figure 1

Open AccessArticle Spatial Modelling and Prediction Assessment of Soil Iron Using Kriging Interpolation with pH as Auxiliary Information
ISPRS Int. J. Geo-Inf. 2017, 6(9), 283; https://doi.org/10.3390/ijgi6090283
Received: 14 July 2017 / Revised: 28 August 2017 / Accepted: 4 September 2017 / Published: 7 September 2017
Cited by 1 | PDF Full-text (3050 KB) | HTML Full-text | XML Full-text
Abstract
In this study, different interpolation techniques are presented, assessed, and compared for the estimation of soil iron (Fe) contents in locations where observations were not available. Initially, 400 soil samples from the Kozani area, which is near Polifitou Lake in northern Greece, were
[...] Read more.
In this study, different interpolation techniques are presented, assessed, and compared for the estimation of soil iron (Fe) contents in locations where observations were not available. Initially, 400 soil samples from the Kozani area, which is near Polifitou Lake in northern Greece, were randomly collected from 2013 to 2015 and were analysed in the laboratory to determine the soil Fe concentrations and pH. The soil Fe concentrations were examined for spatial autocorrelation, and semivariograms were used to determine whether pH and Fe exhibited spatial cross correlation. Three interpolation methods, including Ordinary Kriging, Universal Kriging, and Co-Kriging, were applied, and their results were compared with the use of two different cross-validation methods. In the current study, there was evidence of spatial cross correlation of soil Fe and pH for each year, which was subsequently used to improve the interpolation results in locations where there were no measurements. In nearly all cases, Co-Kriging, which takes advantage of the covariance between the two regionalized variables (Fe and pH), outperformed the other interpolation techniques each year. Full article
Figures

Figure 1

Open AccessArticle The Governance Landscape of Geospatial E-Services—The Belgian Case
ISPRS Int. J. Geo-Inf. 2017, 6(9), 282; https://doi.org/10.3390/ijgi6090282
Received: 14 July 2017 / Revised: 9 August 2017 / Accepted: 21 August 2017 / Published: 7 September 2017
Cited by 1 | PDF Full-text (306 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Geospatial data and geospatial e-services require governance and coordination between different governmental organisations. This article aims to understand what governance, and specifically what coordination, is used in Belgium for geospatial e-services and data. The Belgian case, with a focus on the regions and
[...] Read more.
Geospatial data and geospatial e-services require governance and coordination between different governmental organisations. This article aims to understand what governance, and specifically what coordination, is used in Belgium for geospatial e-services and data. The Belgian case, with a focus on the regions and federal administration, is researched by making use of a document analysis, interviews with key stakeholders and an online survey. In contrast to the federal and Walloon administration, the Flemish administration and the Brussels Capital Region administration have a clearly developed governance model. Flanders combines hierarchy with network governance, whereas the Brussels administration is known for its hierarchical way of working. The transposition of the INSPIRE Directive had a strong influence: The Brussels Capital Region became more network-oriented, and the Walloon Region developed a form of network governance. The federal level, however, struggles to make the connection between geospatial data and e-services. From an inter-organisational perspective, the coordination can be labelled as a weak form of network governance: Cooperation exists, but only in a few areas. Nevertheless, geospatial data are exchanged within and between regions and the federal level. Geospatial e-services are also developed but there is a clear influence of the degree of organisational coordination on the development of geospatial e-services. Full article
(This article belongs to the Special Issue Innovative Geo-Information Tools for Governance)
Open AccessArticle Mapping Parallels between Outdoor Urban Environments and Indoor Manufacturing Environments
ISPRS Int. J. Geo-Inf. 2017, 6(9), 281; https://doi.org/10.3390/ijgi6090281
Received: 11 July 2017 / Revised: 24 August 2017 / Accepted: 4 September 2017 / Published: 6 September 2017
PDF Full-text (1581 KB) | HTML Full-text | XML Full-text
Abstract
The concepts of “Smart Cities” and “Smart Manufacturing” are different data-driven domains, although both rely on intelligent information technology and data analysis. With the application of linked data and affordance-based approaches, both domains converge, paving the way for new and innovative viewpoints regarding
[...] Read more.
The concepts of “Smart Cities” and “Smart Manufacturing” are different data-driven domains, although both rely on intelligent information technology and data analysis. With the application of linked data and affordance-based approaches, both domains converge, paving the way for new and innovative viewpoints regarding the comparison of urban tasks with indoor manufacturing tasks. The present study builds on the work, who state that cities are scaled versions of each other, by extending this thesis towards indoor manufacturing environments. Based on their structure and complexity, these environments are considered to form ecosystems of their own, comparable to “small cities”. This conceptual idea is demonstrated by examining the process of human problem-solving in transportation situations from both perspectives (i.e., city-level and manufacturing-level). In particular, the authors model tasks of human operators that are used to support transportation processes in indoor manufacturing environments based on affordances and spatial-temporal data. This paper introduces the fundamentals of the transformation process of outdoor tasks and process planning activities to indoor environments, particularly to semiconductor manufacturing environments. The idea is to examine the mapping of outdoor tasks and applications to indoor environments, and vice-versa, based on an example focusing on the autonomous transportation of production assets in a manufacturing environment. The approach is based on a spatial graph database, populated with an indoor navigation ontology and instances of indoor and outdoor objects. The results indicate that human problem-solving strategies can be applied to indoor manufacturing environments to support decision-making in autonomous transportation tasks. Full article
Figures

Figure 1

Open AccessArticle Towards an Affordance-Based Ad-Hoc Suitability Network for Indoor Manufacturing Transportation Processes
ISPRS Int. J. Geo-Inf. 2017, 6(9), 280; https://doi.org/10.3390/ijgi6090280
Received: 30 June 2017 / Revised: 19 August 2017 / Accepted: 31 August 2017 / Published: 5 September 2017
Cited by 1 | PDF Full-text (3253 KB) | HTML Full-text | XML Full-text
Abstract
In manufacturing companies, productivity and efficiency are the main priorities, besides an emphasis on quality issues. The outcome of this research contributes to increasing production quality and efficiency in manufacturing. The article deals with indoor manufacturing environments and the transportation processes of production
[...] Read more.
In manufacturing companies, productivity and efficiency are the main priorities, besides an emphasis on quality issues. The outcome of this research contributes to increasing production quality and efficiency in manufacturing. The article deals with indoor manufacturing environments and the transportation processes of production assets—referred to as smart transportation. The authors modelled the objects present in the indoor manufacturing environment with ontologies including their affordances and spatial suitability. To support flexible production and dynamic transportation processes have to be tailored towards the ‘needs’ of the production asset. Hence, the authors propose an approach utilizing an ad-hoc suitability network to support the “optimal” path computation for transportation processes. The objective is to generate a graph for routing purposes for each individual production asset, with respect to the affordances of the indoor space for each production asset, and measurements of a sensor network. The generation of the graph follows an ad-hoc strategy, in two ways. First, the indoor navigation graph is created exactly when a path needs to be found—when a production asset shall be transported to the next manufacturing step. Secondly, the transportation necessities of each production asset, as well as any disturbances present in the environment, are taken into account at the time of the path calculation. The novelty of this approach is that the development of the navigation graph—including the weights—is done with affordances, which are based on an ontology. To realize the approach, the authors developed a linked data approach based on manufacturing data and on an application ontology, linking the indoor manufacturing environment and a graph-based network. The linked data approach is finally implemented as a spatial graph database containing walkable corridors, production equipment, assets and a sensor network. The results show the optimal path for transportation processes with respect to affordances of the indoor manufacturing environments. An evaluation of the computational complexity shows that the affordance-based ad-hoc graphs are thinner and thus reduce the computational complexity of shortest path calculations. Hence, we conclude that an affordance-based approach can help to decrease computational efforts for calculating “optimal” paths for transportation purposes. Full article
(This article belongs to the Special Issue 3D Indoor Modelling and Navigation)
Figures

Figure 1

Open AccessNew Book Received Making Spatial Decisions Using ArcGIS Pro: A Workbook. By Kathryn Keranen and Robert Kolvoord, Esri Press, 2017; 376 Pages. Price $69.99, ISBN 9781589484849
ISPRS Int. J. Geo-Inf. 2017, 6(9), 279; https://doi.org/10.3390/ijgi6090279
Received: 1 September 2017 / Revised: 4 September 2017 / Accepted: 4 September 2017 / Published: 5 September 2017
PDF Full-text (170 KB) | HTML Full-text | XML Full-text
Abstract
The following paragraphs have been reproduced from the website of the publisher [1]:[...] Full article
Open AccessReview Spatial Orientation Skill Improvement with Geospatial Applications: Report of a Multi-Year Study
ISPRS Int. J. Geo-Inf. 2017, 6(9), 278; https://doi.org/10.3390/ijgi6090278
Received: 24 July 2017 / Revised: 29 August 2017 / Accepted: 31 August 2017 / Published: 3 September 2017
PDF Full-text (277 KB) | HTML Full-text | XML Full-text
Abstract
There are several competences and spatial skills to be acquired by the student related to the treatment of geo-information in Science, Technology, Engineering, and Mathematics (STEM) disciplines. Spatial orientation is the spatial skill related to the use of georeferenced information, and geospatial applications
[...] Read more.
There are several competences and spatial skills to be acquired by the student related to the treatment of geo-information in Science, Technology, Engineering, and Mathematics (STEM) disciplines. Spatial orientation is the spatial skill related to the use of georeferenced information, and geospatial applications (on-line map interfaces) such as the spatial data infrastructure offer a great opportunity for development of this skill. In this report we present several experiments, carried out over five academic years with 559 university students, to improve the spatial orientation skill of the students. Survey learning and wayfinding activities were conducted. First- and second-year university students performed the experiments on a PC and also used digital tablet support. The statistical analysis showed that the students improved their spatial orientation skill with a range from 12.90 (minimum) to 19.21 (maximum) measured with the Perspective Taking Spatial Orientation Test, regardless of the academic year, the hardware (PC or Tablet-PC), or the orientation strategy (survey learning or wayfinding). The second year students improved more than those in their first year. The methodologies employed could be developed by teachers or researchers, and the results presented could be taken as a reference for comparisons in future research in the field of strategy planning with geospatial applications and location-based tools for spatial orientation skill improvement in education. Full article
Open AccessArticle Mapping Forest Species in the Central Middle Atlas of Morocco (Azrou Forest) through Remote Sensing Techniques
ISPRS Int. J. Geo-Inf. 2017, 6(9), 275; https://doi.org/10.3390/ijgi6090275
Received: 26 July 2017 / Revised: 12 August 2017 / Accepted: 29 August 2017 / Published: 3 September 2017
Cited by 1 | PDF Full-text (1870 KB) | HTML Full-text | XML Full-text
Abstract
The studies of forest ecosystems from remotely-sensed data are of great interest to researchers because of ecosystem services provided by this ecosystem, including protection of soils and vegetation, climate stabilization, and regulation of the hydrological cycle. In this context, our study focused on
[...] Read more.
The studies of forest ecosystems from remotely-sensed data are of great interest to researchers because of ecosystem services provided by this ecosystem, including protection of soils and vegetation, climate stabilization, and regulation of the hydrological cycle. In this context, our study focused on the use of a spectral angle mapper (SAM) classification method for mapping species in the Azrou Forest, Central Middle Atlas, Morocco. A Sentinel-2A image combined with ground reference data were used in this research. Four classes (holm oak, cedar forest, bare soil, and others-unclassified) were selected; they represent, respectively, 27, 11, 24, and 38% of the study area. The overall accuracy of classification was estimated to be around 99.72%. This work explored the potential of the SAM classification combined with Sentinel-2A data for mapping land cover in the Azrou Forest ecosystem. Full article
Figures

Figure 1

Open AccessArticle Closing Data Gaps with Citizen Science? Findings from the Danube Region
ISPRS Int. J. Geo-Inf. 2017, 6(9), 277; https://doi.org/10.3390/ijgi6090277
Received: 23 May 2017 / Revised: 24 July 2017 / Accepted: 11 August 2017 / Published: 1 September 2017
Cited by 1 | PDF Full-text (8923 KB) | HTML Full-text | XML Full-text
Abstract
Although data is increasingly shared online and accessible for re-use, we still witness heterogeneous coverage of thematic areas and geographic regions. This especially becomes an issue when data is needed for large territories and including different nations, as, for example, required to support
[...] Read more.
Although data is increasingly shared online and accessible for re-use, we still witness heterogeneous coverage of thematic areas and geographic regions. This especially becomes an issue when data is needed for large territories and including different nations, as, for example, required to support macro-regional development policies. Once identified, data gaps might be closed using different approaches. Existing—but so far non accessible—data might be made available; new public sector information could be gathered; or data might be acquired from the private sector. Our work explores a fourth option: closing data gaps with direct contributions from citizen (Citizen Science). This work summarizes a particular case study that was conducted in 2016 in the Danube Region. We provide a gap analysis over an existing macro-regional data infrastructure, and examine potential Citizen Science approaches that might help to close these gaps. We highlight already existing Citizen Science projects that could address a large part of the identified gaps, and suggest one particular new application in order to indicate how a—so far uncovered—gap might be approached. This new application addresses bioenergy as a particular field of the circular economy. On this basis we discuss the emerging opportunities and challenges for this particular way of public participation in regional development policy. We close by highlighting areas for future research. Full article
(This article belongs to the Special Issue Innovative Geo-Information Tools for Governance)
Figures

Figure 1

Back to Top