Special Issue "Geosensor Networks and Sensor Web"

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (31 July 2016).

Special Issue Editor

Prof. Dr. Silvia Nittel
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Guest Editor
Spatial Informatics, School of Computing and Information Science & National Center of Geographic Information and Analysis, University of Maine, Orono, ME 04473, USA

Special Issue Information

Dear Colleagues,

The last two decades have seen unprecedented advances in the development and miniaturization of a variety of sensors, as well as inexpensive, small computing platforms, and a plethora of wireless communication media. These technological developments have lead to the related research areas of geosensor networks and the sensor web.

Geosensor networks are wireless, ad hoc sensor networks that employ recent research progress from electrical engineering, computer science, and spatial information science to create small devices, running compact, space and time-aware algorithms for live, in-place analytics. Sensors can range from stationary environmental sensors to drones or autonomous vehicles collecting imagery data, or even to humans acting as sensors using smartphones. The sensor web, on the other hand, realizes the idea of a standardized, interoperable platform for everyone to easily share, find, and access sensor data that is based on space, time, and other attributes, similar to easily searching for and sharing information on the Internet. Today, we see further growth in the availability of massive numbers of real-time sensor streams, precipitating a need for real-time analysis. From a practical perspective, geosensor networks can be simply defined as “networked geosensors”, or networks of sensor nodes deployed in geographic space with various communication topologies. Such geosensor networks enable us to observe, reason about, and react to events in space and time in near real-time. To truly leverage this ubiquitous sensing infrastructure, research advances relating to the sensor web are of utmost importance, enabling easy access, sharing, and interoperability.

We invite original research contributions on all aspects of geosensor networks, the sensor web, and their applications, and, particularly, encourage submissions focusing on the following themes for this Special Issue.

  • ž   Formal foundations of geosensor networks
  • ž   Decentralized spatial computing and spatial self-organization
  • ž   Languages for describing spatial tasks and patterns
  • ž   Real-time sensor data streams
  • ž   Integration of real-time sensor streams and historic streams
  • ž   Data management for Big Sensor Data
  • ž   Integration of heterogenous sensor streams
  • ž   Analytics of sensor data streams
  • ž   Crowdsensing for emergency applications and humans as sensors
  • ž   Cooperative sensing using drones, and UAVs
  • ž   Experiences and lessons learned deploying geosensor networks
  • ž   Geosensor network and sensor web use cases: government, participatory
  • ž   GIS, health, energy, water, climate change, etc.
  • ž   Platforms, architectures and open source software for geosensor
  • ž   Networks and the sensor web
  • ž   Geosensor networks, ontologies and standards
  • ž   Benchmarking geosensor networks
  • ž   Ethical and societal impacts of geosensor networks

Dr. Silvia Nittel
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

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Research

Article
Forecasting Public Transit Use by Crowdsensing and Semantic Trajectory Mining: Case Studies
ISPRS Int. J. Geo-Inf. 2016, 5(10), 180; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5100180 - 30 Sep 2016
Cited by 19 | Viewed by 2099
Abstract
With the growing development of smart cities, public transit forecasting has begun to attract significant attention. In this paper, we propose an approach for forecasting passenger boarding choices and public transit passenger flow. Our prediction model is based on mining common user behaviors [...] Read more.
With the growing development of smart cities, public transit forecasting has begun to attract significant attention. In this paper, we propose an approach for forecasting passenger boarding choices and public transit passenger flow. Our prediction model is based on mining common user behaviors for semantic trajectories and enriching features using knowledge from geographic and weather data. All the experimental data comes from the Ridge Nantong Limited bus company and Alibaba platform which is also open to the public. We evaluate our approach using various data sources, including point of interest (POI), weather condition, and public bus information in Guangzhou to demonstrate its effectiveness. Experimental results show that our proposal performs better than baselines in the prediction of passenger boarding choices and public transit passenger flow. Full article
(This article belongs to the Special Issue Geosensor Networks and Sensor Web)
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Article
Field Motion Estimation with a Geosensor Network
ISPRS Int. J. Geo-Inf. 2016, 5(10), 175; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5100175 - 27 Sep 2016
Cited by 3 | Viewed by 2276
Abstract
Physical environmental processes, such as the evolution of precipitation or the diffusion of chemical clouds in the atmosphere, can be approximated by numerical models based on the underlying physics, e.g., for the purpose of prediction. As the modeling process is often very complex [...] Read more.
Physical environmental processes, such as the evolution of precipitation or the diffusion of chemical clouds in the atmosphere, can be approximated by numerical models based on the underlying physics, e.g., for the purpose of prediction. As the modeling process is often very complex and resource demanding, such models are sometimes replaced by those that use historic and current data for calibration. For atmospheric (e.g., precipitation) or oceanographic (e.g., sea surface temperature) fields, the data-driven methods often concern the horizontal displacement driven by transport processes (called advection). These methods rely on flow fields estimated from images of the phenomenon by computer vision techniques, such as optical flow (OF). In this work, an algorithm is proposed for estimating the motion of spatio-temporal fields with the nodes of a geosensor network (GSN) deployed in situ when images are not available. The approach adapts a well-known raster-based OF algorithm to the specifics of GSNs, especially to the spatial irregularity of data. In this paper, the previously introduced approach has been further developed by introducing an error model that derives probabilistic error measures based on spatial node configuration. Further, a more generic motion model is provided, as well as comprehensive simulations that illustrate the performance of the algorithm in different conditions (fields, motion behaviors, node densities and deployments) for the two error measures of motion direction and motion speed. Finally, the algorithm is applied to data sampled from weather radar images, and the algorithm performance is compared to that of a state-of-the-art OF algorithm applied to the weather radar images directly, as often done in nowcasting. Full article
(This article belongs to the Special Issue Geosensor Networks and Sensor Web)
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Article
A Sensor Web and Web Service-Based Approach for Active Hydrological Disaster Monitoring
ISPRS Int. J. Geo-Inf. 2016, 5(10), 171; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5100171 - 24 Sep 2016
Cited by 7 | Viewed by 2819
Abstract
Rapid advancements in Earth-observing sensor systems have led to the generation of large amounts of remote sensing data that can be used for the dynamic monitoring and analysis of hydrological disasters. The management and analysis of these data could take advantage of distributed [...] Read more.
Rapid advancements in Earth-observing sensor systems have led to the generation of large amounts of remote sensing data that can be used for the dynamic monitoring and analysis of hydrological disasters. The management and analysis of these data could take advantage of distributed information infrastructure technologies such as Web service and Sensor Web technologies, which have shown great potential in facilitating the use of observed big data in an interoperable, flexible and on-demand way. However, it remains a challenge to achieve timely response to hydrological disaster events and to automate the geoprocessing of hydrological disaster observations. This article proposes a Sensor Web and Web service-based approach to support active hydrological disaster monitoring. This approach integrates an event-driven mechanism, Web services, and a Sensor Web and coordinates them using workflow technologies to facilitate the Web-based sharing and processing of hydrological hazard information. The design and implementation of hydrological Web services for conducting various hydrological analysis tasks on the Web using dynamically updating sensor observation data are presented. An application example is provided to demonstrate the benefits of the proposed approach over the traditional approach. The results confirm the effectiveness and practicality of the proposed approach in cases of hydrological disaster. Full article
(This article belongs to the Special Issue Geosensor Networks and Sensor Web)
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Article
A Semantic Registry Method Using Sensor Metadata Ontology to Manage Heterogeneous Sensor Information in the Geospatial Sensor Web
ISPRS Int. J. Geo-Inf. 2016, 5(5), 63; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5050063 - 13 May 2016
Cited by 8 | Viewed by 2731
Abstract
Efficient information management and precise discovery of heterogeneous sensors in the Geospatial Sensor Web (GSW) are a major challenge. Intelligent sensor management requires a registry service to store and process sensor information efficiently. In this paper, we propose a Sensor Metadata Ontology (SMO) [...] Read more.
Efficient information management and precise discovery of heterogeneous sensors in the Geospatial Sensor Web (GSW) are a major challenge. Intelligent sensor management requires a registry service to store and process sensor information efficiently. In this paper, we propose a Sensor Metadata Ontology (SMO) to achieve a unified semantic description for heterogeneous sensors that is used to express sensor semantics. Through mapping between the sensor registry information model and the SMO, the sensor metadata could be stored with semantic information for the registry. The framework of a Sensor Semantic Registry Service (SSRS) has been successfully implemented for the registration and discovery of heterogeneous sensors. The results of GEOSENSOR-SSRS experiments show that the proposed semantic registry method can be used to enable sharing in an open distributed sensor network as well as to promote accuracy and efficiency of discovery. Full article
(This article belongs to the Special Issue Geosensor Networks and Sensor Web)
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Article
An Assessment of Urban Surface Energy Fluxes Using a Sub-Pixel Remote Sensing Analysis: A Case Study in Suzhou, China
ISPRS Int. J. Geo-Inf. 2016, 5(2), 11; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5020011 - 04 Feb 2016
Cited by 14 | Viewed by 2540
Abstract
Urban surface energy fluxes are closely associated with land-cover types (LCTs) and critical biophysical compositions. This study aims to assess the contribution of LCTs, vegetation fractional coverage (VFC) and percentage of impervious surface area (ISA%) to urban surface energy fluxes using remote sensing. [...] Read more.
Urban surface energy fluxes are closely associated with land-cover types (LCTs) and critical biophysical compositions. This study aims to assess the contribution of LCTs, vegetation fractional coverage (VFC) and percentage of impervious surface area (ISA%) to urban surface energy fluxes using remote sensing. An advanced urban surface energy flux algorithm was used to combine satellite imagery and meteorological station data to investigate the thermal environments in the city of Suzhou, China. The land cover abundances retrieved by multiple endmember spectral unmixing analysis (MESMA) were used to retrieve the per-pixel sensible heat flux (H) and latent heat flux (LE). The resultant heat fluxes were assessed using evaporation pan data collected from meteorological stations and ratios of the heat fluxes to the net radiation (Rn). Furthermore, spatial patterns of urban heat energy were investigated using an integrated analysis among land surface temperature (LST), heat fluxes, LCTs, VFC and ISA%. The high values of H and LST were found over the urbanized areas, which also had low values of LE. Conversely, the vegetated area was characterized with high LEs, as well as low LSTs and Hs. Moreover, a statistically-significant correlation (p < 0.05; R2 = 0.88) was observed between LE and VFC at the zonal level, and a statistically-significant correlation (p < 0.05; R2 = 0.90) was exhibited between H and ISA%. It is concluded that VFC, ISA% and LCTs are promising for delineating urban heat fluxes. Overall, this study indicates that remote sensing techniques can be used to quantify urban thermal environments. Full article
(This article belongs to the Special Issue Geosensor Networks and Sensor Web)
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