The Spatial Analysis and Modeling (SAM) Specialty Group of the Association of American Geographers (AAG) is currently soliciting research papers to be published in a special issue of International Journal of Applied Geospatial Research (IJAGR). We specifically look for papers that illustrate recent advances in spatial and temporal data analysis to address geographical issues, as well as related research in spatial data mining. Authors who are interested in contributing to the special issue should submit a letter of intent that describes the main content of paper by September 15, 2010. The guest editors will decide if the paper fits the scope of the special issue and invite the authors of selected papers to submit a full paper by January 15, 2011.
Many geographic phenomena occur in both space and time. Methods for spatial and temporal analyses have been increasingly important for spatial studies due to the rich datasets that have been made available for a wide range of applications. These methods are essential in applications such as spatial patterns of traffic accidents, infant mortality variations, landscape pattern changes, and unemployment rate changes, often over multiple time periods. We welcome papers in all relevant research areas including, but not limited to, transportation, urban and environment planning, crime, health, economics, statistics, and GIS.
This special issue aims at introducing the spatial and temporal data analysis to the GIScience/SAM/IJAGR audience.
Topics to be discussed in this special issue include (but are not limited to) the following:
- Applications of tools such as GIS or remote sensing for space-time analysis
- Multilevel modeling
- Panel/Longitudinal data analysis
- Space and time model
- Space-time analyses
- Space-time clusters
- Spatial data mining
- Spatial variation in temporal trends
- Spatio-temporal processes
- Spatio-temporal representation/geovisualization
Researchers and practitioners who are interested in contributing to the special issue should submit a letter of intent that describes the main content of paper by September 15, 2010. The guest editors will decide if the paper fits the scope of the special issue and invite the authors of selected papers to submit full papers for this special theme issue on Spatial and Temporal Data Analysis on or before January 15, 2011. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/development/author_info/guidelines submission.pdf. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.
All submissions and inquiries should be directed to the attention of:
Changjoo Kim (firstname.lastname@example.org)
Eric Delmelle (Eric.Delmelle@uncc.edu)
Ningchuan Xiao (email@example.com)
The Open Geospatial Consortium, Inc. (OGC) members are seeking comments on the “Earth Observation Satellite Tasking Extension for OGC Sensor Planning Service (SPS).” The SPS configuration proposed in this profile supports the programming of Earth Observation (EO) sensor systems. The candidate standard describes a single SPS configuration that can be supported by many satellite data providers who have existing facilities for managing sensor system programming requests.This SPS standard defines interfaces for queries that provide information about the capabilities of a sensor and how to task the sensor, where the sensor may be any type of sensor with a digital interface. The SPS and EO-SPS standards are part of the OGC Sensor Web Enablement (SWE) (http://www.opengeospatial.org/ogc/markets-technologies/swe) suite of standards. SWE standards enable developers to describe, discover, task, and access any Internet or Web accessible sensor, transducer and sensor data repository.
The candidate OGC Sensor Planning Service Application Profile for Earth Observation Sensors and information on submitting comments on this document are available at http://www.opengeospatial.org/standards/requests/70. The public comment period closes on September 16, 2010.
The OGC is an international consortium of more than 395 companies, government agencies, research organizations, and universities participating in a consensus process to develop publicly available geospatial standards. OGC Standards support interoperable solutions that “geo-enable” the Web, wireless and location-based services, and mainstream IT. OGC Standards empower technology developers to make geospatial information and services accessible and useful with any application that needs to be geospatially enabled. Visit the OGC website at http://www.opengeospatial.org/contact.
[Source: OGC press release]
International Journal of Geographical Information Science, Volume 24, Issue 8 August 2010 , pages 1127 – 1147
Wenwen Li; Chaowei Yang; Chongjun Yang
“The increased popularity of standards for geospatial interoperability has led to an increasing number of geospatial Web services (GWSs), such as Web Map Services (WMSs), becoming publicly available on the Internet. However, finding the services in a quick and precise fashion is still a challenge. Traditional methods collect the services through centralized registries, where services can be manually registered. But the metadata of the registered services cannot be updated timely. This paper addresses the above challenges by developing an effective crawler to discover and update the services in (1) proposing an accumulated term frequency (ATF)-based conditional probability model for prioritized crawling, (2) utilizing concurrent multi-threading technique, and (3) adopting an automatic mechanism to update the metadata of identified services. Experiments show that the proposed crawler achieves good performance in both crawling efficiency and results’ coverage/liveliness. In addition, an interesting finding regarding the distribution pattern of WMSs is discussed. We expect this research to contribute to automatic GWS discovery over the large-scale and dynamic World Wide Web and the promotion of operational interoperable distributed geospatial services.”
2010 ESRI International User Conference, San Diego, CA
Hoyong Kim, Jisook Kim, and Hojong Baik
“In this study, we present the influence of sun glare on traffic flow using GIS tool. The analysis was carried out ith following three steps: 1) First, the strength of sun glare is modeled as a function of height and the azimuth of sun over season and over time of day, 2) Using geometry and orientation of highway, the strength of sun glare is estimated on different segments of highway, and 3) using the traffic flow data (i.e., speed, volume, etc) collected from traffic detector system, the relation between traffic flow and sun glare on highway segment are statically examined. It should be noted that GIS provides an excellent tool for analyzing temporal-spatial characteristics imbedded in the different data sets (i.e. sun glare, highway geometry and crash data). For the analysis, traffic data collected from RTMS (Remote Traffic Microwave Sensor) detector system on I-270 around St. Louis area is used.”
Master’s Thesis, Middle East Technical University, September 2007
“Crime is a behavior disorder that is an integrated result of social, economical and environmental factors. In the world today crime analysis is gaining significance and one of the most popular subject is crime prediction. Stakeholders of crime intend to forecast the place, time, number of crimes and crime types to get precautions. With respect to these intentions, in this thesis a spatio-temporal crime prediction model is generated by using time series forecasting with simple spatial disaggregation approach in Geographical Information Systems (GIS).
“The model is generated by utilizing crime data for the year 2003 in Bahçelievler and Merkez Çankaya police precincts. Methodology starts with obtaining clusters with different clustering algorithms. Then clustering methods are compared in terms of land-use and representation to select the most appropriate clustering algorithms. Later crime data is divided into daily apoch, to observe spatiotemporal distribution of crime.
“In order to predict crime in time dimension a time series model (ARIMA) is fitted for each week day, Then the forecasted crime occurrences in time are disagregated according to spatial crime cluster patterns.
“Hence the model proposed in this thesis can give crime prediction in both space and time to help police departments in tactical and planning operations.”