Spatial Analysis for Crime Pattern of Metropolis in Transition Using Police Records and GIS: A Case Study of Shanghai, China

JDCTA: International Journal of Digital Content Technology and its Applications, Vol. 5, No. 2, pp. 93 ~ 105, 2011

Haidong Zhong, Jie Yin, Jianping Wu, Shenjun Yao, Zhanhong Wang, Zhenhua Lv, and Bailang Yu

“Crime is a long plagued issue of human society. Especially, with the expansion of cities and population aggregation in recent years, crime problems have become a great challenge in urbanization process. Both urban policy-makers and police departments have realized the importance of a better understanding of the dynamics of crime. This study explores the spatial characteristic of crime in Shanghai using Geographical Information System (GIS) and police call data of the metropolis in 2006. In the research, the combination of both applied and theoretical methods is used to analyze the characteristics of Shanghai crime. To find out the crime pattern of the city, three spatial levels (i.e. macrolevel, mesolevel and microlevel) are adopted. In this paper the crime is divided into two categories: violent crime and property crime. The spatial distribution of the two kinds of crimes is analyzed on a comparative basis of different properties in terms of land use type and population features, and the relevant factors of the crime pattern are investigated. The results reveal that there are some hotspots in downtown, transportation hubs, where population density is relatively high and the crime density decreases gradually away from the center. The analytical and theoretical result will undoubtedly lead to enhanced crime prevention strategies of Shanghai in the future.”

Privacy Issues in Geospatial Visual Analytics

GeoViz: Linking Geovisualization with Spatial Analysis and Modeling, 10-11 March 2011, Hamburg, Germany

Gennady Andrienko and Natalia Andrienko

“Visual and interactive techniques can pose specific challenges to personal privacy by enabling a human analyst to link data to context, pre-existing knowledge, and additional information obtained from various sources. Unlike in computational analysis, relevant knowledge and information do not have to be represented in a structured form in order to be used effectively by a human. Furthermore, humans can note such kinds of patterns and relationships that are hard to formalize and detect by computational techniques. The privacy issues related to the use of visual and interactive methods are currently studied neither in the areas of visualization and visual analytics nor in the area of data mining and computational analysis. There is a need to fill this gap, which requires concerted inter-disciplinary efforts.”

Methods of Spatial Knowledge Discovery in the Scope of Planning and Development

GeoViz: Linking Geovisualization with Spatial Analysis and Modeling, 10-11 March 2011, Hamburg, Germany

Martin Behnisch and Alfred Ultsch

“Most of the large databases currently available have a strong spatio-temporal component and potentially contain information that might be of value. Cartographic visualizations usually provide information of low dimensional data sets (e.g. distribution, density, correlation, structure or the spatial/temporary change). Data mining in connection with knowledge discovery techniques play an important role for the empirical visualization and examination and of high dimensional spatial data. The increasing discussions about data interoperability require a transparent transfer of spatial semantics (metaphors, abstractions) and a comprehensible syntax (Shekhar 2003). However procedures on the basis of knowledge discovery are currently not exactly scrutinised for a meaningful integration into the regional/urban planning and development process (Demsar, 2006, Behnisch, 2009).”

Nominations Process for URISA’s GIS Hall of Fame Opens

Nominations for URISA’s GIS Hall of Fame are being accepted until May 1, 2011.  URISA established the GIS Hall of Fame in 2005 to recognize and honor the most esteemed leaders of the geospatial community. To be considered for the GIS Hall of Fame, an individual’s or an organization’s record of contribution to the advancement of the industry demonstrates creative thinking and actions, vision and innovation, inspiring leadership, perseverance, and community mindedness. In addition, nominees must serve as a role model for those who follow. URISA Hall of Fame Laureates are individuals or organizations whose pioneering work has moved the geospatial industry in a better, stronger direction.

URISA welcomes nominations from any profession and is not restricted to those having a past or current relationship with URISA. This award is not given every year, and some years there may be multiple recipients.

The selection criteria for this honor are:

  • At least 25 years of sustained professional involvement in the GIS field.
  • Original and creative contributions to the field.
  • Well known and respected by a wide range of peers.
  • Consistent demonstration of sound professional and personal ethics.

Previous inductees include:

  • 2005: Edgar Horwood, Ian McHarg, Roger Tomlinson, Jack Dangermond, Nancy Tosta, and the Harvard Lab
  • 2006: Dr. Gary Hunter
  • 2007: Don Cooke and Michael Goodchild
  • 2009: Will Craig and Carl Reed
  • 2010: C. Dana Tomlin

Nominations must be submitted to URISA by May 1. For details and to learn more about current members of URISA’s GIS Hall of Fame, visit: http://www.urisa.org/hall_of_fame

[Source: URISA press release]