PenBay Integrates Esri and ARCHIBUS Software for 3D Facilities Management at UNCC

The University of North Carolina, Charlotte (UNCC), is implementing an integrated facilities management system based on Esri’s ArcGIS Server and ARCHIBUS Web Central software. The system will store and display data based on the facilities’ geographic location. This will add location-based intelligence to the university’s structural asset database as well as speed work order processing, improve business insight, and extend the life cycle of asset information.

UNCC is working with PenBay Solutions LLC of Brunswick, Maine, an Esri partner, to establish an enterprise geographic information system (GIS). UNCC was initially interested in simply locating all buildings, equipment, and grounds to help with work order execution. The extensive capabilities of ArcGIS Server expanded the scope of the project.

“We are able to include 3D representation of the buildings on campus as well as visually query assets,” says Ray Dinello, director of Facilities Information Systems, UNCC. “Being able to link to the university’s building automation system is providing us with the ability to pull together an integrated perspective of our facilities.”

The university has integrated ArcGIS Server Advanced Enterprise edition and ARCHIBUS Geospatial Module for Esri as well as developed custom tools and libraries with the ArcGIS API for JavaScript. Integration of these GIS tools with existing and newly created ARCHIBUS views will spatially enable several campus workflows including

  • Identifying employee locations at both the building and floor levels
  • Visualizing work requests on a map according to total per building, dollar value, and work order system
  • Accessing information about design services projects including project costs via maps
  • Determining emergency phone locations and status of assets

Currently, UNCC is upgrading to ArcGIS 10, which will allow it to easily perform 3D campus-wide routing, including interiors of buildings.

For more information on Esri’s offerings for facilities managers, visit

[Source: Esri press release]

Esri Wins Visual Studio Magazine’s Readers Choice Award

ArcGIS API for Microsoft Silverlight/WPF Tops Mapping/GIS Components Category

Esri received the top honor in the mapping/geographic information system (GIS) components category of Visual Studio Magazine’s Readers Choice Awards. Esri won the award for its ArcGIS API for Microsoft Silverlight/Windows Presentation Foundation (WPF).

The ArcGIS API is designed for developers who want to create Web-based mapping applications quickly and easily with minimal coding. Many governments and businesses use the API because it provides an intuitive framework for creating GIS Web applications, such as data portals and interactive map viewers, and combines multiple technologies into a single development platform.

“I’m pleased to see Visual Studio users finding so much use for the ArcGIS API for Microsoft Silverlight in their daily work,” says Jack Dangermond, Esri president. “GIS is the best tool for organizing geographic knowledge, and this API is a key component for sharing this knowledge and integrating it with everything we do.”

Visual Studio Magazine‘s Readers Choice Awards recognize the most influential and widely used third-party tools in the Visual Studio and Microsoft .NET Framework development space. This year’s contest spanned 29 categories, including new ones for components and in the areas of team development, life cycle management, and data handling.

For more information on ArcGIS API for Microsoft Silverlight, visit

[Source: Esri press release]

Spatial Analysis of Egg Distribution and Geographic Changes in the Spawning Habitat of the Brazilian Sardine

Journal of Fish Biology, published online 23 November 2010

E. S. Gigliotti, D. F. M. Gherardi, E. T. Paes, R. B. Souza, M. Katsuragawa

“This paper establishes the spawning habitat of the Brazilian sardine Sardinella brasiliensis and investigates the spatial variability of egg density and its relation with oceanographic conditions in the shelf of the south-east Brazil Bight (SBB). The spawning habitats of S. brasiliensis have been defined in terms of spatial models of egg density, temperature–salinity plots, quotient (Q) analysis and remote sensing data. Quotient curves (QC) were constructed using the geographic distribution of egg density, temperature and salinity from samples collected during nine survey cruises between 1976 and 1993. The interannual sea surface temperature (SST) variability was determined using principal component analysis on the SST anomalies (SSTA) estimated from remote sensing data over the period between 1985 and 2007. The spatial pattern of egg occurrences in the SBB indicated that the largest concentration occurred between Paranaguá and São Sebastião. Spawning habitat expanded and contracted during the years, fluctuating around Paranaguá. In January 1978 and January 1993, eggs were found nearly everywhere along the inner shelf of the SBB, while in January 1988 and 1991 spawning had contracted to their southernmost position. The SSTA maps for the spawning periods showed that in the case of habitat expansion (1993 only) anomalies over the SBB were zero or slightly negative, whereas for the contraction period anomalies were all positive. Sardinella brasiliensis is capable of exploring suitable spawning sites provided by the entrainment of the colder and less-saline South Atlantic Central Water onto the shelf by means of both coastal wind-driven (to the north-east of the SBB) and meander-induced (to the south-west of the SBB) upwelling.”

Dynamic Analysis of the Wenchuan Earthquake Disaster and Reconstruction with 3-year Remote Sensing Data

International Journal of Digital Earth, Volume 3, Issue 4 December 2010 , pages 355 – 364

Huadong Guo; Liangyun Liu; Liping Lei; Yanhong Wu; Liwei Li; Bing Zhang; Zhengli Zuo; Zhen Li

“Earth observation is an effective technique that plays an important role in earthquake damage reduction and reconstruction. This paper introduces the results of dynamic analysis on monitoring and assessing heavily impacted areas affected by the Wenchuan Earthquake using remote sensing data acquired in the past 3 years from 2008 to 2010. Immediately after the disaster on 12 May 2008, the Chinese Academy of Sciences launched a project entitled ‘Wenchuan Earthquake Disasters Monitoring and Assessment Using Remote Sensing Technology.’ More than 400 images from 17 satellites and 20.2TB airborne remote sensing data were acquired to facilitate quick monitoring and evaluation of severely damaged areas in 14 counties. Results of the image analyses were forwarded on a timely basis to assist with consultative service and decision-making support. In subsequent years, in order to monitor the process of environmental restoration and reconstruction, airborne optical remote sensing images covering most of the severely damaged areas were again acquired in May 2009 and April 2010. These images were analyzed and compared along with images from 2008. Results were useful in support of further work on environmental protection and reconstruction in earthquake-damaged areas. Three typical areas were selected for illustrative purposes including Tangjiashan Barrier Lake, Beichuan County, and counties of Yingxiu and the new Beichuan. These results well demonstrate the importance and effectiveness of the utility of earth observation for disaster mitigation and reconstruction.”

Public Housing and Poverty Concentration in Urban Neighbourhoods: The Case of Hong Kong in the 1990s

Urban Studies, June 2010; vol. 47, 7: pp. 1391-1413., first published on January 12, 2010

Claudio O. Delang and Ho Cheuk Lung

“The undesirable effect of public housing on poverty concentration has been recognised by a series of studies that use census-tract-level aggregate data. This paper examines whether the poverty concentration mechanism of public housing that has been observed elsewhere also functions in Hong Kong. Hong Kong has one of the largest supplies of public housing in the world and also a distinct urban environment. After assessing the poverty rates in Hong Kong in 1991 and 2001, we build a series of regression models to examine the impact of public rental housing on poverty concentration during the 1990s. Using aggregated census tract-level data, the analysis concludes that public housing does not necessarily concentrate poverty in particular census tracts. Public policy and city planning by the Hong Kong government are found to be effective in avoiding or reducing the possible adverse effect of public housing by maintaining social heterogeneity and spatial homogeneity.”