The four California URISA Chapters, along with the California Geographic Information Association (CGIA), are pleased to present the 19th Annual CalGIS Conference taking place April 15-17, 2013 in Long Beach. The deadline for abstract submissions (and also for registration at the super-early discounted rate) is November 1.
The CalGIS 2013 Conference Committee welcomes the submission of individual papers, complete sessions, luncheon presentations, panels, posters and lightning talks within these overall program tracks/themes (note that all abstracts received will be reviewed and considered for the conference program regardless of the list below):
- Geospatial Technologies – This track will focus on GIS technology and innovations. Topics in this track could include: software, web mapping, programming, automation, databases, tools, customization and similar technologies.
- Ports, Transportation and Logistics – This track encompasses presentations with a nod to topics of local (and statewide) interest. The Port of Long Beach is a major player in the area as well as highway, rail and air hubs. Security and risk assessment topics are also welcome.
- Education/Certification/Training/Mentoring – This track includes presentations focused on GIS education and skills development. Topics could include GIS education in K-12 and Higher Education environments as well as professional education and certification (e.g. GISCI – GISP, Esri Certification, ASPRS Certification as examples of professional development). Other topics may include job skills (DOL Competency Model) and industry/agency needs and training for both students and continuing professionals.
- Water Resources/Marine – Consider this track for presentations focused on statewide and local water issues in both freshwater and marine environments. With Southern California being both a major importer of water as well as having a major coastal/marine connection, this track should have particular significance and relevance for attendees.
- Government/ Non-Profit – This track will focus on examples and applications of the use of GIS in Government and non-profit sectors. Sub-tracks focusing on public safety, public health, community planning, etc. will be of particular interest.
Melisa Caric Lee, GISP, President of Compass Rose GIS and 2013 Conference Chair, noted, “CalGIS always offers an exciting mix of technical workshops, presentations, and networking opportunities. GIS professionals at all levels are invited to share ideas and solve problems together. CalGIS is the place to create life-long partnerships and friendships alike! Please join us at the 19th Annual California GIS Conference in beautiful Long Beach, CA. We hope to see you there!”
For information about CalGIS, early registration opportunities and presentation proposals, visit www.calgis.org. The conference will feature training courses and workshops, breakout sessions, keynote addresses, exhibits and networking events. Specific program details will be available in early 2013.
[Source: URISA press release]
Holy Cross Energy Saves Money, Improves Customer Service with Street and Security Light Project
Holy Cross Energy, a member-owned electric cooperative utility that serves more than 55,000 consumers in western Colorado, recently used Esri technology for a street and security light project that has helped update and correct its billing system.
“We have saved $442 per month for one of the towns we serve, as they were paying for devices that no longer existed and were paying for higher wattage bulbs than they should have been,” said Holy Cross Energy meter supervisor Tonya Warmenhoven. “An association in our service area, on the other hand, had been getting free street lighting and the address marker power for at least 10 years. They are now billed $600 per month for 178 new devices we have added.”
The utility’s security and streetlight project involved digitally mapping security lights and streetlights within its service area using GPS, aerial photographs, and a custom web mapping application powered by Esri’s ArcGIS technology.
Holy Cross Energy can now provide correct information to its consumers and its billing department. Service and billing personnel now have precise data about devices in the field. In the past, field crews would have had to call the billing department to get information about street and security lights. Now they have access to that data via laptops in the line trucks.
Read more about how Holy Cross Energy implemented its street and security light project.
[Source: Esri press release]
Paul Doherty, Qinghua Guo, Wenkai Li, Otto Alvarez, and Jared Doke
“The application of GISystems to solve real-world problems continues to expand from reactive, where we simply document and visualize where and when a phenomenon happened, to proactive, where we are able to reliably forecast event locations based on what we have learned from previous events. During this process we often test GIScience theories and techniques, leading to new scientific discovery. This is especially true in the field of spatial epidemiology, which merges spatial analysis with studies from public health (Ostfeld et al. 2005, Robertson et al. 2010). The objectives of such studies are to collect information about spatially varying factors that may contribute to the occurrence of disease, illness or injury.
Yosemite National Park with the overall PBL probability for search and rescue occurrence based on 2001 – 2009 incident data. Red indicates areas with the highest likelihood for incident occurrence based on conditional probability. Trailheads (access points) are shown as white dots.
“Within spatial epidemiology, datasets often consist of incident coordinates or other locality descriptions that need to be georeferenced. Furthermore, most data describe locations where illness or injuries have previously occurred (presence) but not where they have not occurred (absence). Therefore, analyses have often been limited to descriptive analyses (density or “heat maps”) and spatial statistics (hot spot or Getis Ord G* maps; Getis and Ord 1992) because traditional modeling approaches requires presence and absence data to derive relationships from underlying factors (Hirzel et al. 2002). This limitation is known as the geographic one-class data issue (GOCD; Guo et al. 2011) and requires a specialized approach to generate probability maps.
“Here we study a real-world problem: wilderness or wildland search and rescue (WiSAR) incident prevention in Yosemite National Park using a novel GIScience technique. WiSAR is the process of locating, accessing, stabilizing, and transporting people in remote environments (Worsing 1993). Therefore, our objectives are to describe our methodology, present our results, and discuss the preliminary implications of our findings for WiSAR incident prevention, spatial epidemiology, and GIScience. To do so we used a novel machine learning approach based on GOCD (incident occurrence) to forecast areas of probable occurrence in the future.”
Computers & Geosciences, Volume 42, May 2012, Pages 64-70
Igor Rychkov, James Brasington, and Damià Vericat
- We present a software toolkit for processing terrestrial point clouds.
- The toolkit can be applied to TLS surveys of gravel river beds.
- Improved DEM differencing is one outcome.
- Estimating surface roughness and grain size distribution is possible now with point-based, statistical metrics.
- Other applications and extensions are enabled by the library being freely available and open source.
“Processing of high-resolution terrestrial laser scanning (TLS) point clouds presents methodological and computational challenges before a geomorphological analysis can be carried out. We present a software library that effectively deals with billions of points and implements a simple methodology to study the surface profile and roughness. Adequate performance and scalability were achieved through the use of 64-bit memory mapped files, regular 2D grid sorting, and parallel processing. The plethora of the spatial scales found in a TLS dataset were grouped into the “ground” model at the grid scale and per cell, sub-grid surface roughness. We used centroid-thinning to build a piecewise linear ground model, and studied “detrended” standard deviation of relative elevations as a measure of surface roughness. Two applications to the point clouds from gravel river bed surveys are described. Linking empirically the standard deviation to the grain size allowed us to retrieve morphological and sedimentological models of channel topology evolution and movement of the gravel with richer quantitative results and deeper insights than the previous survey techniques.”