City of San Diego Analyzes Trends in Ocean Data with Dynamic GIS Tools

2011 Esri CA/HI/NV Regional User Group Proceedings

Dawn Olson and Jodi Luostarinen

“The City of San Diego Public Utilities Department’s Environmental Monitoring and Technical Services (EMTS) Division is responsible for ensuring compliance with California Ocean Plan water-contact standards, detecting movement and dispersion of the wastewater field, and identifying any changes to marine communities, water quality, or sediment conditions that may be associated with wastewater discharge.

“The City has enlisted the help of Esri business partner Quartic Solutions LLC to develop a web based GIS application which greatly increases staff access to ocean monitoring data. The Web application, called ‘BioMap’, has analytical tools which will enable staff to synthesize and explore large volumes of data dynamically, in ways not possible in the past. The BioMap GIS application is served by Esri’s ArcGIS Server product and was built in Adobe Flex using Esri’s API to deliver a fast, flashy, functional, and intuitive user interface. Several of Esri’s free ArcGIS Online web services are utilized for the basemap, and PHP is used as the connector to access the Oracle database holding the City’s ocean monitoring data.

“BioMap’s main strength is its ability to simplify complicated spatial processing for users not trained in GIS. It also makes touch-of-a-button, rapid feedback data exploration possible. It will reduce the time scientists currently spend performing data manipulation tasks, and it allows statistical comparisons on large, interactively selected datasets. It can also quickly show users the spatial relationships and temporal trends in tabular data by highlighting selected data points within a map. So it should come as no surprise that we fully expect BioMap to revolutionize the analysis and presentation of ocean monitoring data in San Diego.”

Planning Los Angeles’s Nonpotable Water Use Future

2011 Esri CA/HI/NV Regional User Group Proceedings

Dawn Flores

“The City of Los Angeles has a goal to use recycled water to the fullest extent. One way that the City is attempting to meet this goal is by using recycled water for non-potable uses such as landscape irrigation, in cooling towers, and at commercial laundries. GIS has played a critical role in planning how non-potable water will be used. Mapping of existing recycled water pipelines and potential users has aided in discussions with City departments and with stakeholders. Spatial analyst has been used to show areas of high demand density, and target these areas for more efficient planning of recycled water pipelines and connections. Pipeline shapefiles have been used directly by hydraulic modelers to obtain system specifications for the new recycled water system. The end result of the GIS analysis has provided a base that has been used to focus the City’s Non-Potable Reuse Master Plan.”

Healthy City: Geographic Analysis to Stop the Schoolhouse to Jailhouse Track

2011 Esri CA/HI/NV Regional User Group Proceedings

Chris Ringewald

“The Los Angeles Police Department recently released five years of truancy ticket data and the Labor/Community Strategy Center and Advancement Project (LCSC/AP) wondered if patterns existed in ticket distribution, specifically whether tickets were disproportionately given to minority students in low-income communities.

“Together, as a part of a joint ‘Stop the Schoolhouse to Jailhouse Track’ initiative, LCSC/AP decided to analyze the data in a GIS because it would enable them to access spatial statistics and create impactful visuals to present to policymakers. Using ArcGIS 10, the team geocoded, analyzed, and mapped the 35,000+ truancy tickets, creating point, choropleth, and dot density maps, and using the point density tool in the Spatial Analysis toolbar.

“The analysis and maps reveal an uneven distribution of truancy tickets citywide, and clusters of tickets in low-income, minority communities, often within a short distance from school campuses. This project is instructive for other point-location analyses of inequality. ”

Spatio-Temporal Analysis of Malaria in Paraguay

Master’s Thesis, University of Nebraska, May 2011

Nicole Wayant

“Malaria is a mosquito-borne disease that has afflicted humans for thousands of years.  Today it is considered a re-emerging disease.  Malaria is most prevalent in tropical and subtropical parts of the world.  The disease has been linked to several environmental parameters, including precipitation, temperature, and deforestation.  However, these relationships have mainly been studied in Africa and have not been explored in other parts of the world.  The study area for this thesis was the South American country of Paraguay.

“Paraguay has experienced an oscillation in malaria cases over the past 20 years, with monthly cases ranging from 0 to 1200.  Additionally, the country has experienced vast amounts of deforestation and climate variations.  The thesis study area was two Paraguayan departments, Alto Parana and Canindeyú.  Both departments had a record of monthly malaria cases for the years of 1981-2003.

“It was discovered that there was a positive correlation between malaria and temperature and vegetation strength and a negative correlation between precipitation and malaria.  Spatial comparisons of deforestation maps and maps of malaria risk based on the selected environmental parameters, suggests recent deforestation increases the probably of malaria occurrence.  Additionally, time series analysis provides evidence that an increase in temperature increases malaria cases every 2-3 years.  The annual oscillation of temperature, precipitation, and vegetation change from the wet and dry seasons corresponds with the low and high activity time periods for malaria case rates.”

Industrial Diversity and Economic Performance: A Spatial Analysis

Doctoral Dissertation, University of Nebraska, May 2011

Hoa Phu D. Tran

“This study examines the linkage between industrial diversity and economic growth in the 48 contiguous states of the United States.  The period of analysis is 1992 through 2009.  Five diversity indices are considered and economic growth is measured as the growth rate of nonfarm earnings.  Other variables thought to influence economic growth are included in the analysis.  They are the growth rate of nonfarm employment, capital, and farm earnings.  Tests for the endogeneity of variables are conducted and the need for instrumental variable estimation methods is demonstrated.

“First, I consider multivariate model that relates nonfarm earnings growth to the diversity indices and the other variables noted above.  The model includes regional fixed effects and time effects but does not allow for spatial dependence among states.  The results show that diversity positively influences economic growth.  Growth in nonfarm employment and capital are also found to be positively influence economic growth.

“Second, I consider two spatial models that allow for a spatial lag and spatial autocorrelation effects among states.  The first spatial model assumes a common spatial lag parameter for all states.  The second spatial model allows the spatial lag parameter to be unique for each of eight regions within the United States.  Two estimation methods are used, the generalized spatial two-state least squares estimator and an instrumental variables estimator along with a spatial heteroskedasticity and autocorrelation consistent matrix estimator.

The spatial lag parameter is small and statistically insignificant when the parameter is assumed to be the same across regions.  However, when the spatial lag parameter is allowed to vary across regions, spatial effects among states are detected and are reasonably strong in some regions.  Under both estimation methods for both spatial models, the results provide strong evidence that states with higher levels of diversity experience higher growth rates in nonfarm earnings.  Nonfarm employment growth and capital growth are also significant influences upon the growth rate of nonfarm earnings.”