Day: April 23, 2010

New Best Practices e-book: GIS for Non-Governmental Organizations (NGOs)

/ Matt Artz

“GIS technology enables organizations of all sizes in both the public and private sectors to take advantage of their geographic data. GIS is an important tool—one that helps shape the world around us. Nongovernmental organizations (NGOs) have successfully used GIS technology for many years to help the environment and society.

“Conservation: GIS enhances NGOs’ effectiveness with data collection, science-focused modeling, conservation planning, and the creation of maps and visualizations that support various efforts to conserve nature and manage natural resources.

“Sustainable Development: GIS supports many sustainable development efforts throughout the world, providing policy makers and planning agencies with visualization tools to manage growth and change.

“Disaster Response: NGOs actively use GIS to support their response to earthquakes, fl ooding, hurricanes/cyclones, wildfi res, and other disasters.

“Social Programs: GIS technology helps NGOs leverage limited resources and multiply the positive impact of benefi ts to individuals, families, and society.

“We invite you to read the following case studies to learn more about some of the many successes NGOs have had in applying GIS technology to their missions.”

Predicting and Mapping Malaria under Climate Change Scenarios: The Potential Redistribution of Malaria Vectors in Africa

/ Matt Artz

Malaria Journal, 9:111, 23 April 2010

Henri EZ Tonnang, Richard YM Kangalawe, Pius Z Yanda

“Background: Malaria is rampant in Africa and causes untold mortality and morbidity. Vector-borne diseases are climate sensitive and this has raised considerable concern over the implications of climate change on future disease risk. The problem of malaria vectors (Anopheles mosquitoes) shifting from their traditional locations to invade new zones is an important concern. The vision of this study was to exploit the sets of information previously generated by entomologists, e.g. on geographical range of vectors and malaria distribution, to build models that will enable prediction and mapping the potential redistribution of Anopheles mosquitoes in Africa.

“Methods: The development of the modelling tool was carried out through calibration of CLIMEX parameters. The model helped estimate the potential geographical distribution and seasonal abundance of the species in relation to climatic factors. These included temperature, rainfall and relative humidity, which characterized the living environment for Anopheles mosquitoes. The same parameters were used in determining the ecoclimatic index (EI). The EI values were exported to a GIS package for special analysis and proper mapping of the potential future distribution of Anopheles gambiae and Anophles arabiensis within the African continent under three climate change scenarios.

“Results: These results have shown that shifts in these species boundaries southward and eastward of Africa may occur rather than jumps into quite different climatic environments. In the absence of adequate control, these predictions are crucial in understanding the possible future geographical range of the vectors and the disease, which could facilitate planning for various adaptation options.

“Conclusion: Thus, the outputs from this study will be helpful at various levels of decision making, for example, in setting up of an early warning and sustainable strategies for climate change and climate change adaptation for malaria vectors control programmes in Africa. ”

Geographically and Temporally Weighted Regression for Modeling Spatio-Temporal Variation in House Prices

/ Matt Artz

International Journal of Geographical Information Science, Volume 24, Issue 3 March 2010 , pages 383 – 401

Bo Huang; Bo Wu; Michael Barry

“By incorporating temporal effects into the geographically weighted regression (GWR) model, an extended GWR model, geographically and temporally weighted regression (GTWR), has been developed to deal with both spatial and temporal nonstationarity simultaneously in real estate market data. Unlike the standard GWR model, GTWR integrates both temporal and spatial information in the weighting matrices to capture spatial and temporal heterogeneity. The GTWR design embodies a local weighting scheme wherein GWR and temporally weighted regression (TWR) become special cases of GTWR. In order to test its improved performance, GTWR was compared with global ordinary least squares, TWR, and GWR in terms of goodness-of-fit and other statistical measures using a case study of residential housing sales in the city of Calgary, Canada, from 2002 to 2004. The results showed that there were substantial benefits in modeling both spatial and temporal nonstationarity simultaneously. In the test sample, the TWR, GWR, and GTWR models, respectively, reduced absolute errors by 3.5%, 31.5%, and 46.4% relative to a global ordinary least squares model. More impressively, the GTWR model demonstrated a better goodness-of-fit (0.9282) than the TWR model (0.7794) and the GWR model (0.8897). McNamara’s test supported the hypothesis that the improvements made by GTWR over the TWR and GWR models are statistically significant for the sample data.”

A New Approach To Earth Science Data Analysis: NASA Earth Exchange

/ Matt Artz

The way we analyze planet Earth will never be the same, thanks to a new initiative at NASA that integrates supercomputers with global satellite observations and sophisticated models of the Earth system in an online collaborative environment. As part of its celebration of Earth Week, NASA unveiled the NASA Earth Exchange (NEX) at a “Green Earth” public forum held at the NASA Exploration Center, Moffett Field, Calif.

By making NEX available, NASA expects to better enable scientists to collaboratively conduct research and address the impacts of changes in climate and land use patterns on ecosystems. NEX will link NASA’s supercomputing resources with massive Earth system data sets, and provide a collection of tools for analysis and visualization.

“Currently, it can require months for scientists to gather and analyze global-scale data sets, due to computing limitations, data storage requirements and network bandwidth constraints”, said Ramakrishna Nemani, senior research scientist at NASA Ames Research Center, Moffett Field, Calif. “By bringing NASA supercomputer resources to bear on the problem, we can reduce that time to hours, accelerating research on topics ranging from global rates of forest change to the effects of climate change on the reliability of our water resources.”

For example, scientists at NASA have created global high resolution “snapshots” of the Earth’s vegetation from Landsat data over the past 30 years. These snapshots contain quantitative information that is detailed enough to characterize human-scale processes such as urban growth, agricultural irrigation, and deforestation. By comparing vegetation cover and biomass estimates from different time periods, scientists can improve our understanding of where and how the Earth is changing. Using NEX, scientists are now able to create snapshots of global vegetation patterns containing over half a trillion pixels in less than ten hours.

NEX uses a new approach for collaboration among scientists and science teams working to model the Earth system and analyze large Earth observation datasets. Using on-line collaboration technologies, NEX will bring together geographically dispersed multi-disciplinary groups of scientists focused on global change research. Scientists will be able to build custom project environments containing the datasets and software components needed to solve complex Earth science problems. These project environments, built using virtualization technology, will be highly portable and reusable and will automatically capture the entire analysis process, including the data and processing steps required to replicate the results in an open and transparent way. For example, results from the processing of the global Landsat data would be available to scientists with the additional expertise required to analyze rates of urbanization, deforestation, or biodiversity impacts. The science teams would have access to not only the data, but also each processing step used to create the global mosaics.

The NEX uses NASA’s largest, most powerful supercomputer, Pleiades, a 56,832-processor Silicon Graphics International Altix ICE system, Pleiades’ storage system, with an approximately 1.4 petabyte capacity, and the hyperwall-2 visualization system, featuring 128 screens, which measure 23-feet by 10-feet is located at the NASA Advanced Supercomputing (NAS) facility at NASA’s Ames Research Center, Moffett Field, Calif.

“Pleiades now provides an enormous capability for scientists to make new discoveries and gain insight into Earth’s system,” said William Thigpen, high-end computing capability deputy project manager at the NAS.

“Fitting these Landsat tiles together was like working a giant, complicated jigsaw puzzle¬ – it was not a trivial matter,” said Tim Sandstrom, science visualizations expert at the NAS facility. “It required custom algorithms, an extensive amount of memory and a large number of processors, afforded by NASA’s supercomputers.”

NASA’s Earth Science Division in the Science Mission Directorate at NASA headquarters, Washington, D.C., sponsored the NASA Earth Climate Exchange to complement the agency’s efforts to capture global Earth observations from space.

The NAS facility’s supercomputing environment operates under the agency’s High End Computing Capability (HECC) Project, which plans for and provides high-end computing systems and services to support NASA’s mission needs in aeronautics, exploration, science and space operations.

For more information about the NASA Earth Exchange, visit:

http://nex.arc.nasa.gov

For information about the NASA Advanced Supercomputing facility, visit:

http://www.nas.nasa.gov/

[Source: NASA press release]

Research Shows Additional Liquor Outlets Add To Drunken Incidents

/ Matt Artz

As many communities throughout New Zealand continue to protest about the number of liquor outlets opening in their neighbourhood, researchers have for the first time come up with a model that relates the level of alcohol-related harm to the number of liquor outlets.

The research was carried out by the Population Studies Centre (PSC) at Waikato University. It was commissioned and funded by the Alcohol Advisory Council of New Zealand (ALAC), and supported by Manukau City Council.

An initial database of liquor licensees was obtained from Manukau City Council in January 2009. Data for selected indicators of social harm were obtained from the New Zealand Transport Agency (traffic crashes), Counties Manukau District Health Board (accident and emergency event data, and alcohol-related admissions to Middlemore Hospital), and New Zealand Police (police attendances) for the period 1 July 2008 to 30 June 2009.

The model used statistical methods to relate the level of liquor outlet density to a range of events such as police callouts, emergency room admissions, and motor vehicle accidents, while also taking into account the effects of population density and social deprivation. Individual models for each type of event as well as an integrated model of all events were constructed, and the results were similar between the two methods. Data on the events covered the period 1 July 2008 to 30 June 2009, while outlet density was measured based on a survey conducted in January 2009.

Several key results were found relating to the characteristics of alcohol sales in Manukau City. First, on-licence outlets (bars, clubs, restaurants and cafes) were most dense in areas with good transport links, such as town centres, and in areas with high amenity value. This is because these outlets cater to consumers who are looking for a destination at which to drink, or where drinking is incidental to some other activity such as eating a meal.

Second, off-licence outlets (alcohol retailers, supermarkets and bottle stores) tended to locate in areas of high social deprivation and high population density. Higher off-licence density was in turn associated with lower alcohol prices and longer opening hours.

The researchers found that in Manukau the addition of a single extra off-licence was associated with an extra 60 to 65 police events or incidents in the year to June 2009. Each additional club or bar was associated with an extra 98 to 101 police events or incidents, while each additional restaurant or café was associated with an extra 24 to 29 police events or incidents.

ALAC Chief Executive Officer Gerard Vaughan said in order for local body planning to effectively address ways to minimise alcohol-related harm, information about the impact of liquor outlets on local areas was needed. “We have now for the first time a New Zealand model that can be used by local authorities to show the impacts of extra liquor outlets.”

Mr Vaughan said the Law Commission was due to release its recommendations to Government on reforming New Zealand’s alcohol laws next week. “Options being considered by the Commission to recommend to Government include widening the grounds for refusing liquor licences to include things like outlet density.

“If the law is changed to allow density to be raised as grounds for refusing a liquor licence, evidence will still need to be produced of the harms that might result. This model provides the important evidence base for decisions on licensing at a local level.”

Waikato research associate Dr Michael Cameron said although the Manukau results were specific to that area, the model that had been developed could be used in other areas to determine what impact extra liquor outlets would have on a district.

The research showed higher liquor outlet density of both on and off-licences was associated with higher numbers of total police events.

In particular, off-licence density was associated with higher levels of anti-social behaviour, drug and alcohol offences, family violence, property abuse, property damage, traffic offences and motor vehicle accidents.

Density of clubs and bars was associated with higher levels of anti-social behaviour, dishonesty offences, drug and alcohol offences, property abuse, property damage, sexual offences, traffic offences, and violent offences.

Density of restaurants and cafes was associated with higher levels of dishonesty offences, property abuse, traffic offences, and motor vehicle accidents.

Total police events were based on all police attendances recorded in the New Zealand Police database from 1 July 2008 to 30 June 2009. (A police attendance may not necessarily lead to anyone being charged with an offence.)

Manukau City Council Senior Policy analyst Paul Wilson said the research supported what the community had been telling the council and could be used to inform the new Auckland Council on how alcohol-related harm could be addressed.

For more information or comment please contact ALAC CEO Senior Communications Advisor Lynne Walsh on 021 369 081 or ALAC CEO Gerard Vaughan on 021 549 848; Waikato research associate Dr Michael Cameron on 07 8585082; Manukau City Council Communications Advisor Sharleen Pihema on 09 262 8900 ext 8650.

Questions and Answers

Why was the research commissioned?
There has been significant recent debate over the impact of liquor outlets on communities in New Zealand. This has arisen in part because of the liberalisation of the sale of alcohol following the Sale of Liquor Act 1989, which allowed the sale of wine in supermarkets and grocery outlets and led to a substantial increase in the number of outlets supplying alcohol.

In February 2008, there were 494 active liquor licences in Manukau City – compared with just 148 in 1990. Substantial increases in the number of both on- and off-licence liquor outlets have been matched with an escalation in the level of community unease about alcohol-related harm. Of particular concern are the more vulnerable communities of Manukau City, in which the high density of liquor outlets relative to other parts of the city is a notable feature.

If residents are opposed to an extra liquor outlet, why do they not appeal to the Liquor Licensing Authority?
Under the 1989 Sale of Liquor Act the grounds for opposing an extra liquor outlet are limited. Significant issues such as social impact and the number of outlets in an area are not grounds for refusing an application. However, the Law Commission is currently carrying out a review of New Zealand’s liquor laws and in an issues paper discussing options round licensing applications, the Commission has put forward options including allowing licences to be refused on grounds such as outlet density, The options being considered are:

  • No change
  • Change the law to allow the licensing decision-maker to refuse licences on wider grounds than at present, for example, on grounds that:
    • the overall social impact of the licence is likely to be detrimental to the well-being of the local or broader community, taking into account matters such as the site of the proposed premises, the density and type of other premises in the area, and the health and social characteristics of the local population;
    • granting the licence would be inconsistent with the object of the Act;
    • the amenity, quiet or good order of the locality would be lessened by the granting of the licence.
    • the licence would be inconsistent with the relevant local alcohol policy.
  • Allow the licensing decision-maker to impose any licence condition it considers appropriate for the purpose of reducing alcohol-related harm.
  • Widen the category of persons who can object to a licence application.
  • Specifically authorise medical officers of health to report on all types of licences and licence renewals.
  • Better define and strengthen the criteria for suitability of licence applicants.
  • Improve the effectiveness and efficiency of the process for notifying the public of licence applications.

When will decisions on the Law Commission’s review of New Zealand’s liquor laws be made public?
The Law Commission is expected to report back to Government next week.

How did you develop the model?
The model takes a snapshot of information related to liquor outlets and measures of social harm for the Manukau region for the period 1 July 2008 to 30 June 2009. The model is not concerned with comparisons with earlier time periods.

The model uses regression analysis, a technique used to understand how a variable changes (such as total police events; these are often called the outcome variables or dependent variables) when another variable changes (such as the number of liquor outlets; these are often called explanatory variables). The technique describes how the variables are associated (i.e. an increase of X liquor outlets is associated with an increase of Y total police events) but it does not necessarily imply causality.

In this study there were a number of outcome variables examined including the total number of police events, A&E admissions and hospital discharges and more specific measures relating to anti-social behaviour, dishonesty related offences, drug and alcohol related offences, family violence, property abuse, property damage, traffic offending and motor vehicle accidents, sexual offending and violent offending. Liquor outlets were the explanatory variable involved and they were divided into off-licence premises, and two categories of on-licence premises (clubs/bars and restaurants/cafes).

Regression techniques take into account the effect of other variables that could impact on the dependent variable (such as total police events) by accounting for or controlling for their effects, such as keeping the effect of other explanatory and control variables fixed. Spatial regression techniques are used when the variables of interest are spatial such as based on or affected by geography (for example all variables in this study were based on rates involving census area units) and where nearby spatial areas (in this case census area units) may influence each other and the variables of interest. Different spatial analysis techniques were used to deal with different types of spatial dependence when they were found to exist in the analyses. A number of different variants of the model were also tried to check how different model assumptions influenced the findings.

Can this model be applied to other areas?
The modeling approach employed can be used in any area where appropriate data are available.

Would it produce the same results in other areas?
The quantitative results would be different as our research has shown that the links between outlet density and alcohol-related harms are highly context-specific. However, it is likely that similar results would be obtained in some areas.

How accurate is the model?
The model is robust to a number of alternative specifications. In other words, if we try the model different ways, we get results that are broadly similar.

Does it produce a direct causal link?
Models of this nature are unable to definitively prove causality. This is not unusual – to determine causality we would need to conduct a controlled experiment. However, we can say that the observed associations between the variables are strong, statistically robust, and consistent with theory.

What other New Zealand literature is there on outlet density?
The New Zealand literature on the impacts of liquor outlets is limited, but has grown recently. Kypri et al. (2008) found a significant positive relationship between outlet density and drinks per typical drinking day among tertiary students at six university campuses, as well as a measure of alcohol-related problems. No significant differences in the effects were noted between Maori and New Zealand Europeans, but the effects were larger for off-licence outlets. Huckle et al. (2008) found a significant positive effect of outlet density on how much was consumed on a typical drinking occasion among Aucklanders aged 12-17 years, but no significant effect on either the frequency of drinking or frequency of intoxication.

A copy of the research is available at www.alac.org.nz

[Alcohol Advisory Council of New Zealand press release]

Modelling Habitat Selection at Multiple Scales with Multivariate Geostatistics: An Application to Seabirds in Open Sea

/ Matt Artz

Oikos, Published Online 13 Apr 2010

Edwige Bellier, Grégoire Certain, Benjamin Planque, Pascal Monestiez, and Vincent Bretagnolle

“Modelling habitat of species necessitates robust identification of relevant environmental variables linked to species distribution. To achieve this, we connect hierarchical patch theory and habitat modelling at multiple scales. We suggest discriminating between ‘circumstancial variables’ and ‘process variables’ on the basis of temporal evolution of the spatial links between species distribution and their environment at different scales. ‘Process variables’ are informative of the ecological processes driving the distribution of organisms at multiple scales. By opposition, ‘circumstantial variable’ provide little insight because their relationship with animal spatial distribution is subject to great variations through time. As a real case study, we investigate the relationships between auk distribution (mainly Uria aalge) and oceanographic landscapes over two scales (i.e. large ∼ 200 km and medium ∼ 50 km) during the wintering season in the Bay of Biscay. Surface salinity, mixed layer depth and chlorophyll a are identified as ‘process variables’ as they are invariably correlated with the spatial distribution of auks, whereas bottom temperature can be viewed as a ‘circumstantial variable’ since the correlation is non-constant through time at large scale. The process variables at large scale are used to model the potential habitat of auks in the Bay of Biscay during the wintering season. At medium scale, only the chlorophyll a is identified as ‘process variable’ and used to model preferential habitat of wintering auks in the Bay of Biscay. The analytical approach proposed here (i.e. multivariate factorial kriging in a temporal context) is an effective framework to model the potential and preferential habitat of a species and can be related to the ecological niche concept and by focusing explicitly on scale dependence, the distinction between the variables that can be used as niche descriptors into species distribution models. Then our method lead to the identification of variables that should be used to define the Grinnellian niche which is defined by environmental conditions on broad scales and the Eltonian niche which focuses on biotic interactions and resource–consumer dynamics that can be measured principally at local scales.”

GIS Aids Dry Cleaner Water Resources Risk Analysis

/ Matt Artz

EPA Department of Toxic Substance Control Uses Geospatial Analysis to Target Site Remediation

Environmental Observer, Spring 2010

“Need to get that stain out of your favorite business suit? Surely the local dry cleaner shop can remove it. For years, dry cleaners have used perchloroethylene (perc) to efficiently remove spots from garments. But what is good for your clothes is not good for your health, because perc is a carcinogen.  The residue produced in dry cleaning processes is classified as hazardous waste that contaminates soil and gets into the drinking water. In California, the Environmental Protection Agency’s (EPA) Department of Toxic Substance Control (DTSC) has been using ESRI’s geographic information system (GIS) technology to locate and prioritize community sites that have been contaminated by dry cleaning chemicals and need remediation.”