Using new methods to control the spread of invasive species

In ecosystems where many species do not thrive, the implementation and control of invasive species to help bolster the ecosystem is a controversial topic.  While these plants often help to regulate and increase the overall health of the ecosystem, over time they can choke out other species due to the fact that they are able to thrive in their new environment.

This is exactly what happened in south Texas in riparian ecosystems with the saltcedar.  Until recently, the data collection methods used to survey and ultimately control the saltcedar population in the Rio Grande basin in Texas were not stopping the spread of the cedars and the destruction of the ecosystem.

Coarse-resolution remote sensing data had been used to determine where exactly the saltcedar was located.  However, this did not allow for differentiation between it and other riparian plants, and in the process of eradicating the cedar many other species were also damaged.  Now, they are using higher resolution remote sensing which allows the surveyors to be much more specific in their identification and eradication.

Thanks to GIS this ecosystem will become healthier, and much more likely to return to its original state because the native plants will be able to thrive.  This is one of the many ways that GIS is able to help ecologists and conservation biologists to do their jobs more effectively.

Challenging the Implications of a Food Desert

Food deserts have become a hot topic in recent years when discussing sustainability, food cultures, and class. A food deserts are areas in developed nations which are in a relative area of exclusion when it comes to physical and economic barriers to access healthy foods such as vegetables, fruits, and cereals which are needed to form a healthy diet. This study focuses on one food desert in the United States, Lawrence, Kansas and maps, surveys, and studied Lawrence's relationship with food resources. Lawrence is a very small city, so the analytical methods used were tested throughly. Stores such as gas stations and food outlets which do not offer food with a significant nutritional value are indeed in many of these areas, but they are not what is needed to form a healthy and livable lifestyle.

One other factor which was taken into consideration during this study was the mode of transportation for the families that live in these food deserts to get to a healthy food source. They divided people up into four groups, people who walked, people who took public transportation, people who carpooled, and people who drove themselves. Along with these groups came other factors, if one walked, there was only so many bags they could carry, if one took the bus, the amount of bags in which they carried was limited, if you carpooled, you were limited by the amount of time the person who drove you had, and if you drove yourself, you had to pay for gas, meaning less money to pay for food.

Aside from transportation to actually acquire the food, one must consider the food miles (farm to consumer miles) that are attached to goods within a food desert. Consequentially, the transportation of the good to the food desert consumer, usually decreases the quality of the good just because it takes exponentially longer to get to the store. Within the food system, the food miles attached to different goods effects and manipulates both costs and nutritional value of the food. To accurately determine the cost variation “a cost model was created to calculate the cost variation between the distance from the stores, the mode of transportation, and income” (1212).

Much like physical deserts, food deserts do not have definite lines. However, what does make up the dividing line is food outlets, individual dietary preferences, and the transportation means available for the consumer. The cost model above, can be applied to inner city neighborhoods, segregated communities, and other rural areas, much like the city of Lawrence. 

Works Cited

Lucious F. Hallett IV, D. M. (2010). Quantifying the Extent and Cost of Food Deserts in Lawrence, Kansas, USA. Applied Geography, 1210-1215

Using GIS to Identify Locations for Outreach

Socha, Y. M., Oelschlegel, S., Vaughn, C. J., & Earl, M. (2012). Improving an outreach service by analyzing the relationship of health information disparities to socioeconomic indicators using geographic information systems.  J Med Lib Assoc, 100 (3), 222-225.

Disparity in income and other resources has long been known to have an effect on the assistance, as well as knowledge of potential assistance sources, for different communities.  Many organizations attempting to educate and provide services to communities have struggled with outreach campaigns due to the difficulty in pinpointing specific regions of the communities they serve that require the most attention to make such campaigns successful in their goals.

One such organization, the Preston Medical Library in Preston, Tennessee, provides a free over-the-telephone service called the Consumer and Patient Health Information Service (CAPHIS).  Community members can call CAPHIS with questions regarding health information and the staff will respond over the phone and with information packets sent in the mail. Unfortunately, some of the regions of the community most in need of the free service often were unaware of its existence. 

In order to yield a more successful outreach campaign to account for some of this disparity, Library staff combined location data from calls to CAPHIS (zip codes) and county data from the U.S. Census regarding race, age, disease, and socio-economic levels in the ArcMap program.   This allowed staff members to identify regions of the county that had a higher rate of disease or a larger number of elderly or low-income individuals and yet from which there was little to no record of calls to CAPHIS.  The spatial analysis created in ArcMap with the combined data provided Library staff the information needed to improve their outreach campaigns in a very clear manner that was easy to understand, highlighting one of the many potential uses of GIS programs in community development/service organizations.   

GIS in Hydrology and Water Management

These are four possible applications of a GIS-hydrological model relationship:

1) Hydrological assessment to represent hazard/vulnerability through weighted/summed influences of significant factors rather than through physical laws

2) Hydrological parameter determination as the GIS provides input to the model in terms of parameters such as surface slope/channel length/land use/soil characteristics

3) Hydrological modeling within the GIS, which some say is feasible with time snapshots/temporal averages and not time-series

4) Linking GIS and hydrological models to utilize the GIS as an input/display device, including real-time process monitoring if the necessary [remotely sensed?] observations are available.  The primary challenge here is the disparity between GIS and hydrological data models.

Whereas scientific GIS was developed in a modeling context, commercial water utilities first used GIS as a core integrating technology which led to failed expectations.  The database is now the center of corporate information handling, with network computing capability expected to replace the database’s central role in the future. 

In water utilities 70-80% of all corporate information is geographic, but there are several problems with increasing data resolution:

1) Necessitated increase in storage/processing speed – technological advances tend to annul this

2) Pixelated raster models tend to speckle at high resolution.  This requires zooming out or smoothing, which remove the benefits of higher resolution.  If resolution increases to a magnitude where zooming in does not create speckling, this issue would be solved (in theory).  Is this feasible?

3) Many features represented are physically “fuzzy” or temporally time-bound transitions

4) Higher resolution may create specificity that decreases unknowns/errors in estimating risk probability which, due to professional implications, may render it a net detriment

High Resolution in GIS & Flood Insurance:

-Higher resolution allows underwriter to remove extreme high risk individuals, depending on the location this could be a benefit or loss for the underwriter depending on whether the high risk individuals capitalized in the past or whether future-oriented process models are more suited, the % of the customer base for the firms is important here

-raises premium for high risk individuals to the point that they can’t afford insurance, this % is important

            -social justice concerns arise here

-low risk individuals opt out of insurance, how many % would this be?

-based on these prior numbers the company may or may not be able to lower mid-range premiums to bring in a potentially wider customer base and continue operating

-depending on the % individuals lost on the high-risk end [a benefit for the company] and the % individuals lost on the low-risk end [a loss for the company], the firm may or may not be able to continue operating

-this situation is significant because GIS models are often off by as much as 3.75 m in estimating risk and insurance is a pivotal component of national/international infrastructure through which advanced societies manage/mitigate risk

-a discussion concerning the role of how corporate structure is related to technological innovation [e.g. is large-scale information analysis predicated upon a corporate structure, or can business change this? – or at least I’d like more information on this], modeling, natural systems change that can’t be predicted based on past experience, the use of technology to stop technology is all warranted here

Clark, M. J. (1998). Putting water in its place: a perspective on GIS in hydrology and water management. Hydrological Processes, 12, 823-834.

Retrieved from https://lms.southwestern.edu/file.php/3722/Literature/Clark-1998-Putting_Water.pdf

Current Knowledge Production and the Effect on Geographical Learning

Schuurman, N. (2012). Tweet me your talk: Geographical learning and knowledge production 2.0. The Professional Geographer, doi: 10.1080/00330124.2012.693873

Link:  http://dx.doi.org/10.1080/00330124.2012.693873

An important characteristic about the human brain is it's flexibility, or brain plasticity. The human brain is capable of restructuring and rewiring itself as a response to exposure and usage of knowledge and experiences. For example, brain scans of taxi drivers displayed larger hippocampi than control subjects, presumably due to their significant increase in spatial knowledge. 

Today, people in developed countries spend an enormous amount of time browsing the Internet for answers. Most of the time, people spend only 19-21 seconds on a Webpage before moving to the next one. In academia, students and professors research with Google and online journal databases more often than with hard copy books and journals.

Online journal databases are responding to the new style of researching information. As seen below, databases such as the Journal of Health Geographics have created Web formats that encourage users to view articles under labels such as most viewed or most forwarded. While this may allow researchers to find articles quickly and effectively, it also establishes a form of collectivism and discards other articles that may be sufficient. 

While we have successfully rewired our brains to excel at activities such as skimming or searching for keywords, we have consequently lost the ability to concentrate, to focus, and to fully absorb knowledge and information.We prefer PowerPoint to lectures, and would rather browse the Internet for hours than pick up a good book. 

Although these methods are useful for deciphering the growing amount of information we have access to, we have to acknowledge the price that is paid and consider, how much does our brain need to change?

Privatized Water and Spatial Variegations

Bakker, Karen (2013). Neoliberal Versus Postneoliberal Water: Geographies of Privatization and Resistance, Annals of the Associaton of the American Geographers. 103(2), 253-260. 
http://web.ebscohost.com/ehost/detail?vid=3&sid=7934ae76-dd21-4bd9-b42d-766d78a90bb3%40sessionmgr104&hid=108&bdata=JmxvZ2luLmFzcCZzaXRlPWVob3N0LWxpdmUmc2NvcGU9c2l0ZQ%3d%3d#db=a9h&AN=85797429

Water is understood by the United Nations to be a basic human right. Still, much of the world's population lacks access to potable water supplies. In some places, the public sector supplies this utility at subsidized costs to citizens. However, in many developing states, there are inadequate and/or corrupted public funds which inhibit the supply of potable water to all citizens. Kathryn Bakker draws on numerous sources from World Bank data to a wide array of published authors to describe the process of water privatization since the 1980s. 

Private management of water supply was rare in the 1980s, but by the  1990s it was increasingly popular and concentrated in cities. In developing countries, the rise of privatized water coincided with conditional lending policies set forth by the bilateral lending agencies and multilateral development banks, such as the World Bank.

 Privatization proponets justified their work by parading the need to provide water to the poor. Specifically, a common trend was the tendancy for upper and middle class neighborhoods to receive public water supplies at a lower cost and greater supply than lower class neighborhoods. Private suppliers were championed to fill the gap of this systematic exclusion. 

In time, it became apparent that the actual execution of privatized water reinforced the resource gap. A key point to this reality was that companies faced a majority low income population which lacked the ability to pay for the water. Additionally, political risks assosiated with privatizing water deterred many private investors. 

Finally, in 2005 the World Bank admitted it was adventagous for the majority of the world's water supply to remain publicly, rather than privately, owned. At the same time, the number of private water companies and their customers increased world wide. 

Spatial maps of these trends confirm that private water companies are concentrated in middle to upper income urban neighborhoods, while being vacant or scarecly represented in the areas that need water most, such as Sub-Saharran Africa. Bakker asserts this spatial variegation leads to cherry picking specialized water markets an an intensification or mutation of neoliberalism. 

GIS and Resource Accessibility-New Zealand

Source:

Jamie Pearce, Karen Witten, Phil Bartie 
J Epidemiol Community Health 2006;60:389–395. doi: 10.1136/jech.2005.043281 

Access to amenities in neighborhoods is always a factor when looking for a place to live. That access is shown to correlate with the health of it's occupants as a community. This article explains how how the different material amenities and the access to these amenities  are linked to the health of a community. Using GIS, the distance to different shopping, education, health and recreational facilities is measured from the population weighted center of a neighborhood. An example in this article claims that in New Zealand, the average travel time to he nearest food supplier ranged from ~1 minute to more than 244 minutes.

You'll notice the lighter spots of the map are extremely prevelant and widespread in the Southern part of New Zealand, rather than clustered in small areas. This type of GIS methodology can help countless disadvantaged members of neighborhoods and help with zone planning of future shopping centers. GIS was also used to look at the road networks that these disadvantaged populations were taking to get to the suppliers.

Historic Churches in Georgetown, TX

GTography map of Coffee Shops

GIS in the Classroom

        The importance of being able to work with and utilize geographic information is become increasing important in today's society. Some high schools are starting to offer GIS courses and Norwegian legislation has recently mandated two hours a week for upper secondary students (those from 16 to 19). Norwegian geographers have compiled a comparison of available programs and suggestions on how best to incorporate GIS into the classroom.

Map allowing students to explore volcanoes and fault lines

        The authors emphasized the importance of learning with GIS technology not about the technology. By learning with GIS students will look beyond technical aspects of program components in order to apply their new knowledge of spatial data and GIS to real situations in their community. The integration of GIS to current curriculum not only enhances students understanding of geography but also allows subjects such as statistics and natural sciences to be further explored and understood. The ability for statistics to be visualized in maps as well as understood in tables and charts is a vital skill for students to master, which GIS programs can help to achieve. Since students focus on the basics of GIS rather than technical aspects, simpler web applications and data viewers allow students to benefit from the interaction and manipulation of data without having high costs of more complicated commercial software.
           While the authors found that similar aims to implement GIS into classrooms in other nations met with resistance, in Norway teachers were found to be open and willing, as well as already having experience with using various GIS programs. The availability of inexpensive and often free web applications and data viewers leaves no cost prohibition to schools and extensive textbooks, lesson plans and other resources for teachers help transition the use into the classroom. Norway has the available resources to blaze the trail of a fully integrated GIS curriculum in secondary schools and produce students proficient in understanding the importance of spatial data and geography.

Work Cited:

          Rød, Jan Ketil, Wenche Larsen, and Einar Nilsen. "Learning geography with GIS: Integrating GIS into upper secondary school geography curricula." Norwegian Journal Of Geography 64, no. 1 (March 2010): 21-35. Academic Search Complete, EBSCOhost (accessed March 20, 2013).