Land use in Belize

In this article the author explores deforestation in Belize and the impact that road making has on the landscape and development of the country. Roads are what allow access to remote forests in the country and they do not always lead to the most efficient use of the land. The author suggests that is GIS methods were put into use by the people making the road then the land could be use more efficiently. By studying the land through the use of GIS it is more likely that road planners would have a better idea of what resources these roads may lead to so that trees are not needlessly cut down in vain. By planning out the use of land spatially and in the context of the environment, rather than just clear cutting a road, there can be a cut down on unneeded loses.

By following the model of von Thiinen and the equations that can better determine the cost and benefits of land use we can put value to the land so that a plot of land is used to its best economic and environmental potential. Methods like this and GIS can be used to better plan out the use of land not only in Belize but really anywhere there is land to be developed.

Chomitz, Kenneth M., and David A. Gray. "Roads, Land Use, and Deforestation: A Spatial Model Applied to Belize." Oxford University Press, n.d. Web.

Abstract: Ecuador's Rose Farms

Behind Colombia, Ecuador is the world's leading exporter of cut roses. In addition, they export numerous other cut flowers. The United States of America is the number one consumer of Ecuadorian roses, and the rose floriculture provides significant economic impact in both Ecuador and the U.S.A. This project's aim is to provide a visual of rose farm concentration in Ecuador and provide market information on the quality of roses as it relates to altitude. A map such as this does not exist, and as such, this map will provide a social service to the rose growers in Ecuador. ExpoFlores, an organization that manages the social and environmental impact and image of the Ecuador's flower farms, provides a list of farms. From this list, I will create my own specific list of rose farms. Luckily, most farms have a website;however, most do not list the address, but the town. Since the exact locations of farms are not always provided, I will use Normalized Digital Vegetation Difference (NDVI) technology through ArcGIS online to locate the farms.

Digital Elevation Models (DEM) will be used to determine the altitude of the farms. Rose growers in Ecuador claim roses grow taller, stronger and straighter with higher altitudes. Once I have the farms location and altitude plotted, I will refer to sights such as FlorEcuador and ExpoFlores to see if the quality of the rose does indeed correspond to the altitude. If the DEM model proves to be too time intensive, I will then plot all flower farms to create a map which models concentration of rose farms compared to other flowers.

Industrial Evolution in Austin, Texas: From Environmental Hazards to a High-Tech Explosion (Abstract)

Grady Sampley

Abstract:

As the Capital of Texas, Austin has always been a major epicenter and leader for  Texas economic and cultural progression. Generally, Texas has been known for their large-scale  manufacturing industry wherein the petrochemical sector takes the lead. This highly industrial  economy and culture carries along with it a variety of environmentally hazardous byproducts.  Austin has also historically absorbed this kind of large-scale manufacturing industry as will be  shown in this project via GIS applications using the Toxic Release Inventory (TRI); however, as it  has advanced into modern times, Austin has moved towards a more innovative, creative, eco-friendly, and high-tech culture and economy. This budding cultural and economic change has resulted from the influx of young and educated populations who are mainly attracted to Austin’s unique and recently fostered progressive reputation which, in turn, prompted the explosion of its high-technology industrial sector generally due to the abundance of suitable potential employees. To show this explosion of high-tech industry within the Austin area my project uses the “Directory of Austin-Area High-Tech Firms” produced by The Greater Austin Chamber of Commerce in unison with GIS mapping applications. Through the utilization of both TRI and this directory, my project will illustrate the evolution of Austin’s Industrial landscape from a large-scale manufacturing industry – along with its environmentally hazardous byproducts – towards a much more clean, creative, and innovative high-tech industry. With these illustrations, my project analyzes the positive and negative implications of this industrial evolution on Austin’s socio-economic landscape.

Mexican-American Socioeconomic Status and Obesity

Source: 

Fisher-Hoch SP, Rentfro AR, Salinas JJ, Pérez A, Brown HS, Reininger BM, et al. Socioeconomic status and prevalence of obesity and diabe- tes in a Mexican American community, Cameron County, Texas, 2004-2007. Prev Chronic Dis 2010;7(3)

In this article, the risk for obesity and diabetes is examined in a small county on the U.S-Mexico border in Texas. The study is partial to Mexican-Americans, as the county is predominately made up of Mexican-Americans. Randomly selected and studied persons aged 35-64 year olds are looked at along with their socioeconomic status and the correlation to diabetes risk along with obesity. The final sample, after going through multiple cuts to make the sample more accurate, was made up of all hispanics with 68% being female. 

Variables such as, BMI, waist circumference, fasting blood glucose and insulin were taken into account. They then took this information and compared it too the annual household income, using GIS "to visualize spatial distribution" by different income quartiles. The findings were phenomenal, as this county was found to have a large uninsured racial minority population. People in the lower income stratum were found to be more likely to have undiagnosed diabetes, as the risk increases with age. Oddly enough, there were no differences between socioeconomic status with prevalence of obesity. 

Conservation of Viperids in North-West Africa Using Ecological GIS

When one thinks of the wilderness of Africa, one of the first concerns that comes to mind is the presence of venomous snakes.  Scientists are also extremely interested in the locations of these snakes, and in conserving them and their habitats.  They are now beginning to implement High-Resolution GIS imagery into their methods of determining the environments of these snakes.

As you can see in this first image, the use of raster data is crucial in the determination of the landscape of various regions in this section of NW Africa.  This map also includes vector data of the points at which the various species of snakes are located.  These two types of data are combined to create the map below, which shows the different species of snakes along with the likely overlap of species in the various regions.

The knowledge of the density and variety of viperids in the various biomes of NW Africa is instrumental in their conservation.  Knowing the variety and density of viperids in each type of habitat allows conservation biologists to tailor the conservation programs to the individual scenarios that occur.

1. • Brito et al., 2011
   • J.C. Brito, S. Fahd, P. Geniez, F. Martínez-Freiría, J.M. Pleguezuelos, J.-F. Trape
   • Biogeography and conservation of viperids from North-West Africa: an application of ecological niche-based models and GIS. Journal of Arid Environments, 75 (11) (2011), pp. 1029–1037

Links in Diabetes Rate Among Mexican American

 

Mexican Americans are more likely to have diabetes than any other ethnic group in the United States. Many believe that this is because the disease is genetic but may in part be due to the lower economic status of this ethnic group. Many cannot afford the decent health care that can identify early warning signs of diabetes and they do not get treatment right away.

 

 

 

Using GIS we can conclude that many of the clusters of diabetes form near the border to Mexico. The correlation between higher risks of diabetes and these areas is due largely to the socioeconomic status. Many Mexican Americans living along border towns are not wealthy and therefore cannot afford proper medical care. It can be seen that with better medical care comes less cases of diabetes among Mexican Americans. People who can afford the better medical care will be healthier and it shows among this particular group of people. This data can be useful for government agencies wishing to release funds for better medical care among struggling communities.

 

https://lms.southwestern.edu/file.php/5109/Literature/Wilson-2010-OBESITY_MEXICAN_AMERICANS.pdf

 

Swine Flu 2010

When the Swine Flu (H1N1) outbreak occurred in 2009 many people feared this outbreak. But by using GIS techniques scientists could be able to better watch out for an outbreak and know how to react when such a case happens. In Brownsville Texas GIS data is used to track past information about outbreaks of diseases from previous years. They can use this data to identify clusters where the disease may have sprung from or where it began spreading. If a certain disease is spreading rapidly in one specific area consistently, there may be some reason for this.

 

After you get a general feel for where and how severely specific influenza type diseases like ILI, RIDT, and S-OIV spread in a town like Brownsville, you can compare this to a new disease like Swine Flu and get a general idea for where your front line defenses should be. By mapping out specific danger zones you can actually be better prepared for when a major disease hits a city. When Swine Flu hit the city of Brownsville the city officials had a better idea of where care for the disease would be necessary and that way they were better prepared.

 

https://lms.southwestern.edu/file.php/5109/Literature/Wilson-2010-SWINE_FLU.pdf

Austin 2002 Species Distribution

 

Scientists are starting to use geographic information systems (GIS) to track growth and extent of plant life in a specific area. This information can be used to understand and predict the trends in certain species of plants. They can visually see growth, decline, or migrations that might be occurring and use that information to get a general idea of how a species is competing.

 

In order to get a good understanding of the environment there are three models of information that need to be taken into account, the ecological model, a data model, and a statistical model. The ecological data is information that can be taken from the field and tested to find results. The data model is the numerical value of the ecological findings and the statistical model measures the level of error and determines the significance. We can now see trends and find possible reasons for a change in a species and natural ecosystem of this specific area. Discrepancies between process model and statistical model will demonstrate our lack of knowledge and may also indicate the way forward. Different environmental factors affect specific areas differently.

 

https://lms.southwestern.edu/file.php/4373/Literature/Austin-2002-SpeciesDistribution.pdf