Voter Migration and the American Electorate

When viewing a map of the political partisan spatial layout amongst states in the United States one can see it is nonrandom. The partisan clumps that exist within the United States are "self-perpetuating" and voter migration in homogenous partisan groups is increasing over time. The consequences of these homogenous partisan groups require more study. Bishop asserts that the clustering of like minded groups only narrows ones point of view. Whereas, in "heterogenous communities [they] teach their members to compromise" through exposure of opposing view points. Bishops assumes that if this trend continues within the states then it will result with a country of "intolerance that will tear...apart at its seams". This study is concerned with what is creating and defining these partisan boundaries and if geographic sorting in the electorate is an issue at all.
It is important to consider all of the factors that could be contributing to this unbalanced partisan spatial layout. Some of these factors include "population migration,...polarization of the national parties and the evolution of individual attitudes". This migration of ideals is a natural occurrence as one gravitates towards social settings compatible with their own mindset. In order to truly determine this individual migration this study focuses on individual patterns such as migrating towards or from like minded areas.
Data from the YouGov Cooperative Congressional Election Study supports the idea that partisanship is heavily considered during relocation. They acquired this data from a national sample taking from recent movers asking them to rank in importance their different considerations for their final choice in destination.

Even though co-partisanship was not the foremost considered reason for the final destination of the movers about 30 percent did heavily weight partisanship. This percentage can make a substantial effect. Despite being able to see concentrations of partisanship across the country it is hard to determine wether individual migration contribute to these apparent partisan differences. This study is the first of its kind in examining geographic sorting effects. However, this study concludes that jobs and family concerns remain to be the most important factors in regards to migration. 

URBANIZATION AND ITS EFFECT ON RUNOFF

This article was on a study done in the Whiteoak Bayou Watershed, which is located near Houston, TX. The study looked at the watershed's ability to urbanize without being compromised. Generally, a watershed can handle some development and runoff because they have a certain capacity for adjusting to change. The study used a GIS technique called Spatial Metrics to look at how the land was being used and to view changes to it, and to see if the development and runoff patterns had caused the watershed to be pushed beyond where the hydrologic conditions could correct themselves. The method allows the land to be divided into different categories so that it can be more thoroughly analyzed. Once all the development data was collected the people conducting the survey converted the information into raster data, assigning different values to developed and undeveloped areas. This raster data was then converted into spatial metrics that allowed the researchers to identify important information about runoff.

As you can see from the graph above, there is an obvious upward trend in the amount of runoff that occurs each year since the 1950s. The researchers concluded that this watershed reached a level beyond that which it could handle. The runoff depth was effected by both the amount of development in the area, and the amount of precipitation. The researchers also noted that this method was done specifically for this area, and any application of it to other watersheds should be done with care.

Olivera, Francisco, and Buren B. DeFee. "Urbanization and Its Effect On Runoff in the Whiteoak Bayou Watershed, Texas1." (2007): 170-182.

Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning

The 3G iPhone was the first consumer device to provide a seamless integration of three positioning technologies: Assisted GPS (A-GPS), WiFi positioning and cellular network positioning. This study presents an evaluation of the accuracy of locations obtained using these three positioning modes on the 3G iPhone.The GPS technology adopted in most cell phones employs a server-side component
for the processing of the GPS signal and is referred to as Assisted GPS (A-GPS). While
high-sensitivity GPS chipsets have been adopted in recent years, A-GPS does not work
well indoors and as a result complementary positioning systems are employed under
these conditions.

Description of the positioning method behind the WiFi positioning system

Statements by Skyhook Wireless regarding the performance of its WiFi positioning

system

Most GPS-enabled cell phones, including the 3G iPhone, employ a technology known as Assisted GPS (A-GPS). With A-GPS many of the functions of a full GPS receiver are

performed by a remote GPS location server. This remote server provides the A-GPS
mobile device with satellite orbit and clock information; the initial position and time
estimate; satellite selection, range and range date; and position computation.

Topography-based Analysis of Hurricane Katrina Inundation of New Orleans

Geospatial data are critical for hurricane response and recovery activities,and topographic data are a primary requirement. High-resolution, high-accuracy elevation data were used extensively during the first weeks of response to Katrina to provide rough estimates of inundation, and they continue to be
useful for studies of the impacts of the storm. Lidar is a relatively new remote-sensing technology
that has advanced significantly over the last 10 years and is now a standard survey tool used by the mapping industry to collect very detailed, high-precision measurements of land-surface elevations. In an effort to improve the quality of the Nation’s topographic data available for mapping and scientific

This image uses colors to represent the sea levels of New Orleans. 

applications, the U.S. Geological Survey (USGS) has been integrating recently collected lidar elevation data into the National Elevation Dataset (NED).












Lidar data were collected for southeastern Louisiana in 2002 under the auspices of the Louisiana Oil Spill Coordinator’s Office. These data are publicly available through Atlas, the Louisiana statewide geographic information system Web site operated by Louisiana State University

This image has taken the image above and converted it into the lidar site. 

Coupling Geographic Information Analysis Techniques with Ethnographic Methods in Urban Research

This article that I have selected to write about emphasizes on how GIS has recently been adopted in the ethnographic component of the Welfare Project. We must understand that when the Welfare Project was being created, GIS was not thought as an original design. We can identify some of the
challenges and opportunities faced in promoting GIS within multi-site ethnography and describe some of the ways we have used GIS to facilitate distance-based ethnography. One advantage of the mapping and data visualization capabilities of a GIS is that the system can handle data collected on multiple spatial scales.

This image is just one example on how we can use GIS to map population densities 

The Welfare Project includes a focus on children and child development, includes a disability component, incorporates qualitative data from an extensive ongoing family and neighborhood ethnography, includes both welfare recipients and non-recipients, is based in three different geographical contexts, and is longitudinal in design. Within the Welfare Project, we characterize the ethnography as being one of ‘‘structured discovery,’’ an approach that focuses on primary research topics while building in sufficient flexibility to capture emergent themes and unanticipated information.

The coordinating site pursued multiple strategies to introduce GIS concepts and methods to ethnographers. Throughout the project we have worked with one or more sites to create new and integrate existing geospatial databases within a GIS framework. The intent was both to demonstrate to the sites what we could do with the data they collect and to encourage the collection of geographic
identifiers, however crude, on the location of family activities and neighborhood resources within each city.

A “Neogeographical Education”? The Geospatial Web, GIS and Digital Art in Adult Education

To understand neogeography, the basics of science of geography plays a key role. A linkage between science of geography and digital art are a relationship provided by neogeography. As explained by Fivos Papadimitriou, neogeography encompasses the traditional ideas of geography while also participating in newer ideas such as a variety of personal, intuitive, absurd or artistic explorations and representations of geographical space. With the help of neogeography there is a new outlook on what is going on beyond the traditional geography, the perspective now demonstrates a larger view on spacial experiences through a digital cartography. Although neorogeography has been an idea from middle 1990's it's techniques were not very popular. It was not until recently that neorogeography became a questionable notion in relation to its impact on geographical education. Along with considering neorogeography, Papadimitriou assesses the Geospatial Web and digital art and their impact in geographical education. From one outlook, neogeography allows for individuals to interpret the historical and cultural dimensions of the enrichment of geography. Meanwhile there are those who would argue that using neogeography and Geospatial Web will lead to the end of GIS workers to amateurs who can now photograph and upload their own pictures on the web. Now the goal is to continue to create more advanced technology to make GIS workers job easier and widespread.

Topography-based Analysis of Hurricane Katrina Inundation of New Orleans

After the effects of hurricanes along the coast of Gulf of Mexico and the United States, the importance of high-resolution, high-accuracy elevation data proved valuable for development of topographic equipment. Because of the equipment there were a couple of light detections of hurricane Katrina causing the inundation in New Orleans a few years back. In order for a community to take the proper cautions and procedures, geospatial is a critical factor. Since the day of the trauma caused by the hurricane, high-accuracy elevation data was one of the resources used to estimate the inundation. As technology increases the mapping industry is able to create a clear high-precision measure of land-surface elevations, placing a large pressure on incorporating newer techniques like the lidar elevation data. Thanks to the involvement of the new elevation data that was installed around June 2005, about two months prior to the hurricane, people were able to properly respond to Katrina. Due the availability of the elevation data collected in 2002 from southern Louisiana, it became a beneficial resource to many geospatial data users who were responding to the aftermath of Katrina to have the information online. Few after the effects from the hurricane there was a high demand for maps to illustrate an estimation of how much of the city would be flooded.

Gesch, D. (n.d.). Topography-based Analysis of Hurricane Katrina Inundation of New Orleans. Science and the Storms: The USGS Response to the Hurricanes of 2005, 53-56.

The chart is an illustration of the contribution of foot of flood water per cumulative flood volume and area within New Orleans, La during September 2005. The flood depth is measured in relation to the elevation of the water surface within the city. For example, at elevations of 10–12 ft (3–3.7 m) below the elevation of the floodwater surface, only a relatively small area of less than 5 mi2 (13 km2 ) is inundated, but at the elevation of the water surface as measured on September 2, nearly 75 mi2 (194 km2 ) are inundated."

Global Consequences of Land Use

               This article discusses the effects of land use on the environment. Looking at food resources, freshwater resources, forest, regional air quality, and infectious disease. Using GIS they are able to address a growing issue that has gone on unmonitored for hundreds of years.
                After evaluating the information it is discovered that agriculture and pasture land rivals that of the largest terrestrial land mass or ecosystem. with nearly 40 percent of all land being covered by either farms or pasture land. This has a profound effect on runoff into the water tables and irrigation drawing water from the water table both very unsustainable practices. Also the increase of infectious disease is allowed to spread much more rapidly and uniformly. Most all excess nitrogen and phosphorus that runs in to dead zones of river deltas resulting from the clearing and subsequent use of farming practices on the land. Since 1850 over 35% of human carbon emissions have been attributed to land use and change. Often from the amount of energy and heat either reflected or observed. Often any land change often leads to a radical change in the hydro logical cycle to account for irrigation and sanitation.

               The map blatantly displays the change of land over thousands of years of use and what it was used for or the Bio sphere in each area. Land change can be caused from a number of reason not addressed in the map but related to deforestation, road construction, dams, and urbanization all increase the rate of deforestation. Not shown but could be interesting would be the a map that shows the 40% or so of the eroding and currently degrading land.
                     This is a growing issue that needs to be addressed and better managed using GIS we are able for the first time address the whole picture and see the change over time, for what reason, and how to combat the change and resulting effects on the environment.

Foley, Johnathan A. "Global Consequences of Land Use." Science 309.11 (2005): 570-75. Print.

Statistical confirmation of indirect land use change in the Brazilian Amazon

           One environmental impact that has raised serious concerns is loss of Amazonian forest through indirect land use change (ILUC), whereby mechanized agriculture encroaches on existing pastures, displacing them to the frontier. This phenomenon has been hypothesized by many researchers and projected on the basis of simulation for the Amazonian forests of Brazil. It has not yet been measured statistically, owing to conceptual difficulties in linking distal land cover drivers to the point of impact.
           Global demands for food and biofuel are expected to soar in coming decades . To meet these demands, new land will need to be brought into production. Brazil, with its abundant land resource, will no doubt continue to play an important role as a global supplier of agricultural commodities . Although conversions of forest to mechanized agriculture have been observed, pasture expansion remains by far the primary direct cause of Amazonian deforestation. Recent research suggests, however, that mechanized agriculture may exert a significant indirect effect, by the displacement of old pastures, and their recovery on the forest frontier. The present letter takes this displacement mechanism as ILUC, for the purposes of its analysis.
         

           In general, statistical explanations of land cover change have defined explanatory and dependent variables for a single location, possible with a set of nearby neighborhoods, a method that does not capture the effect of potentially distant influences. The approach in this letter overcomes the problem of distal spatial effects by using GIS to associate locations in the forest frontier where deforestation is occurring with ‘distant’ neighbors in the settled agricultural parts of Amazonia. The statistical models implemented possess a sufficiently general form that they can be implemented wherever ILUC is of interest to policy makers.
            The statistical models indicate that deforestation in the forest frontiers of the basin is strongly related to soy expansion in its settled agricultural areas, to the south and east.


Source: Arima, E. Y., Richards, P., Walker, R., & Caldas, M. M. (2011). Statistical confirmation of indirect land use change in the Brazilian Amazon.Environmental Research Letters, 6(2), 024010.

Socioeconomic Status and Prevalence of Obesity and Diabetes in a Mexican American Community, Cameron County, Texas, 2004-2007

In recent years there has been an increase of diabetes cases, not only in the older population but varies from young adults and children to elders. One of the leading factors for this large increase of diabetes cases is the increase in poverty among minority groups. Finding a group within US boarders, a group of people were chosen to partake in an experiment to determine the increase of obesity and diabetes within the community. The selected population consisted of 310 people from ages ranging from 35 and 64 years old. More specific, the goal of the experiment was to look at the socioeconomic statuses within Mexican American communities to determine whether or not it played a role in their health. GIS was then incorporated to illustrate "the spatial distribution of households by income quartile and the density of sampling." Using longitude and latitude coordinates to geocode the location of the households were revised for accuracy and later layouts were created through ArcMap. Overall the conclusion was made that due to low socioeconomic income Mexican American families along the borders had higher populations of children with diabetes. Due to the lack of insurance and or lack of money, there is a large percentage of children who go undiagnosed along with the overall factor of being in risk of developing the disease somewhere along their futures. 

The graph is a representation on the part of the research focused on the percentage of participants who tested positive for diabetes. Considering Cameron County Hispanic Cohort from 2004 to 2007, the information is categorized through ages and by socioeconomic status. The first quartile consisted of participants with an income of < $17,830, and people in the third quartile whose incomes ranged from $24,067-$31,747. 

-Hoch, F., & P, S. (2010). Socioeconomic Status and Prevalence of Obesity and Diabetes in a Mexican American Community, Cameron County, Texas, 2004-2007. Preventing Chronic Disease: Public Health Research, Practice and Policy, 7(3), A53-A53.

Rain Forest Roads

     This Case study shows how GIS has been used to give Socio-spatial information to the country of Brazil to better manage and propagate the Amazonian basin and State lands. Citing manly roads as the primary cause of deforestation by fragmenting the forest into a Dendritic pattern. With the use of Geographic Modeling and methods to determine the true area roads in particular take up in this area. Discovering that State and federal "official roads" only account for .005 km2 of the land of the Amazonian Basin while unofficial or logging roads and agricultural roads account for near .586 km2 of the land. Giving reason to concentrate on the pattern and expansion of these unofficial logging roads. Although these temporary logging roads can quickly be consumed and taken over by the forest they  often allow access from villagers and expansive farms to take root in the land and prevent new growth.

       The map above represents the "dendritic" identified with deforestation and expansion of civilizations, many studies have been done to identify why this method is replicated by humans in the environment. Ariba uses GIS to see if hydro-logical patterns play a role in both the Expansion of logging roads but also density of the Forest. 

Arima, E. Y., & Walker, R. T. (2008). Emergent Road Networks. In The Fragmentation of Space in the Amazon Basin: (6th ed., Vol. 74). N.p.: 2008 American Society for Photogrammetry and Remote Sensing.

Evaluating spatial patterns of drought-induced tree mortality in a coastal California pine forest

     Recently, California has been plagued by droughts caused by improper water management as well as atmospheric blocking of high pressure weather. This is a major problem because the central valley of California is one of the biggest agricultural producing areas i the US. Beyond an economic impact, these droughts also have an ecological impact when forests die or change composition due to less moisture increasing temperatures.

     In this study, a team used aerial photography and LIDAR to map out the density and health of Bishop pine populations on Santa Cruz Island off the coast near Los Angeles. They took information such as precipitation and cloud coverage and compared it to models which had tree density and height in order to see how the drought affected the forest. They determined that larger trees located in medium elevations that were partially concealed by fog survived the drought more readily. Surprisingly, trees in the center of the island did not fair so well, in part due to higher elevation as well as having no cloud cover due to being on the leeward side (behind the mountain). The innovative thing done in this study was that dead trees where found by differentiating LIDAR models of trees with dead canopies; basically, the radar did not reflect off of leaves and this allowed them to find clusters of trees that had only died because of the recent drought.
     Using this kind of refined methodology we can create programs that tailor to specific species of trees in order to map out drought effects on natural ecology. Since this study focused on Bishop pines on one Island, maybe we can use their models to map out other pine species along the coast of California. It would probably be easy to map larger trees such as redwoods in coastal state parks such as Big Sur.   

    Graph made using data from a LIDAR elevation model and aerial photography. Taking the information from all eight graphs allows us to "paint a picture" of Santa Cruz Island and see the effects of droughts.  

     Graph showing the mortality of the Bishop pine on Santa Cruz Island during recent droughts in Southern California.



     Source: Baguskas, S. A., Peterson, S. H., Bookhagen, B., & Still, C. J. (2014). Evaluating spatial patterns of drought-induced tree mortality in a coastal California pine forest. Forest Ecology and Management, 315, 43-53.

Spatial Distribution of Suicide in Queensland, Australia

This study explored the spatial distribution of suicide, while considering both gender and age. 

I chose this study during preliminary research for my final GIS project. While I am applying Durkheim’s theory of anomic suicide, this study demonstrates the methodology for analyzing suicide rates. This study, conducted in 2010, used GIS and sociological theory to analyze and explore the spatial relationship of suicide distribution in Queensland, Australia. Queensland, Australia is the northeast portion of the country, the second-largest and third most populous state. This state is less centralized, with most of its population living in smaller urban areas, and greatly relies on tourism. This study analyzes the spatial distribution of rates of suicide deaths, as well as other demographic variables, at the level of the local government, mapping the clusters with GIS. This study argues that the mapping of the suicide clusters highlights vulnerable areas, and the need to address mental health services. In line with other empirical research, the majority of suicides were male, and around half of the suicides were committed by young adults. The gendered division in suicide is thoroughly researched and documented. Due to socialization practices, women attempt suicide three times that of men, but men commit suicide at a higher rate than women. This discrepancy is due to modes used to commit suicide, with men using more destructive tools or situations such as guns, while women use medication or other methods with a higher likelihood of being stopped. 

In Figure 1, we see that male suicide is spread throughout the north and the east, but the female suicide is concentrated in the north and along the eastern shore. Brisbane had the most cases of suicide, while Wide Bay Burnett had a cluster of high risk areas of suicide, due to the few health resources available. This research is important to identify clusters of suicidal actions and completed cases, so there may be further development of resources within communities. Additionally, this also shows the variation in both gender, age, and geographic location, emphasizing the connection between available resources and suicide cases. 

Xin, Qi, Tong Shilu, and Hu Wenbiao. 2010. "Spatial Distribution of Suicide in Queensland, Australia."BMC Psychiatry 10, 106-115. 

Improving Health Outreach Using GIS Data

Background

As an alternative to those who do not have Internet access or with limited health literacy, Preston Medical Library in Knoxville, Tennessee offers a free telephone-based Consumer and Patient Health Information Service (CAPHIS) which mails packets filled with health information specific to a caller's needs and at a literacy level that matches that of the caller. Medical libraries like these began using US Census data in the 1990's when Census and demographic data became more readily available to the public through TIGER files as well as American Fact Finder (AFF) and the American Community Survey (ACS). In 2003, the Preston Medical Library decided to use archived information - addresses, zip codes, health information - on calls from 1998 to the present in order to establish a calling rate as well as the areas of frequent callers at a rate of calls per 100,000 and plot this data on a map. Using this information, the Preston Medical Library was able to create a choropleth map that illustrated the frequency of callers to the CAPHIS in the context of disease prevalence within the state of Tennessee with the aim of reaching out to those areas of Tennessee with unmet medical needs.

Results

Through its study, Preston Medical Library ultimately found that many areas in Knox county and surrounding counties contained a high number of people who were at high risk for medical complications due to age, poverty, disability, etc., but who also did not take advantage of Preston's CAPHIS. More specifically, through the maps displaying this information, Preston Medical Library was able to clearly see the particular counties in Knoxville that were good targets for outreach by the CAPHIS, with a total of 31 zip codes in 14 counties containing strong candidates for CAPHIS outreach due to their unmet health information needs. 

This figure shows the rate of calls and ambulatory disability per 100,000. 

Conclusion

As demonstrated by the example of Preston Medical Library, GIS data can be extremely helpful for determining demographic patterns and tendencies in order to make more informed decisions regarding public health and outreach. Choropleth maps in particular provide a much clearer way to see and understand populations and, as the article notes, are a much more efficient data source than numerical data when the size of data sets increases. Overall, maps of this kind of information are an invaluable data source even if for the sheer fact that maps provide a much more interesting and compelling story than numerical data. 

Source: Socha, Y., Oelschlegel, S., Vaughn, C., & Earl, M. (n.d.). Improving an outreach service by analyzing the relationship of health information disparities to socioeconomic indicators using geographic information systems. Journal of the Medical Library Association : JMLA,222-225.

Geodesy in the 21st Century

Geodesy is the study of Earth's size, shape, orientation, and gravitational field, and the variations of these qualities over time.  Nowadays this field is concerned with changes in the shape of Earth's surface, because small detectable changes are associated with issues with impactful events on society, such as ice melting, sea level rise, land subsidence, and aquifer depletion. Twenty-first-century geodetic studies are dominated by geodetic measurements from space. Current space geodetic measurements can detect small movements of the Earth's solid and fluid surfaces as well as changes in the atmosphere and ionosphere. Space-based geodetic observations can be categorized into four basic techniques: positioning, altimetry, interferometric synthetic aperture radar (InSAR), and gravity studies. Precise positioning is the fundamental geodetic observation required for surveying and mapping. Instead of using traditional  triangulation and leveling networks that require line of sight between measurement points, space geodetic methods are use line of sight between the measurement points and celestial objects or satellites. Relative positioning can be achieved over very large distances in which the precision is almost independent of the distance between the two measurement points. Altimetry, rather than measuring 3-D changes by positioning techniques, involves only changes in surface elevation. Altimetry measurements are conducted by releasing pulses towards the Earth's surface every several milliseconds, resulting in circular ground measurements along the satellite track. Because of these large circular measurements, altimetry measurements are useful for measuring flat surfaces. InSAR is a powerful method to detect surface change. This method compares  pixel-by-pixel SAR phase observations of the same area acquired from roughly the same location in space to produce digital elevation models. Satellite orbits are very sensitive to lateral variations in the Earth's gravity field. Precise measurements of satellite orbits by ranging (distance) and other technologies yield accurate determination of the Earth's shape and its variations over time.
Wdowinski, S., & Eriksson, S. (2009). Geodesy in the 21st Century. EOS,90(18), 153-155.
http://www.ngs.noaa.gov/PUBS_LIB/eos5may_geodesy-21st-century.pdf

Do Indigenous People Have Boundaries?

Participatory cartography is particularly useful for management of indigenous lands, which makes it more equal. Most post-colonial mapping/bordering is often unstable, but indigenous countermappings can create maps and borders more true to what the indigenous peoples themselves consider correct. The study here concerns Pemon lands in Gran Sabana, southern Venezuela. A Gramscian approach to hegemony is taken in regards to boundary making. It is more of a cultural project concerned with inequalities rooted in class and ethnicity, more than anything. The Pemon people face discipline to become "modern," such as having their practices referred to as "traditional" if they are risky, conservation-wise. Thus it is difficult to practice certain kinds of fire use and hunting. Much of Gran Sabana is located inside a national park. There an agency called EDELCA handles fire fighting. This study had fire fighters make their own maps in a workshop and they saw the landscape as pocked with fire scars, much unlike what the Pemon themselves saw. Ethnocartography was put into practice with the Pemon: all different ages groups and genders were studied and each group was able to create their own maps. It was found that teenagers created different maps than those made by their elders. What was the difference? Apparently the teens saw their lands as smaller. In conclusion, the notion that indigenous people don't have any boundaries is a myth.

Bjorn Sletto (2009): "'Indigenous people don't have boundaries': reborderings, fire management, and productions of authenticities in indigenous landscapes." Cultural Geographies 16: 253-277.

Using Fine-Scale GIS Data to Assess the Relationship Between Intra-Annual Environmental Niche Variability and Population Density in a Local Stream Fish Assemblage

GIS systems have proved useful in assessing species populations. Scientists are able to sample local populations and extrapolate their overall numbers. This analysis is applicable across a range of applications. This research analyzed the relationship between “environmental niche breadth and niche position and population density among species of stream fishes in a seasonally variable environment” using fine-scale GIS. They used this to study the patterns of 11 niche fish species. The data was collected four times a year on population and position. This allowed the researchers to find patterns in environmental variability that coincided with species variability.

Through the utilization of GIS study the analysis found that species in October were predicted by niche breadth and January was predicted by niche breadth and location. This gave them insight into the environmental factors that most effect species. It is integral to know which factors effect populations in different seasons. The results suggested that species are greatly affected by the amount and distribution of available habitats. This result transcends season and habitat. Both niche breadth and niche location affect local abundance.  

Knouft, J. H., Caruso, N. M., Dupre, P. J., Anderson, K. R., Trumbo, D. R., & Puccinelli, J. (2011). Using fine‐scale GIS data to assess the relationship between intra‐annual environmental niche variability and population density in a local stream fish assemblage. Methods in Ecology and Evolution, 2(3), 303-311.

Spatial prediction of species distribution: an interface between ecological theory and statistical modelling

     The ecosystem is a delicate and complex biological community.  Any effort for conservation or for obtaining accurate species distribution data requires more information about the ecosystem as a whole.  Scientists are able to overcome this obstacle by using GIS software and satellite imagery to map out ecosystems and identify important features.

     In order to better understand a particular ecosystem, researchers begin by identifying the vegetation in the area of interest.  Any patterns of vegetation identified provide a basis for further research and analysis. These patterns do not relate to any particular species, but rather to the vegetation’s growth and density.  As a result, the data does provide information as to the possible life found in a particular ecosystem.

    A statistical model is then developed to identify species distribution.  The statistical model uses several different tests on maps and images to analyze the ecosystem.  These tests include: statistical method, error function, regression analysis and significance tests. Various maps are needed to see the interaction that exists between models so as to identify obvious and subtle patterns.  The diagram below shows a regression analysis of  E. rossil stem density in Australia.

Austin, M. P. (2002). Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecological modelling,157(2), 101-118.

GIS in Hydrology and Water Management

In connecting ideas about climate, catchment, channels, and society, GIS began its use in hydrology and water management. Modelling using GIS can be helpful in river management, however the main concern with it is the quality of the data and its resolution.

The main use for GIS in river management would be flood insurance applications (mapping areas that are most at risk of flooding) and this could be done with high resolution spatial data. With the use of this high resolution data, we would be able to estimate the flood risk for a person, area, or event much easier. The one issue faced by this improvement in technology is that the high resolution typically downgrades the insurability of a client, which is a disincentive for people who want to be insured against floods and natural disasters. This example is just one challenge faced by GIS in the field of hydrology and water management. It faces both technological and social issues in the future, but the hope is that these kinds of problems can be solved by a greater distribution of information and processing power.


Clark, M. J. (1998). Putting water in its place: A perspective on GIS in hydrology and water management. Hydrological Processes, 12(6), 823-834.

Lidar and Hurricane Katrina

Hurricane Katrina imposed the inundation of New Orleans, LA, and Geographical Information Systems (GIS) technology was helpful in studying the effects of the natural disaster. Specifically, light detection and ranging (lidar) remote sensing is used as mapping technology in low-relief hurricane-prone coastal areas - like New Orleans. With a hurricane, elevation data is arguably the most important and most useful data that can be studied and utilized. Lidar is a standard survey tool that is used by the mapping industry to collect data. It collects very detailed, high-precision measurements of land-surface elevations. The National Elevation Database (NED) has recently been worked with by the U.S. Geological Survey (USGS) as it has collected lidar elevation data and incorporated it into the NED. High-resolution lidar-derived elevation data for southeastern Louisiana - including the New Orleans area - was already integrated into the NED, so when Hurricane Katrina hit, the data was available for response to the disaster.

The high-resolution data for southwestern Louisiana (New Orleans) was available online, and thus proved to be a valuable asset for geospatial data users that were responding to the aftermath of the disaster. The lidar-derived elevation data helped tremendously in creating a rough mapping of the depth and extent of the inundation created by Katrina. In the future, by combining the precise elevation information from lidar with accurate ground-based water-level information and inundation delineations derived from remote sensing, a complete history of flooding and water removal can be reconstructed.

Gesch, D. (2005). Topography-based analysis of Hurricane Katrina inundation of New Orleans. Science and the storms: The USGS Response to the Hurricanes of.

Collaborative GIS

Significant challenges remain for scholars and practitioners’’ thinking towards a new style of environmental and resource management. In an effort to work for economic, social and ecological balance, these parties have resort to collaboration with technical, scientific and business experts (along with many other experts) in order to reach this goal. GIS has become a “way to help bridge these divides” within the world. Specifically Collaborative GIS (CGIS), a networked collection of computer technology that allows participants to share information in an institutional setting that can help serve the purpose of managing resources and environmental issues efficiently.

CGIS can be very helpful in numerous ways, whether it is to provide information to another expert or scholar, or to help out someone in need of information for another project, it is like a huge network that everyone contributes to in order to help each other out. In many cases, CGIS can provide useful information; however on occasions, the information may not be as helpful as it seems. Based on who uses it, and how well the information’s validity and reliability is, will determine how well it is. It is important not to abuse CGIS by not providing inaccurate information and only providing useful, reliable information for others to use.

Ramsey, K. (2009). GIS, modeling, and politics: On the tensions of collaborative decision support. Journal of Environmental Management, 90(6), 1972-1980.

A Very Basic Overview of Fractals (in GIS)

Fractals are described by a geometric set (points, lines, areas or volumes) whose measure behaves in such a matter that the larger scale is not proportionately larger, instead it is larger due to more details being visible at the larger scale. This paper focuses particularly on fractals applied in spatial phenomena in four aspects; mathematical, theoretical, cartography and spatial handling data. In a response of measure to scale, the authors describe it as adapting to a real situation, trying to measure accurate lengths of the shore on an island versus the area of a circle.The measurements of the shore depend on cartographic (cartographic scale relays pixel size) generalization, which affects both length and area measurements. The "Steinhaus Paradox" refers to the fact that measured length increases with increasing accuracy. Study in this area about these details that affect measurements aroused from the study of nations and common boundary. With this early study, the scientist behind it discovered that detail becomes apparent at a predictable rate.  
The more irregular the line, then the greater the increase between the 2 measurements at different scales. If irregular, D will be greater than 1.
Self-similarity is defined as when any part of a feature is enlarged indistinguishable without vision of the feature as a whole. Irregular features are indistinguishable at all scales. This is used to create topographic scales.
In recursive subdivision of space, a self similar line is regenerated by recursive procedure. This was then used to develop algorithms to generate irregular fractal curves and surfaces. Self similarity is argued as the property of real landscape. Without self similarity, any stimulation would be visually unacceptable because the basic proof of nature is seeing.
The paper stresses that fractals rely on cartography and spatial data handling applications, which is the origin of the math equations.



ESRI definition of a fractal: A geometric pattern that repeats itself, at least roughly, at ever smaller scales to produce self-similar, irregular shapes and surfaces that cannot be represented using classical geometry. If a fractal curve of infinite length serves as the boundary of a plane region, the region itself will be finite. Fractals can be used to model complex natural shapes such as clouds and coastlines

         Recently, there have been several worldwide disease outbreaks.  These contagious diseases soon turned into epidemics that have claimed many lives.  Fortunately, doctors and scientists are able to track these diseases using GIS software, such as WebDMAP.  This program uses a process called adaptive spatial filtering.  This method relies on adaptive bandwidth filter  “that increases in size inversely with population density rate calculation”. 

There are five essential properties that scientists should use when analyzing disease maps.

            First, these disease maps need to be analyzed with using different base maps.  The figure below illustrates three different maps monitoring colorectal cancer in Iowa.

The next step requires that the disease-infected regions be displayed on the map.  This gives scientists a clear view as to where they should concentrate their efforts.

            Attention to geographic detail is essential when analyzing disease maps.  Geography can act as a highway for disease to spread.  One such example is a contaminated water source;  which can infect a large population of people and/or animals.

            The population’s age and gender need to be measured and recorded for accuracy.   Diseases have the potential to effect men and women differently.   A person’s age is a very important factor that determines the patient’s ability to resist the effects disease or infection.  

            The data collected and the disease/mortality maps created need to be made available to the public.   This is in an effort to offer an outside perspective that can be beneficial in preventing future epidemics.

Researchers have been able to use these maps to identify environmental characteristics and measure disease risk.

Beyer, K. M., Tiwari, C., & Rushton, G. (2012). Five essential properties of disease maps. Annals of the Association of American Geographers, 102(5), 1067-1075.