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GIS Planning Intern-City of Helen, Georgia
In the Summer of 2015 I joined the City of Helen, Georgia to become their first intern. My main focus for my internship was to create a geodatabase for the City. Prior to my arrival, the City of Helen had very little knowledge of the power of GIS, needless to say, there was very few GIS data of the city. As part of my internship, I introduced the concept of GIS to the city creating a Geodatabase with more than 30 layers. I created several maps, all of which are in use for the city today. Many of my maps are also being used to illustrate and gather ideas for the City's Comprehensive Plan.
Along with my GIS work, I participated in City Commission Meetings, a review of the financial budget, and I used spatial statistics to determine the appropriate use of an annual paving budget to repair the road system for a portion of the City.
All my maps, a list of the geographic layers I created, and other planning related work I completed can be seen in following slideshows.
Along with my GIS work, I participated in City Commission Meetings, a review of the financial budget, and I used spatial statistics to determine the appropriate use of an annual paving budget to repair the road system for a portion of the City.
All my maps, a list of the geographic layers I created, and other planning related work I completed can be seen in following slideshows.
GIS and Climate Change in the Andean Mountains in Southern Peru
In the Summer of 2015, I was chosen from a pool of other graduate students to be a graduate assistant on a short-term study abroad trip, led by Climate Scientist Dr. Baker Perry. During my time, along with assisting Dr. Perry. I collected GPS points and observed the impacts of climate change to the area. During my time there, I observed temperature differences for the area. Temperature varies throughout landmasses and geographical extents across the world. There are many factors that influence temperature, such as latitude, altitude, wind patterns, and surface albedo. As we progress into the 21st century, we are now experiencing warmer temperatures than ever recorded. In colder climates of the world, snowfall is becoming less abundant, ice caps are becoming less prominent, and the quality of life for the flora and fauna that rely on these colder conditions are weakening.
Upon our arrival back to the United States I conducted a GIS Analysis of this phenomena and wrote a research paper over the matter. In this, I used Landsat 8 Imagery to show the variance of temperature in the area of the Cordillera Vilcanota around an 8-day trek we took. During this trek, Dr. Perry myself and a group of undergraduate students observed Osjollo Anante Ice Cap and an ice corridor above Laguna Sibinacocha, two prominent features that have received considerable rates of ice melting in recent years, in spite of their higher altitudes. It is believed that places with higher elevations, will receive a higher rate of temperature increase, than places of lower elevations. To support this hypothesis, this study will apply a list of algorithms to extract temperature values from a temporal analysis of this Landsat 8 Imagery.
Perhaps the most surprising result of this analysis was the wide ranges in temperature in each of the images, and how these ranges increase through each year. The results show that the low, average, and high temperature for July 22, 2013 was: -15.95, 6.46, and 25.98 degrees Celsius. The low, average, and high temperature for June 24, 2014 was -15.05, 9.75, and 27.66 degrees Celsius. Lastly, the low, average, and high temperature for July 13, 2014 was -16.52, 11.16, and 33.88 degrees Celsius. With respective standard deviations of these years, from 2013, 2014, and 2015, were 12.97, 13.91, and 15.11. This shows that along with an average temperature change of 4.7 degrees Celsius, the standard deviation grew 2.24 units. This shows that along with higher temperatures, there is a higher range of temperatures throughout the region.
These results explain that some areas are more greatly affected by climate change than others, in respect to ground surface temperature. Ground surface temperature, being directly affected by albedo, assumes that these areas with higher temperature increases than others have experienced an increase in solar radiation absorption. In more undeveloped regions such as this region that experiences variable snowfall, one would assume that places with less snow than previously seen would have a greater albedo, thus leading to greater temperature.
While the color gradient on these maps provide a good insight on the temperature ranges of each individual year, it does not provide a good understanding of how these temperatures have changed throughout the years. In order to combat this issue, an additional map was made using the shapefile created from the ROI tool in ENVI, a point shapefile, showing the temperature change from 2013-2015 of each pixel. Each temperature difference was classified into 7 classes, with white being no change or a decrease in temperature, light red being a small change in temperature, and darker red being greater changes in temperature.
This map gives a clearer representation of how climate change in the Andes Mountains has impacted temperatures. The hypothesis of this study, that suggests that higher elevations receive higher temperature increases than lower elevations are proven wrong from these methods. This study shows that, while there have been increases in higher elevations, these increases range from 3-10 degrees, in in some cases, such as the southwestern portion of Osjollo Anante, at 5,540 meters have experienced a reduction in temperatures. The ice corridor above Laguna Sibinacocha received moderate temperature range around 1-3 degrees Celsius as well. Other higher elevations such as Candor Pass at 5,205 meters received a reduction of temperature. On the northeastern portion of the study area, at an elevation around 4,000 to 5,000 meters, temperatures have been rising considerably, in some places 15-25 degrees Celsius higher in 2015 than in 2013.
The results of this project conclude that greater attention needs to be taken into concern on the eastern side of the Andes Mountains, towards the Amazon River. This area is below the tree line. Most of the study area is well above the tree line which is often more vulnerable to higher albedos, and thus warmer temperatures. Mentioned earlier, the eastern portion of the Andes are generally moist, however as precipitation levels have decreased the moisture of this region has decreased as well. The results of this project suggest that decreases in moisture in these areas have resulted in drier climates, and higher temperatures.
Upon our arrival back to the United States I conducted a GIS Analysis of this phenomena and wrote a research paper over the matter. In this, I used Landsat 8 Imagery to show the variance of temperature in the area of the Cordillera Vilcanota around an 8-day trek we took. During this trek, Dr. Perry myself and a group of undergraduate students observed Osjollo Anante Ice Cap and an ice corridor above Laguna Sibinacocha, two prominent features that have received considerable rates of ice melting in recent years, in spite of their higher altitudes. It is believed that places with higher elevations, will receive a higher rate of temperature increase, than places of lower elevations. To support this hypothesis, this study will apply a list of algorithms to extract temperature values from a temporal analysis of this Landsat 8 Imagery.
Perhaps the most surprising result of this analysis was the wide ranges in temperature in each of the images, and how these ranges increase through each year. The results show that the low, average, and high temperature for July 22, 2013 was: -15.95, 6.46, and 25.98 degrees Celsius. The low, average, and high temperature for June 24, 2014 was -15.05, 9.75, and 27.66 degrees Celsius. Lastly, the low, average, and high temperature for July 13, 2014 was -16.52, 11.16, and 33.88 degrees Celsius. With respective standard deviations of these years, from 2013, 2014, and 2015, were 12.97, 13.91, and 15.11. This shows that along with an average temperature change of 4.7 degrees Celsius, the standard deviation grew 2.24 units. This shows that along with higher temperatures, there is a higher range of temperatures throughout the region.
These results explain that some areas are more greatly affected by climate change than others, in respect to ground surface temperature. Ground surface temperature, being directly affected by albedo, assumes that these areas with higher temperature increases than others have experienced an increase in solar radiation absorption. In more undeveloped regions such as this region that experiences variable snowfall, one would assume that places with less snow than previously seen would have a greater albedo, thus leading to greater temperature.
While the color gradient on these maps provide a good insight on the temperature ranges of each individual year, it does not provide a good understanding of how these temperatures have changed throughout the years. In order to combat this issue, an additional map was made using the shapefile created from the ROI tool in ENVI, a point shapefile, showing the temperature change from 2013-2015 of each pixel. Each temperature difference was classified into 7 classes, with white being no change or a decrease in temperature, light red being a small change in temperature, and darker red being greater changes in temperature.
This map gives a clearer representation of how climate change in the Andes Mountains has impacted temperatures. The hypothesis of this study, that suggests that higher elevations receive higher temperature increases than lower elevations are proven wrong from these methods. This study shows that, while there have been increases in higher elevations, these increases range from 3-10 degrees, in in some cases, such as the southwestern portion of Osjollo Anante, at 5,540 meters have experienced a reduction in temperatures. The ice corridor above Laguna Sibinacocha received moderate temperature range around 1-3 degrees Celsius as well. Other higher elevations such as Candor Pass at 5,205 meters received a reduction of temperature. On the northeastern portion of the study area, at an elevation around 4,000 to 5,000 meters, temperatures have been rising considerably, in some places 15-25 degrees Celsius higher in 2015 than in 2013.
The results of this project conclude that greater attention needs to be taken into concern on the eastern side of the Andes Mountains, towards the Amazon River. This area is below the tree line. Most of the study area is well above the tree line which is often more vulnerable to higher albedos, and thus warmer temperatures. Mentioned earlier, the eastern portion of the Andes are generally moist, however as precipitation levels have decreased the moisture of this region has decreased as well. The results of this project suggest that decreases in moisture in these areas have resulted in drier climates, and higher temperatures.
The following two maps were created upon my return to a short-term Study Abroad Trip in the Cordillera Vilcanota, a mountain range in the Southern Peruvian Andes. During this trip, I was a graduate assistant for my professor who has spent the past several years researching climate change and its force on the tropical glaciers, ice caps, and ice sheets of this area. I was asked to complete maps of 2013, 2014, 2015 that compared the display temperature, and quantify they difference in temperatures ranges throughout the years. The first map shows a color scale, from blue being the coldest, and red being the warmest, showing the range of temperatures for 2015. I created a similar map for the years 2013 and 2014 as well. The following map shows a red color gradient displaying the changes in temperature from 2013 to 2015. All maps were created from applying a series of algorithms in ArcGIS to change the values of Bands 10 and 11 of a Landsat 8 Image to degrees Celsius. I then create a series of ROI's from a scatterplot in ENVI to create a point shapefile showing the differences in temperature throughout the years. This shapefile is the base map for the second map.
