Lab 10 - Supervised Image Classification

GIS 4035

 

 

The map above is of Germantown, Md.  In this weeks project we were to work with Supervised Image Classification.  I worked to create spectral signatures and AOI features within EDRAS.  I was then able to produce a classified image from the satellite image that identified key areas of Land Use so they could be monitored moving forward.  This exercise also reinforced the ability to identify spectral confusion by identifying features that might have similar characteristics, but when viewed in different bands became more unique to identify.

 

Bringing all these elements together I was able to produce the above map, and show where there may be discrepancies in the classification with the distance inset provided.

 

Overall I enjoyed this lab, and it allowed me to gain a better knowledge of how images can assist in land classification through automated processes and tools in the EDRAS program.



Lab 9: Unsupervised Classification

GIS 4035

 

 

In Lab 9 we let the computer do some of the work.  Unsupervised Classification was my introduction to automated classification of an image based off of different spatial and spectral resolutions.  There was a little manual work to be done, but overall the program assisted greatly.  I was able to use both ArcGIS as well as ERDAS to reclassify and code images simply based off of the pixel colors and grouping like pixels together. 

 

In ArcMap I utilized tools like Maximum Likelihood Classification tool, and the Iso Cluster tool, while in ERDAS I utilized tools such as Unsupervised Classification found in the Raster tab, Classification group.

 

Ultimately using the tools provided I was able to generate the map above which shows each Class by name, and from this I was able to calculate the total Permeable and Impermeable surfaces.



Lab 8 - Thermal and Multispectral Analysis

GIS - 4035

 

 

In this weeks lab I was given the opportunity to interpret radiant energy, and utilize both ArcMap and ERDAS to interpret thermal infrared data from a multispectral image.  The map above highlights the merger of two rivers in Ecuador, the Daule River and the Babahayo river.  I approached the area with two questions:  Is there a lot of Vegetation at the Daule River delta?  Which river is warmer, the Daule River or the Babahayo River?

 

Utilizing a NIR band combination (R-4, G-3, B-2) I was able to show that there is little to no vegetation at the river delta, as this area is mostly urban.  I was then able to utilize the Thermal Band (band 6) and show that the Daule River (darker blue) is in fact warmer than the Babahayo River (lighter blue). 

 

Overall I found it quite interesting all the data you can gather and show utilizing the multispectral images.  I feel that the information that a person can gather from these images can be put to many uses and offer the viewer an opportunity to see information that isn't visible to the naked eye.

 

Lab 7 - Multispectral Analysis

GIS 4035

In this weeks lab we looked at image histograms, how to operate the inquire cursor, interpreting images, utilizing the help function, and interpreting digital data.  When then utilized the skills that we learned in the exercises to properly locate and accentuate a specific location within an image that was provided.  In this case, an image of forest surrounding the Olympic Mountains in Washington State.

The first Figure located was a dark waterbody.  Utilizing near infrared RGB settings to make the water darker, the reader can easily identify the dark waterbodies.  As described in the map the pixel values ranged from 12 and 18 in band 4.  This was observed utilizing the inquire cursor in ERDAS.

The next Figure that I located was the snowcapped mountains.  These features produced pixel values of 200 in the 1-4 band layers.  These features also had a large spike between pixel values 9 and 11 in Bands 5 and 6.  These features can be observed in the image above as yellow.

My final figure was an area of water that layers 1-3 seemed much brighter than normal, with layer 4 become slightly more brighter. Layers 5 and 6 stayed unchanged.  I utilized the band selection to set up 1-3 and then changed the blue band between 5 and 6 to identify the location that the description was illustrating.  In this case the description identified shallow waterbodies that could be seen as a greenish color.

Lab06- Image Enhancement

GIS 4035

In this weeks lab we worked more with the ERDAS program as well as ArcMap.  With the government shutdown we were unable to get into the USGS website to download the Landsat 7 images, but our instructors were kind enough to provide the data to us.  With the data downloaded and extracted we began to perform spatial enhancements.  We utilized Fourier Transformation function as well as Basic Filters found in both ERDAS and ArcMap. 

I felt most of this lab dealt with Convolution Filtering found in the ERDAS program, and we were able to utilize different Kernel settings to see a multitude of outputs based off these settings.  

Finally I was tasked with modifying an image to generate an image that reduced the Scan line corrector failure lines so that they were less  noticeable, but the image still retained enough detail to let the viewer see the obscured image.  This image is shown in the map above.  As is the description of the steps taken to clear up the image as much as possible.

Lab 5a - Intro to ERDAS Imagine

 

GIS 4035

 

 

 

This week I worked with a new program called ERDAS Imagine 2011, as well as learned how to calculate wavelength, frequency, and energy of EMR (Electromagnetic radiation).  With the ERDAS Imagine program I learned how to navigate the basic tools, viewer, and how to add and remove data.  Ultimately we combined the data we had obtained and modified in ERDAS Imagine into ArcMap and the above map is an example of this capability.  In the above map, I show the user multiple classifications, as well as the total acres that the classification covers.

 

The lesson this week was a great opportunity to work with a new program that I have not used yet.  It allowed me to see how the program performed basic functions as well as allowed me to manipulate the attribute table associated with it.  



Lab 04 - Ground Truthing and Accuracy Assessment

 

GIS 4035

 

 

In this weeks lab, I continued with the Pascagoula, Mississippi Land Use/Land Cover map that I created.  The class was to focus in on Truthing, and verifying that the data we surmised last week was true and accurate.  Utilizing Google Street Views I was able to look at sample site locations and determine if the classifications that I determined last week were in fact accurate.  Overall for this sampling I was 70% accurate when comparing last weeks assessments to this weeks samplings of the areas. 

 

In the above map, you can see my sample locations.  Those locations that I found to be of an accurate assessment were colored green.  However, if I looked at a sample location and found that the area represented in the classification was false, I symbolized the dot in a red. 



Lab 3 - LU/LC Classification

GIS 4035

 

 

 

This weeks lab, we looked at Land Use and Land Cover.  The above map of the Pascagoula, Mississippi area was created utilizing an aerial photograph.  Based on that aerial photograph and utilizing the skills we learned in the past two lessons I was tasked with identifying different locations within the photograph and classifying them based on their looks.  I utilized size, color, shape, surrounding features to identify each location.  The Minimum Mapping Units (MMU) that I used on this map was approximately 2.5 hectares (roughly 6 acres).  If something was smaller than this standard it was typically lumped in with the other surrounding classification.

 

This was a time challenging map.  I utilized a lot of time trying to get as much detail as I could into the islands in the marshland area.  I could have cut corners, but in the end, I think it looks better and presents the data in a more professional manner.



Lab 2 - Visual Interpretation

GIS 4035

 

 

 

In this weeks lab and lecture we learned about identifying tone and texture in an aerial photograph.  Above you will see areas that are defined by their tone.  Tones are defined by the brightness or darkness an area displays on an aerial image.  This varies from a very light tone, all the way up to the very dark tones.  Also in the above aerial, I show different textures.  Texture is how rough or smooth a surface looks when viewing the aerial photo.  I have shown a range from very fine texture (water) all the way up to a very rough course texture (housing development).

 

 

 

 

The map above identifies features based on shape/size, shadows, patterns, or associations.  Shape and Size of features is a common way that analysts look at aerial photos and quickly determine what they are looking at.  Roadways, Buildings, Water bodies can all be identified in the photo by the way they look and the size they are relative to their surroundings.  Shadows help show the viewer what may not be clear with an initial viewing of the photograph.  Take for instance the water tower, sign and Utility Pole, all of which can easily be identified on the ground but from the air, may be more difficult.  Shadows help the analyst make a better determination of what is on the ground.  Pattern is also used by analysts to determine what they may be looking at.  Housing developments, Vegetation, and Parking Lots can be looked at and by a pattern show the user what they are looking at.  Finally, through association we can make a determination of what we are looking at.  The end of a major water body and the pier makes it easy to associate a beach to the coastline.  While a pool and building shape, with cars and a parking lot helps the analyst determine a hotel is present.

 





Module 11: Sharing Tools

GIS 4102

 

 

This weeks lab assignment worked with sharing custom tools to others.  The above screenshot is an example of a custom tool that was created to generate random points within a feature class no closer than a specified distance.  The points that were generated were then given buffers as defined by the tool.  All the results were then exported out to a specified destination folder. 

 

Overall, the custom tools section of this class has just been very rewarding to me.  I find that the ability to create custom tools and then share them to others is a huge benefit to me in my line of work.  I also like that passwords can be assigned to these tools that they can only be edited and exported by those that know the passkey.  

Module 10 - Creating Custom Tools

GIS 4102

 

 

This week I learned about creating custom tools from python scripts.  This by far was the most interesting module that I have done.  This module seemed to tie everything together for me and allowed me to understand how I can use these scripts in my workplace.  The above screenshot is of the tool dialog box that I created by defining parameters.  This will allow the user of my tool to type in the data they wish to manipulate, as well as define where that information is stored.  This MultiClip script will allow the user to specify a single feature as the clip boundary, and then select multiple features to clip from.  All of the results are then saved to the Results folder with a unique name that is generated by the tool based off of the clip feature and the feature being clipped.

 

 

 

The above screen shot is the results of a successful run of the tool once the script was modified from its original format.  Here we can see in the Process Summary box messages that the scripts author wanted the user to see.

 

Overall, I enjoyed this module and can't wait to use it in my place of employment.



Participation #2

 GIS 4102

NFL KICKOFF TO YOUTH FOOTBALL ANALYSIS

 

From 2001 to 2006 youth football in the US increased significantly in regards to participation.  This drew the attention of the National Football League (NFL).  The NFL teamed up with USA Football and the National Recreation and Parks Association (NRPA) to conduct a study identifying the reasons for the increased participation as well as where the NFL could focus funds for improvement.

A technical team was formed to conduct the study utilizing ArcGIS.  Several software tools and programs were used following the Geo-Referenced Amenities Standards Process (GRASP).  The parks and recreation industry has utilized this methodology for many years to gather, manage, analyze, and present information.

Nationwide surveys were conducted and the data was compiled.  A primary database was created from these surveys to be analyzed utilizing GIS.  Due to the large study area, the technical team decided to utilize ESRI’s “StreetMap USA” as a basemap.  To generate reports, tables, and analytic results, the team utilized Python.  Python allowed the team to automate the data processing for this large-scale project with ease.

With the matrix of data that was created, collected, and analyzed through GIS, the NFL will be able to better assess where monies and materials will be best utilized.

Source:  http://www.esri.com/news/arcnews/summer08articles/nfl-puts-gis.html

Module 9 - Debugging and Error Handling

GIS 4102

 

This weeks assignment we worked on debugging existing scripts and error handling.  In the above screenshot you will see the results of a script that was originally given to me in with multiple errors.  I was tasked to correct the script and the errors that I found to produce the results you see.  This lab was a bit more challenging for me.  the status bar and error reporting in the interactive window was a huge help in isolating and fixing the errors.

 

In the above screenshot I was again asked to troubleshoot a script that was given to me.  Here I found that several of the errors were found simply by reading through the script and finding misspelled words as well as simple code errors.  I did utilize the debugger tool, but found most of my errors when I ran the program and read the error report in the interactive window.

 

It took a while for me to read through the script and understand exactly what it was trying to do.  I still feel I need to get a better understanding of for loops as well as if then statements. Perhaps a bit more reading and continual use will help me in the process. 



Module 7 - Geometries and Rasters

GIS 4102

 

 

 

PART 1.

 

The above screenshot contains a notepad text file.  It was created using Python and the use of a nested "for" loop.  Using a SearchCursor I was able to identify a polyline object and then using the nested "for" loop extract the information I needed from the feature object.  The arrays within the feature contained multiple points or vertices that are identified above.  Each point has it's coordinates (X, Y) values shown as well as the NAME field from the rivers shapefile that was used.

 

 

PART 2.

 

The above screenshot shows the final result of a raster tiff file that was created working with the elevation and landcover raster files.  Utilizing Spatial Analysis I was able to modify the Forest landcover raster and identify Slopes between 5 and 20 degrees, as well as Aspects between 150 and 270 degrees.  Once all these variables were isolated and identified I utilized a map algebra operator (Boolean "And" function) to classify the combined rasters.  The final raster image is shown above.

 

This module was very robust and covered a lot of data that dealt with nested loops as well as spatial analysis of raster files.  I enjoyed the challenge of this assignment.

 





Module 6: Working Spatial Data

Week 7 - Module 6 - Working Spatial Data

GIS 4102

 

 

 

In this weeks module, we were focusing on working with spatial data.  There was a lot to cover, and it was enjoyable learning about functionality available in Python to accomplish different tasks. I discovered how to utilize lists, tuples, directories, as well as different cursors to manipulate and show data to the end user. 

 

The above screenshot was the results of the script I have written.  This script creates a Geodatabase named JBG16.  It then copies all the shapefiles from the Data directory into the newly created GeoDatabase.  Once copied the cities feature class is searched using a search cursor that gathers and populates a directory named countySeats with the NAME and POP_2000 values. Finally, those results are then printed for the user.

 

Overall, this was the most challenging of all the projects I have done.  I ran into a syntax error that kept me busy for a while, but ultimately was able to discover the problem through script troubleshooting.  Who knew the addition of the letter s at the end of a value could keep me busy for over an hour...



Week 5/6 - Python GeoProcessing

GIS 4102

 

Week 5 - Review

 

Week 6 - Module 5 - Python GeoProcessing

 

This week we worked with Python Script and Geoprocessing.  The screenshot above was taken after a series of code was run to Add XY Coordinates to the hospitals shapefile, then create a 1000 meter buffer around the hospital locations, and finally Dissolve the buffers created into a single feature.  All three of these tasks were completed using python script.  The results were then printed in the interactive window to show that the tools completed their parameters successfully.

 

I can see how a python code can be written to complete routine series of tasks and all that would need to be modified is a few parameters.  I also discovered that using code that was previously written saves both time and cuts down on syntax errors.

 

Overall I definitely am coming away with something that I can use in my current position, and look forward to further growth in Python Script.



Week 4 - Participation 1

GIS 4102

 

GIS can be used in a number of different ways.  The Town of Mooresville, North Carolina utilized GIS to assist them with a stinky situation.  In 2010 the town discovered they were having a problem with an increasing number of overflows and stoppages in their Sanitary Sewer System.

The Mooresville Water/Sewer Maintenance Department (WSMD) reached out to their Engineering Department for a solution to meet the requirement set by the North Carolina Department of Environment and Natural Resources.  This requirement involved the cataloging of the cleaning and maintenance of all sewer lines on a regular basis to identify troubled areas.  Cataloging their findings in Excel spreadsheets, the WSMD logged the cleaning data for the entire month and dates for when the sewer features were cleaned.  They gave each manhole a unique identifier to associate it with a matching manhole on the GIS map.

Then utilizing Python scripting, they were able to simplify the repetition of the steps required to create the cleaning data.  Python script was made available to all ArcGIS users to do analysis on the data which allowed them to determine the number of sewer mains cleaned as well as the total lengths.

The analytical data that was collected was then used to determine “hot spots” that were cleaned seven or more times in the previous year.  This allowed the WSMD staff to work with other departments to isolate and monitor locations that were repeatedly cleaned.  Overall the WSMD saw an increase in productivity by 26% and a decrease of stoppages in gravity main lines throughout town.  This in turn, through the use of technology and teamwork, has saved the WSMD money as well as cut down on overtime.

Town Shapens Proactive Sewer System Management
By Alan Saine, Civil Engineer, Town of Mooresville, North Carolina
ArcNews Fall 2012



Week 4 - Python Fundamentals II

GIS 4102

 

 

 

This weeks exercises and lab assignments reinforced the use of modules, writing conditional statements, using loop structures, correcting script errors, as well as how to write comments within scripts to help with readability and descriptions.

 

The above results are from this weeks lab assignment where I worked with a script to play a dice game.  The dice game was then followed by a sequential numbering from 0 to 5 utilizing a while loop.  The dice game script itself was provided to me and I was asked to use it as a method to reinforce my ability to identify and correct errors in scripts.  I utilized both my own knowledge of script writing, and the check feature provided to me in the Python Win software application.

 

Overall this weeks lab helped build a strong foundation for my Python skills to improve upon.



Week 3 - Python Fundamentals I

GIS 4102

 

This week the class looked closely at the foundation and building blocks of Python script.  We looked at using variables, strings, lists, functions, methods, math equations, as well as conditional statements.

 

The screenshot above is the results of a python script that I wrote.  In the script I was tasked with identifying my full name, breaking down that full name string into a list, identifying my last name from that list, and printing the result.  From there the script went on to identify how many characters made up my last name and multiplied that by the value of 3.  The script then printed the results of that equation.

 

The results were:

 

Griswold

24

 

This was a great opportunity to utilize all the Python features we have learned up to this point.  I am excited to see what is next.

 

Week 2 - Geoprocessing in Arc

GIS 4102

 

 

 

This week we worked on ModelBuilder and the functionality of it within ArcGIS.  We also exported Python script from ModelBuilder as well.  These functions were saved within Toolboxes and then compressed to be shared with others.

 

In the above image, I utilized data provided to create a model that would select all the soils that were considered "Not Prime Farmland" and with those results erase portions of the basin shapefile so that the remaining shape excluded those areas identified as "Not Prime Farmland". 

 

Week 2 really expanded my knowledge on ModelBuilder and the capabilities it has within ArcGIS to allow me to return results.  It also gave me my first opportunity to create a working GIS script and generate output from geoprocessing tools.



Intro to Python - Week 1
GIS 4102
 

 

 

The first week of the summer semester at UWF begins with my introduction to Python.  Python is both a scripting language as well as a programming language; however for this class we will be focusing in on the scripting aspect of things.  Our first module provided me with a script that can seen in the screenshot above.  Its results can be seen on top of the scripting window and after being run, created a series of folders that we will be utilizing in the GIS Programming course this semester. 

 

With the script loaded I ran it by clicking on the running man icon, although I could have pressed ctrl-r or browsed to the function by going to File and selecting Run.  The process ran and created the desired output.  In the interactive window I saw that the script was completed as it displayed a text message saying "Process Complete"

 

The use of hotkeys can also speed up the process of writing script.  I am going to make a concerted effort to identify commonly used feature hotkeys for the Python window interfaces used in this semester.

Final Project

GIS 4043/L

 

 

 

For our final project in the Intro to GIS Class I was tasked with taking on the role of a GIS analyst working with Florida Power and Light (FPL).  The task was to analyze and determine a number of factors in regards to the Bobwhite-Manatee Transmission Line Project.  Among these analyses was to determine the environmental impact, parcel and homes affected as well as schools and daycare centers.  Finally we were also tasked with identifying the length of the preferred corridor and providing a cost analysis.  The following links are to the presentation as well as the slide by slide commentary.

 

 

Presentation 

 

Step by Step Commentary

 

 

 



Final Project

GIS 3015

 

 

For my final project I was tasked with creating a map for the Washington Post which would highlight ACT scores as well as the overall participation per state.  In the above map, I utilized a Choropleth Map with color density to show the level of participation from state to state.  This was accomplished using a Natural Breaks Jenks Classification.  I then utilized an Equal Interval to show the Mean Composite scores for the ACT from state to state, symbolized by a proportional symbol based off the score.  



Week 13 - Georeferencing

 

GIS 4043L

 

 

This week's lab introduced me to Georeferencing, Editing, as well as ArcScene.  The above map was created in ArcMap and shows the buildings, roadways, and aerial images associated to UWF campus.  I was tasked with Georeferencing the aerial images using common points (anchor points) that rubbersheeted the aerial image to the existing shapes of the buildings layer.  Here I also learned about RMS Errors (RMSE) and how to determine if they fall within norms.  I also used the editor tools and created new features.  The UWF Gym and Campus Lane roadway were added to the appropriate layers and attributes assigned to them.  Finally I worked with the multiple ring buffer tool, which allowed me to create a conservation easement around the eagle's nest.

 

 

 

I was also introduced to ArcScene this week which allowed me to utilize 3D modeling for creating maps.  The above map was originally created in ArcScene and the image exported for 2D use in ArcMap.  Here I can also display the new Gym as well as the new Campus Lane roadway that was added earlier in the lab.

 

Overall this lab was very informative and fun to do. 

 

 





Week 13 - Google Earth

GIS 3015

 

 

 

This weeks module introduced the class to Google Earth and how to import both vector and raster layers within the program.  KML and KMZ files were discussed and I had the opportunity to work directly with creating and importing both.  We also took a comprehensive look into how to do a tour of areas within Google Earth while utilizing the Population Dot Density Map that I created in the previous module.  Above, you will see a screenshot of what the map looks like while overlayed on top of the Google Earth program.

 

This week's lab was quite interesting and I look forward to using the skills I obtained here and apply them to my workplace.

Week 12 - Dot Density Mapping

GIS 3015

 

 

This weeks lab involved population density and how to display it through a dot map.  This project was done entirely in ArcGIS and allowed me to take on some artistic challanges.  Utilizing ArcGIS I was able to display dots representing 1 to 25000 population and place the symbology on urban areas thoughout Southern Florida.  Also displayed in the map are Surface Water features which give the reader a better idea of why there may be little urban development and population density in that area.

 

Overall, this lab allowed me the ability to see how to use dot maps to deliver information to the reader.



Week 12 - Geocoding & ModelBuilder

GIS 4043 L

 

 

This week the lab focused on Geocoding and Modelbuilder.  The map above was created in the Geocoding part of the lab.  In it we were provided an excel document with locations of EMS facilities found in Lake County, Florida.  Using an identifier tool we were able to associate those locations with spatial locations based off the address.  Later we utilized this information to build routes based off of stops within a network.  Above is the map that I created showing two stop locations (essentially a pickup and drop-off location) and with GIS was able to compute the fastest/shortest route to the stops in sequence. 

 

We also worked seperately on an ESRI Exercise: Explore an existing model.  This exercise walked us through the building of a simple data model that automated tasks in GIS to spead up productivity and effeciency.



Week 11 - Flow Line Mapping

GIS 3015

 

This week we worked with Adobe Illustrator to create and show content with Flow Lines.  Above is the 2007 Immigration Statistics from the Department of Homeland Security.  This map is intended to show the flow of immigrants into the U.S. as well as report the percent of total immigrants per state, utilizing a choropleth map of the United States. 

This week we also looked at Effects.  Above we can see in the map the utilization of Drop Shadows, Inner Glow Effects, as well as 3D Extrude and Bevel Effects.  Overall this was a fun project and I would welcome more time to work with the effects to become better at them.



Week 10-11 - Vectors Analysis 3

GIS 4043 L

 

 

 

This week's lab had us create a map of Possible Camp Site Locations with specific criteria.  I utilized several overlay tools within the Arc Toolbox to get the desired results. Some of the tools focused on this week were Union, Intersect, Erase, and Buffer.  With the Buffer tool I also learned how to work with ArcPy and do scripting for desired results.  As this was my first time working with ArcPy I found it very interesting and enjoyable to work with.  I found when trying to repeat the same tool several times ArcPy was a great tool to save time. We also used select by attribute tools to analyse our data to retrieve the desired results.

 

For the map design I tried to utilize a color scheme associated with the desired audience.   I found the green and tan (canvas) color very appealing to the eye.  Inially it looked a little too green on the screen, but after printing out the map I found that the layout actually looked quite good. 



Week 9 - Isometric Mapping

GIS 3015

 

 

This week I continued with Adobe Illustrator and worked specifically with the Pen and Pencil tools as I demonstrated Isometric Mapping.  The map above is an example of isohyet lines, which is the representation of areas of equal precipitation, in this case the state of Georgia.  This week's lab also had me create a legend, north arrow as well as other labels from the tools offered in Adobe Illustrator.

My hope is that the reader of the map above will be able to walk away with a clear understanding of precipitation amounts for areas throughout Georgia and more specifically see where there are changes in the amounts of precipitation.



Week 8 - Proportional Symbols

GIS 3015

This week's lab consisted of working with Proportional Symbols.  Above I show a map created solely in ArcGIS and although informative, ArcGIS was unable to manipulate the data in a more user friendly capacity.  I was able to get my point across to the reader, but in the end I wished I had more flexibility in the program.

Here we have a map created using a combination of ArcGIS and polished in Adobe Illustrator.  I was able to use data collected from independent sources to better reflect the symbology in the map.  I modified the size to be proportionate to the actual data it was intended to display.  The reader should be able to quickly identify where wine consumption was greatest in Western Europe.

Overall this project was a fun and useful exercise.  I learned how to label along a path (circle), as well as how to proportionally size symbology to reflect the visual representation of the data.

Week 7/8 - Data Search

 

GIS 4043 L

 

 

This week we were tasked with data searching with a focus on displaying all the data that we compiled.  With this project we also wanted to provide all the data in the same projected coordinate system, in this case UTM 17 N.  Above is the completed map for this project.  I approached this project with the desire to tell a story.  Here we have the environmental concerns for the areas in and around Tooke Lake found in Hernando County Florida, specifically a focus on local bear habits and invasive plantlife.  The reader of this map should come away with a variety of information pertaining to Tooke Lake and it's surroundings, along with the environmental concerns that they might have.  As a mid term project this allowed me to utilize all the skills that I have been taught to this point.    

Participation Assignment #1

Group 3

Oceania

The UNESCO World Heritage List is comprised of sites considered to have outstanding universal value. The sites are chosen due to their cultural and natural heritage. The following map gallery was created to share some of the World Heritage sites for the Asia/Oceania zone. There are ten sites mapped including: archaeological sites, marine protected areas, diverse landscapes, protected wildlife zones, and unique geological formations. The maps were created using ArcGIS online. Included with the maps, visitors will find links to additional interesting information about the sites. This map gallery can be accessed at: http://goo.gl/fl0JN

This map gallery should not be considered a comprehensive review of the UNESCO World Heritage sites in Oceania. Rather, it should be viewed as a compilation of some of the interesting sites within that area. For more detailed and expansive information, one should view the UNESCO World Heritage list: one of the main resources used in building this map gallery. We sincerely hope you enjoy it.

Resource List

There are two internet sites which were commonly used to research location and information related to each of the World Heritage sites in this exercise.

1. Wikipedia; World Heritage Site: http://en.wikipedia.org/wiki/World_Heritage_Site
   World Heritage Site is a place (such as a forest, mountain, lake, desert, monument, building, complex, or city) that is listed by the UNESCO as of special cultural or physical significance.
2. UNESCO; World Heritage List: http://whc.unesco.org/en/list/
   The World Heritage List includes 962 properties forming part of the cultural and natural heritage which the World Heritage Committee considers as having outstanding universal value.

The following sites/resources were valuable in locating and gathering information on each of the individual site.

1. World Heritage Site: Tongariro National Park
• New Zealand Department of Conservation; Tongariro National Park: http://www.doc.govt.nz/parks-and-recreation/national-parks/tongariro/
• Established in 1887, Tongariro was the first national park in New Zealand and the fourth in the world.
2. World Heritage Site Macquarie Island - Tasmania - Australia
   • Australian Antarctic Division: www.aad.gov.au/default.asp?casid=7151
   • This site provides location and historical information about Marquarie Island
3. World Heritage Site: East Rennell
   • UNESCO: http://whc.unesco.org/en/list/854/
   • This site provides information including maps, description, documents and a gallery of photos
4. World Heritage Site: Phoenix Islands Protected Area (PIPA)
   • UNESCO: http://whc.unesco.org/en/list/1325/
   • This site provides information including maps, description, documents and a gallery of photos
5. World Heritage Site: Uluru-Kata Tjuta National Park - Ayers Rock
   • UNESCO: http://whc.unesco.org/en/list/447
   • This site provides information including maps, description, documents and a gallery of photos
6. World Heritage Site: The Royal Exhibition Building and Carlton Gardens
   • Museum Victoria; Royal Exhibition Building: http://museumvictoria.com.au/reb
   • This site provides a description, directions, scheduled upcoming events for the Royal Exhibition Building and Carlton Garden
7. World Heritage Site: Tasmanian Wilderness/Mount Field National Park
   • Tasmanian Parks and Wildlife Service; Mount Field:
     http://www.parks.tas.gov.au/index.aspx?base=3589
   • Tasmanian Parks and wildlife service site providing an overview of the park its animal and plant life, as well as access information.
8. World Heritage site: Kuk Early Agricultural Site
   • UNESCO: http://whc.unesco.org/en/list/887
   • This site provides information including maps, description, documents and a gallery of photos
9. World Heritage Site: Te Wahipounamu
   • UNESCO: http://whc.unesco.org/en/list/551
   • This site provides information including maps, description, documents and a gallery of photos
10. World Heritage Site: Bikini Atoll Nuclear Test site; Marshall Islands
    • UNESCO: http://whc.unesco.org/en/list/1339
    • This site provides information including maps, description, documents and a gallery of photos 

Week 7 - Choropleth Mapping

GIS 3015

 

 

In the above choropleth map I utilized Natural Breaks classification in order to show the percent changes in the U.S. Population Growth from 1990 to 2000.  This project was done initially using ArcGIS and later modified within Adobe Illustrator to move items around and make the map more presentable.

 

 

 

 

In the above choropleth map I utilized Adobe Illustrator to modify the original map to be grayscale.  Then using an excel spreadsheet I calculated the percent change in each Division.  Analyzing the percent change, I chose Equal Interval classification to assign a color (grayscale) scheme to my map.  The intervals were 5.52 (rounded to nearest tenths value in legend), with one outlier.  Displaying this data using this classification method was the most practical.



Week 6 - Typography

GIS 3015

This week we took on the task of Labeling.  More specifically we learned how to use the Typography Floating Palette in Adobe Illustrator.  In this lab we were given a list of locations, around Marathon Florida in the Florida Keys, and tasked with labeling those locations on the Map.   The map above is the result of taking everything we learned this week in Typography and putting it into practice.  Font, font size, color, stroke, and font style all played a role in delivering a useful map to the reader.  With the above map, a reader should be able to find the highlighted Cities, Parks, and City Features around Marathon Florida quite easily.

Week 6 - Projections Part II

 

GIS 4043 L

 

 



 

In my opinion this has been one of the most time consuming, yet beneficial labs that I have done so far in the course.  This lab was all about the Projections.  I defined Projected Coordinate Systems, as well as, re-projected other already defined Projected Coordinate Systems.  I also worked with Excel files and learned how to bring tables that contained Longitude and Latitude coordinates in degrees, minutes, and seconds into GIS utilizing the Add XY data feature in ArcMap.  The map above shows the NorthEast part of Escambia County.  In it you will see several layers that I downloaded and manipulated to have all the data projected as the same Projected Coordinate System.  The Petroleum Storage Tanks were initally an Excel file with locations defined by Longitude and Latitude.  When completed, the Excel file is now a shapefile in which data can be added and manipulated.  

Week 5 - Map Composition

GIS 3015

For Week 5 in Cartographic Skills we looked at Map Composition and organization.  The focus was on the percentage of Hispanic population in Southern Florida.  The above map highlights these areas utilizing a monochrome color scheme from a lighter shade to a darker shade.  The goal in this is to allow the reader to easily recognize Hispanic population density.  Also utilizing feature-ground techniques I applied a lighter shade to the background.  This in turn caused the focus of the map to be accentuated. 

Adobe Illustrator was utilized entirely for this project and in this lesson we learned more about the AI program and the features and tools that are available to the user.  Primarily we learned about the different ways to change colors within AI.

Week 5 - Projections Part 1

GIS 4043 L

This week we discussed Projections.  The above map "Analysis of Florida Projections" was created to highlight to differences in projected coordinate systems.  Looking at the legend you can see the area in square miles for each county specified.  Depending upon the type of coordinate system used the county area is skewed and therefore displays a different area.  The Albers map above is the best coordinate system to use when analyzing the entire state of Florida.  The UTM projected coordinate system bisects the state of Florida, and areas farther East and West of the center will be more distorted.  Whereas, with the State Plane North projected coordinate system, the distortions will be greater further to the south of the state, such as Miami-Dade County due to its distance from the panhandle.  

This week we also discussed the difference between the Project tool and the Define Projection tool.  The differences between these two tools should not be overlooked.

Week 4 - Intro to Illustrator

GIS 3015

This week in my Cartography Skills class we were introduced to Adobe Illustrator.  From what I have seen, visually Adobe Illustrator takes Cartography / Map making to the next level.  Although the ESRI program ArcMap is very robust, it does lack some of the artwork that Adobe Illustrator can provide.  This week's class introduced us to some of the basic functions of AI and taught us how to save MXD files as an AI file and open them in Adobe Illustrator to manipulate them further.  This week we focused on familiarizing ourselves with the Workspace and some of the tools provided there.  We used shape tools, line tools, text tools and layer palettes all in order to present a final map in a more aesthetically pleasing way.  The above map shows the cities, and county boundaries for Florida.  Using Adobe Illustrator we grouped objects together that would allow them to be manipulated and resized all while maintaining their relative positions.

Week 4 - ArcGIS Online and Map Packages

GIS 4043 L

This week we were introduced to ESRI ArcGIS Online and Map Packages.  I was actually fortunate enough already to have an ESRI global account as I maintain my department's ArcGIS licensing.  I did not however have that global account registered to use ArcGIS online.  Once all my accounts were set up and working properly I walked through both the "Authoring Web Maps Using ArcGIS Online" and "Creating and Sharing Map Packages (for ArcGIS 10.1)" from ESRI's Training sessions.  These seminars/training exercises were great!  By the end of training I was able to create group layers, display the same layers in different scale ranges, create map packages, and share map packages making them available to others quickly and easily.  I also went the extra mile and put together a web map for my department.  My supervisor was highly impressed with the demonstration that I showed him, and has set up a meeting with the Township Engineer, OEM Supervisor, as well as the Public Works Director next week.  There I will demonstrate how Web Mapping can be utilized in a crisis event, and open the discussion for future use.  Want to see?  Search for the map "Bernards Township Road Closures during Sandy" at www.arcgis.com/home ... (or I can just attach it for you below)  Keep in mind it's a really rough draft that I threw together in just a few minutes for demonstration purposes.   I just want to show some of the features that are available.

View Larger Map

Week 3 - Data Classification
GIS 3015 L

In this week's lab for Cartographic Skills we delved into Data Classification.  Above you will see a map of Escambia County Florida, which highlights the percentage of Blacks found within the US Census tracts.  We were tasked with highlighting four different classification methods utilizing the same data from the Census.  Utilizing ArcGIS I modified the symbology to reflect the Graduated Colors style found in the Quantities symbology.  Here I was able to modify the different classifications that the Quantities symbology uses.  Doing this I highlight the different ways that data can be shown.  Even though the data has remained constant, the way the data is reflected on the map can visually show a different result.

Also in this week's lab we were asked to isolate which map we thought reflected the data best.  I chose the Natural Breaks classification method.  I feel that this classification method better allows the reader to understand the information and does not leave gaps within the legend that may be confusing to some readers.  I also felt the other classifications did not reflect the data as I thought it should be reflected.  I felt anyone reading this map will be able to quickly determine the percentage of blacks within a tract, and this is the ultimate goal of the map.

Week 3 - Cartography

GIS 4043 L

Population of Mexican States - The map above highlights the different states of Mexico and identifies the estimated population of each state.

Central Mexico: Transportation and Urban Areas - In this map I identified all the major and primary rivers found throughout Central Mexico.  Also identified are the federal roadways and rail lines.  This map also highlights the urban areas found throughout Central Mexico.  The inset was added to allow the reader to orient themselves to the location that is the focus.

Mexico: Elevations - This map utilized stretched symbology to highlight the elevations of Mexico.  A Digital Elevation Model was used to show the elevations.  Modifying the DEM symbology allowed me to display the elevation in an appealing manner.