GIS 4930 Final Group Poster

Here is our final Group Poster that we created as a team

http://students.uwf.edu/dj11/Group2PosterFinal.pptx

And here is a screenshot if that link is broken:

And here is the research that I contributed to the project:

http://students.uwf.edu/dj11/DRJ_SkyTruth_Report_PS.docx


I was lucky to work with a great team and under the leadership of Ray, I think we compiled a great poster.

SkyTruth - Analyze Week

This week we continued our work on our Mountaintop Removal project for SkyTruth.  Our goal this week was to clean up the data by setting the following parameters:

To be considered as an MTR area it must:
1. Be larger than 40 acres
2. Must be farther than 50 meters from roads and rivers
3. Must be farther than 400 meters from Major Rivers and Highways
4. Must Intersect with Mountain Ridges

In order to complete this phase of the project, we had to use several ArcGIS Tools and techniques including:

• Raster to Polygon tool
• Various Selects (By Location and Attribute)
• Feature buffering
• Overlay erasing
• Multipart to SinglePart conversion
• Calculate Geometry
• Creating Random Points
• Data Editing
• Accuracy Checking
• Packaging and Delivery

So in a pretty compact lab, we really got to showcase some of the tools we have been learning not only in this class, but the other classes as well in our UWF curriculum.

SkyTruth - Prepare Week

This week's assignment involved a few tasks to help analyze an area to determine where Mountain Top Removal Mining might be taking place.   This data would be used by SkyTruth.org to empower environmental activism.

Some of the skills needed for this project included:

• Combining Landsat bands to get a multi-band image
• performing unsupervised classification using ERDAS Imagine
• Classifying images of different spectral values
• Manually reclassifying and recoding imagery in ArcMap

It is important to note that this is a multi-week project, so a lot of the "noise" that you see around rivers and roads in this first pass of the analysis will be eliminated in future steps by buffering them out.

Data Sharing Issues

Some common problems in the sharing of GIS data among individuals and organizations include:
·         Silo vs. Enterprise approaches
·         Free vs. Fee Base information sharing
·         Data Gatekeepers vs. Data Access Facilitators
·         Agency Needs vs. Surrounding Entities
·         Data Sharing Agreements vs. informal arrangements
·         Outsource GIS Data Sharing Functions vs. In-House
·         Data Standards
·         Quality of Shared Data

(These are all paraphrased from the URISA article here: http://www.urisa.org/files/Issues%20in%20GIS%20data%20sharing.pdf )

From a real world perspective, some of the problems I have witnessed when it comes to sharing data include:

·         Storage Issues – Some of the data can be very large and this requires external hard drives to be swapped by agencies.   Sometimes it is hard to remember whose drive you have sitting on your desk if you don’t label everything properly.

·         User Levels – We may work from everyone from the non GIS user all the way up to USGS experts in a single day.   You have to be able to deal with different skill levels from the people that you work with.

·         Tools – Not everyone has the same version of ESRI ArcGIS software that we have.   You have to be able to distribute the shared data in alternate formats (KML, XML, and even printed copies if that is all their skill set will allow)

·         Repeat Requests – Our GIS staff would repeatedly get requests for the same data from separate parties.   This called for the creation of a basic GIS library available from our web site which contains these files for download.   You can see this site here:   http://www.srwmd.state.fl.us/index.aspx?NID=319

·         Disclaimers – Whenever working with data that is shared with the public, it is important to provide disclaimers about how the data should (and should not be used).    For example there was some confusion with terms like (100 year flood event).   People thought that meant the event would only happen once every 100 years, so if an event happened 3 years ago, they were in the clear for 97 more years.   This simply wasn’t the case.    Like a lot of things, managing expectations is a priority.

 

LiDAR & Hydro - Report Week

Description of Data:

This MXD contains two important aspects.   The DJ_Group2_Stream feature was calculated using a DEM and the ArcHydro Tools (Fill, Flow Direction, Flow Accumulation, Con, and Stream to Feature).   The DH_Group2_basin data goes one step farther to run the "Basin" tool to delineate drainage areas in the raster.

In the zip file you will find:

• DRJ_Group2_Deliverable.mxd - An ArcGIS Map
• DJ_Group2_GeoDB.gdb - A File Geodatabase conatining key data for the project

The MXD will contain 2 Layers that display the data from the GeoDatabase:

• DJ_Group2_stream - Stream files created using ArcHydro Tools in ArcGIS
• DJ_Group2_basic - Basin files created using ArcHydro Tools in ArcGIS

Data Location:

Here is a link to my files for this week's Lab Data:

               Zipped Copy of Lab Files

Data Instructions:

In order to use the data on your computer, you will need to take the following steps:
1.  Make sure you have ArcGIS 10.1 (or newer) on your computer
2. Download the zip file
3. Unzip the file into its own directory such as    c:\MyFiles\
4. Open the MXD file in ArcGIS

Notes of Interest:
On this assignment, we had a couple of students have trouble with the CON tool.   I did some research and found an article that explained that it could be a problem using an underscore in the naming convention of the Input Raster.    This tip seemed to help several classmates and it felt really good to help one another in that instance.

GIS 4930 - LiDAR & Hydro - Analyze Week

Here is my map for this week's assignment which used ArcGIS Hydrology tools to determine where streams and rivers are found in our study area.

GIS 4930 - LiDAR and Hydro - Prepare Week

Here are my results from the Lidar and Hydrology Prepare Week Lab for GIS4930. 

 

First up is a 2D Profile of a hillside in the Charleston WV area.   The different colors represent different elevations:

 

 

 

Next up we can see a 3D view of roughly the same area.  This was created with the LAS Dataset 3D View tool in ArcGIS.    

 

 

 

Last we can see a map of the general area that is using a Raster created from LIDAR.   This particular map used the LAS Dataset to raster tool with the minimum elevation selected for the cell assignment.   This gives a close approximation of bare earth terrain.

 

GIS 4930 - Web Applications - Report Week

GIS 4930 - Web Applications - Report Week

This week, we wrapped up the last 2 projects (Web Applications) into several useful Tools.

These include, and embedded presentation:



View Larger Map

Be sure to "View Larger Map" when looking at this.

And an Online Web Application:    Online Web Application


And if the text labels look unruly, you can also see this in Explorer mode by using this link:

http://www.arcgis.com/explorer/?open=a4d1a2efdbcd4bc4b10701359d307d2d&extent=-13631325.3718604,4540931.16891003,-13625480.3073334,4544564.4876053


This project involved using tools in ArcGIS.COM's suite of tools.  These include ArcGIS Explorer Online and the ArcGIS.COM Map Viewer.    It also involved using a shared Google Doc for a CSV file.

Project 3: Web Applications - Analyze Week

Project 3: Web Applications - Analyze Week

Here is my interactive map for Bicyclist and pedestrian safety in the San Francisco area.   You can see Google Street views when you click on a Bike Rack Location.    You can also edit the Bike Rack List by editing this document :   Link to editable Document     You can also view the legend, change the basemap, or search for an address.


View Larger Map

Web Applications - Lecture Assignment

Web Applications - Lecture Assignment

The interactive map I chose to highlight is the campus map of my Alma Mater FSU.

The map can be seen here:  http://map.campus.fsu.edu/index.aspx

What I like about it:

• Much more efficient than the way I had to navigate the campus oh so many years ago as an incoming freshman.   We would walk around the campus with our fold-out maps looking like quite the tourist.
• Multiple levels of zoom with "rollup" detail
• Street View enabled
• Ability to show bus routes and dining options
• Good links to useful external related sites

I imagine the incoming Freshman now walks around the campus with their iPads and this map (still looking like a tourist, but a modern tourist!)

Web Applications - Prepare Week

Web Applications - Prepare Week

This week we looked into some of the Online tools that ESRI offers for GIS.   I personally think these are the future of GIS as they allow interactive information sharing with members of the public that don't have special GIS software.

In this map you can see an Evacuation Zone and a route from Tampa General to Tampa Memorial.   You also see push pins that you can click to see more information about the hospitals.   You can also pan, zoom, change base map, and even find an address.


View Larger Map

Network Analyst - Report Week

Network Analyst - Report Week

Here are my two favorite maps from this week's assignment.    They are both driving directions broken out to multiple parts.  Their purpose is to direct staff to shelters.   There is also an extent overview on both which shows the footprints of the maps.

Project 2 : Network Analyst - Analyze Week

Project 2 : Network Analyst - Analyze Week

In this week's assignment, we used Project Analyst to create multiple routes based on emergency conditions.   We also created service areas that would let Tampa Bay residents know which shelter they should use in the case of a hurricane.

Here is my map for this week:

Network Analyst - Prepare Week

Network Analyst - Prepare Week

Here is my base map that I created for this week's assignment.   This map will be used for follow up studies of the Network Analyst tools in order to help prepare and evacuation route for the Tampa area in the event of a hurricane.   Based on the ESRI samples I looked through while preparing for this assignment, I can tell that I will really enjoy the Network Analyst tools.

GIS 4930 Project 1 - Statistical Analysis with ArcGIS

For our first project of this new semester, we will be looking for information to help law enforcement determine potential hotspots for meth activities.

Or task this week was to create our Base Map of the Study Area, as well as generate outrIntroduction/Background information.   We also had to do a Process Summary and provide the results of that work. 

Here is my base map:

Here is Section 3 of my Process Summary:

Prepping the Census Data: Programming with Python
Include notes in this section about how and why to prepare your script in python.
1) Added the CensusTracts data to a new MXD
2) Opened the attribute table
3) Added field pcntPopGro as Float
4)  Used the field calculator to set this to (( [POP2010] - [POP2000]) / [POP2000]) * 100
5) Added field pcntWhite as float and used field calculator to set it to ( [WHITE] / ( [WHITE]+ [BLACK]+ [AMERI_ES]+ [ASIAN]+ [HAWN_PI] + [OTHER] + [MULT_RACE] + [HISPANIC])) * 100
6) Added field Roomates as float ans set to be( [HOUSEHOLDS] - [HSEHLD_1_M] - [HSEHLD_1_F] - [MARHH_CHD] - [MARHH_NO_C] - [MHH_CHILD] - [FHH_CHILD])
7) Next we opened up the AddCalcFieldsShell.py script in IDLE
8) Set my workspace to point to S:\GIS4930-GISSpecialTopics\Project1\Project1Data.gdb so the whole line is :   env.workspace = r'S:\GIS4930-GISSpecialTopics\Project1\Project1Data.gdb'
9) Prepared the last 5 lines as follows:
# pcnt40_49
arcpy.CalculateField_management(censusFC,"pcnt40_49","([AGE_40_49]/[POP2000])*100", "VB")
# pcnt50_64
arcpy.CalculateField_management(censusFC,"pcnt50_64","([AGE_50_64]/[POP2000])*100", "VB")
# pcnt65_UP
arcpy.CalculateField_management(censusFC,"pcnt65_UP","([AGE_65_UP]/[POP2000])*100", "VB")
# M_F_Ratio
arcpy.CalculateField_management(censusFC,"M_F_Ratio","([MALES]/[FEMALES])", "VB")
# pcntUnEdu
arcpy.CalculateField_management(censusFC,"pcntUnEdu","([NotHSGrad]/[EduPop]) * 100", "VB")
10) Saved the MXD, closed ArcGIS and ArcCatalog then ran the script.
11) I had one typo in my script so fixed that and reran it.
12) Opened up ArcCatalog to make sure it looked right.   I wasn’t sure if we needed to multiply by 100 on the male female ratio since it is a ratio rather than a percentage.    I decided I can always multiply by 100 down the road if the lab leads me that way.
13) Looks like all fields were created and populated


Part 2: Join Meth Labs to Census Blocks
Include notes in this section about how and why it was important to join the meth lab and census data. Explain any edits you had to make to the data.
1) Opened up my MXD Again
2) Opened the Spatial Join tool from the Analysis toolbox
3) Verified results
4) This created CensusTract_SpatialJoin layer which has the Join_Count field in it
5) Created a new field called LabDensity as type Float
6) Set this using Field Calculator to equal [Join_Count]/ [SqMile]
7) I found the properties page to be an easier way to toggle fields on and off: