Module 11: Sharing Tools

The FINAL MODULE for GIS Programming!  We explored different methods for sharing script tools, learned ESRI recommended folder and file structure for sharing script tools, identified data and workspaces for script tools.  We learned  how to created a geoprocessing package, embed scripts and password protection tools and created script tool documentation.

This week in lab we focused on the standard folder structure and filepaths necessary when sharing tools and looked at some geoprocessing packages that provide an alternative solution to distributing script tools.

Module 10: Creating Custom Tools

This week we created a custom tool.  We were provided with a stand alone python script.  In ArcMap we created a toolbox and added the script to the toolbox (adding a description and check the "store relative path names").  We added parameters to the tool by right clicking the tool and choosing parameters 1.  Input file location 2. Clip Boundary Feature 3. Input features 4. Output file location.  We set the types for each and location:

Proposal Final Project

This week we prepared our Final Project proposals.  We were provided with a template that outlined sections (Title, Introduction, Methods, Anticipated Results, References) and specifications that were to be addressed in each section.  The proposal written using clear, specific, professional and descriptive language in word format.

I am planning to relocate to this area in the future.  My sister is in Murphy and my parents just relocated to Plano in April.  I wanted to do my project on this area to gain some information for myself of the area.  Initially I thought of looking at the surrounding counties to see some of their economics and natural resources to find areas I might want to focus job searches.

This project made several transformations as the realization that my original desired study area (Collin and surrounding counties) was recognized as much too large.  Another revision when the data that I had acquired for the large area wasn't translating into a smaller study area (airports, lakes and geographic named areas are mostly outside of the study area).  Further revision when I realized that Plano and Murphy are so disproportionate in size, that comparisons were unrealistic.  Finally settling on this Exploration of Plano Texas.  As my parents have only recently moved here, focusing the project on finding and displaying data that would be useful to them, assist me with learning about the area (although limited) and a focus for this school project.

The base map above includes boundaries, roads, railroads, the lone airport, parks and surface water.  The concern for the location of toll roads is already being addressed in the base map and will continue to be highlighted by the bold symbology.  The goal of the project will be to include layers to the parks and water features for farmers markets, destinations and museums.  This will provide visual reference for where to go to do something fun.  A more informational map showing locations of hospitals in the area.  Maybe a larger scale map to show the locations of the airports.  An even larger scale map to show the names of surrounding counties to better follow weather alerts in their area.

Module 9: Raster

This week we learned how to use Python to work with spatial data in ArcMap, specifically working with rasters.  We gained experience listing available raster datasets within a specified workspace, describe properties of the datasets, utilized arcpy.sa (spatial analyst) to define raster parameters and finally wrote algebra expressions in Python. 

We reclassified a raster to show only forested lands, further limited to slope 5-20 and aspect 150-270.  Green in the image above does NOT meet these requirements.  The purple color DOES meet all the requirements. The new raster was saved to the gdb file in our data folder.  Temporary rasters for calculations were not saved.

Module 9: Local Government

This week in lecture, based on collaboration between UWF GIS staff and local GIS staff, the “Essential GIS Skills for Local Government GIS Users.”  The lecture learning outcomes were derived from knowledge, skills, and abilities government personnel outlined as crucial to the field.  We reviewed some roles of GIS in local government like planning departments and tax assessors.  We reviewed Public Land Survey System (PLSS): section, township and range.  We got some experience utilizing a local assessors website to obtain parcel data and land descriptions.  

In lab this week we had two scenarios.  1)A local developer gives you a parcel number and asks for a parcel report of the site and adjacent area. We prepared a map book of the requested parcel data using data driven pages, as well as a corresponding parcel report for added information. 2)Help locate suitable parcels for an extension office based on desired criteria (owned by entity, 20 acres or more, and vacant).

This week data was provided from local county websites.  We examined property based on Zoning ID, Parcel number and PLSS. We edited parcel information, created maps with dynamic text, created data driven pages, created a locator map for a map book.  Updated parcel geometry (merge and split a parcel) and updated attribute table for those parcels.  Identified parcels using location searches and attribute queries.  Produced values in attribute table with field calculator.  Ultimately, a map book (one page displayed above) and report for the developer (below) and a report for the sibling office (below).

Participation: Local Government

This week's participation assignment was to explore land records within your local government.  Specifically we were asked to focus our research in the property appraisal area.  My local property assessors office part of the revenue department of Baldwin County Alabama.  Here is the web site:  http://baldwincountyal.gov/Government/revenue .  They do utilize mapping, here is the web site for the map:  http://isv.kcsgis.com/al.baldwin_revenue/ .  You can utilize the map to click on parcels that you might be interested and pull up their appraisal information and/or their tax

The first document shows the comparison from the appraised to the assessed values. And the second shows the break out of the assessed value.  The rest of this assignment was to investigate recent property sales for the month of June of the current year to locate the highest property sold.  My local office does not have that information available.  The assessor's office directed me to the probate office who then said I could look at individual deeds that were recorded for a particular day but where not able to provide sales price on a monthly basis. 

I also looked at Collin County Texas appraiser office  https://www.collincountytx.gov/tax_assessor/pages/default.aspx   I have family in this area so I thought I would try to locate information in this area.  I was not able to locate sales information on their site either, but they have an interactive map: https://collin.maps.arcgis.com/apps/webappviewer/index.html?id=28b784073c47453895a6f69a22bd76e1 . 

I also checked out Maricopa County, AZ assessor: https://mcassessor.maricopa.gov/ .  This is one of the examples given in our overview for this assignment.  I lived in Phoenix, AZ in another lifetime (more than 15 years ago).  They also have an interactive map: https://maps.mcassessor.maricopa.gov/

but after  searching around the assessor's site I was not able to locate any sale information specific to individual properties. 

The second part of the this participation assignment was to create a map of subject properties in West Ridge Place subdivision.  The map has been requested by the local property appraiser to review land value assessments and assist in evaluating any inconsistencies. 

Accounts that could be reviewed for inconsistencies include are all lots that are not at the 27,075 mark (yellow).  The lots that are significantly below should be checked against the subdivision plat to make sure the non-buildable lots are listed as such on the plat (blues and green).  The buildable lots that are slightly below or slightly above should be reviewed for consistencies (yellow-green, red).  Sometimes there are legitimate reasons for the difference in lot price.  The lay of the land may have storm water run off coming across the lot, a utility or drainage easement may limit the buildable area, or a large oak tree left in tact may raise the value of a lot over others.

Module 8: Geometries

This week used Python to work with spatial data in ArcMap. Specifically, we focused on reading and writing geometry objects (aka Vector data).   Vector data can be organized into rows of an attribute table, each row may contain an array of object or point information continue down to individual vertices that make up the shape.  Geometry tokens are shortcuts to specific geometry properties.  This week in lab we utilized search cursors and for loops to get through, row, array of parts to points.  Then the information was converted to strings to write the OID, point number, x coordinate, Y coordinate and name of the feature to a text file.  Above is a section of the text file, created and written with Python, containing the information

Module 8: Location Decisions

This week in lab we assumed the roll of a consultant for a couple relocating to Alachua Florida.  We helped facilitate their decisions about where to live by performing weight analyses on their ideal dwelling situation.  Close to their places of employment, her at North Florida Regional Medical Center and him at University of Florida.  They also want to be in a neighborhood where there is high percentage of homeowners, 40-49 years old.  We used demographic data, property information, and such spatial factors as proximity to important landmarks. 


We se map environments and map document properties, created a basemap using a basemap layer, calculated distance using the Euclidean Distance.  We reclassified raster data, preformed calculations utilizing the Field Calculator, and utilized Model Builder to preform multiple processes at once.  We conducted analysis using Weighted Overlay tool, and utilized to isolate areas to further investigate.  The maps above hopefully explain results clearly and effectively, while providing the client their desired information.

Module 7: HLS: MEDS Protect Critical Infrastructure

Last week we assembled the Minimum Essential Dataset as defined by DHS for the Boston Metropolitan Statistical Area.     

This week we created new point data (finish line, surveillance points)and utilized data compiled last week to locate streets within a 3 mile buffer surrounding the finish line to define checkpoints.  We used the geographic name data from last week to identify those within the 3 mile buffer to created a summary table.  We focused on the hospitals and showed the 10 closest hospitals to the finish line (omitting specialized hospitals and teaching campuses) by utilizing a near table.  We explored LiDar data using the LAS toolbar, converted LAS Dataset to Raster, utilized the hillshade tool to add depth, and viewshed analysis for potential surveillance points. Lastly we created a Line of Sight in 2D (what was supposed to be for potential camera locations, however I miss read and created the Line of Sight from the proposed surveillance sites).  Also, our survey points were to contain the point number and the elevation.  I set the labels to all with the same python script, but only some of the points were labeled.  Alas, the correction or issue escaped me before due.  We were supposed to transfer this data to 3D in ArcScene, but the copy and paste was being glitchy so that was not possible. This compilation of maps could provide useful information for security and surveillance teams.

Module 7: Explore/Manipulate Spatial Data

This week we will studied various approaches to exploring and manipulating spatial data. Specifically, we looked at list functions and how they can be used, built-in Python functions, the ArcPy data access module arcpy.da, cursors, and were also introduced to tuples and dictionaries.  This week we explored: 

• how to check for and describe data with arcpy.Describe, 
• how to manipulate list of data by indexing, delete, sort and append
• how to create an empty dictionary {}, and add, change and delete
• how to work with search cursors to iterate over data stored in lists 

We learned the benefit of working with dictionaries to obtain our data for the above script. We also used a search cursor with SQL expression and added those results to an empty dictionary.