Wednesday, August 9, 2017

Sharing Tools

Module 11, the last module, has seen my first "happy dance" in that everything worked smoothly and correctly for me for I believe the first time ever!!  This was a helpful module and helped to reiterate the interconnection of PythonWin, ArcMap and ArcCatalog.  It had many helpful tips for making sure data management is correct.  The lab modified a script and embedded/imported the script into the script tool.  The tool was run and created the desired random points with buffers as seen in the following screenshots of my tool input window, results and map respectively:

The part of the script that required editing was the sys.argv[] tool which always returns string objects as the arcpy.GetParameterAsText() code does.  The sys.argv[] expressions have character limits and parameters will be cut short in cases of excessive text.  Finally, the sys.argv[] expressions start with [1] instead of [0] which is used to get the filepath of the script itself.  The advantages of embedding/importing a script into a script tool in terms of sharing the tool is that the only file required to share is the toolbox.  From there, in terms of security, it can be password protected so that no one may edit or see the script without the proper password.  To make Python scripts, and other file types, visible in ArcCatalog simply go to the customize menu and select ArcCatalog options.  From there choose the file types tab and click “new type”.  In the following dialog box you may import from a registry or enter the file type manually by entering the file extension and description.  The file type will then appear in ArcCatalog.

The most useful part about using Python with ArcGIS is the ability to “test” out code in one environment before putting it to use in the other.  I enjoyed this module most for  #1. Everything actually worked right for me and #2. It was helpful use the toolbox, script and tool – editing in PythonWin and executing in ArcMap for a visible result.   I found it most interesting the scope of edits that can be made in PythonWin in order to obtain the result desired in ArcMap.  I also liked the ability to customize tools to obtain the desired results.  I know I am not going to spend my life doing this (the world isn't ready) but I am happy to have the knowledge this course has given me.  

Final - Finding the Ideal Orlando Home

The final project in the Applications course was a culmination of all the previous modules to result in an analysis of Orange County, Florida for the ideal home location for a young couple moving to central Florida.  Two of my maps are below:

The couple wished to satisfy all, or as many of the following criteria as possible to the greatest extent.  1.  Commute distances of less than 40 minutes.  The husband will be working in downtown Orlando and the wife at the Walt Disney World Resort.  Distance analysis was performed using the Euclidean Distance tool and then later with the Weighted Overlay tool.  Both yielded a result of Winter Garden as being a good location.  2.  Parks and recreation should be nearby the new home site.  A parks and recreation layer was added which indeed showed several options around Winter Garden; in addition, there is a large lake in Winter Garden that will be appealing to the couple.  3.  They would prefer a neighborhood where the population is in their age range of 35-45.  A layer of census tracts was added, converted to a raster and reclassified to make the data more visibly understandable.  Finally the Weighted Overlay tool was used to map this against the home ownership percentages.  4. They prefer to be in a neighborhood of high home ownership.  Like the population analysis, a layer was added, converted to raster and reclassified before finally using the Weighted Overlay for analysis against the population age.  The weighted overlay can also be changed from equal influence to differing influences based upon whether the couple places more importance on one of the criteria over another.  This would be for the couple to determine.

Winter Garden was determined to be the ideal location given all criteria.  It is also aptly situated on the Florida Turnpike for ease of access to both work locations as well as the interstate.  The couple has several maps to examine in their relocation given these results.

Wednesday, August 2, 2017

Creating Custom Tools

Module 10 introduces the process of creating custom tools using a combination of PythonWin and ArcMap.  I found this to be the most useful skill thus far in the programming class.  The exercise and assignment made it obvious how customization of tools, using code, can be highly valuable to the GIS process.  The following screenshots are from the assignment:

The properties of the script tool allow for the inputs and parameters to be set.  The parameters need not be set prior to completing the tool.  They may be added later and in between editing the stand-alone script.

This process is quite useful in that stand-alone code can be used to form the script tool with only a few adjustments.   The variables are changed from complete file and path names to the arcpy.GetParameter() where the values contained within the parenthesis are numerical.  This allows for fewer errors.  The same type of changes are made to "print" statements from the stand-alone script; these are converted to arcpy.AddMessage () in a similar fashion.

The script tool is easier to share, edit and allow for fewer errors.  Anyone can use them in ArcMap and Model Builder.  From this lab assignment it is clear that the use of script tools and custom tools is highly valuable to work in the GIS field.

Wednesday, July 26, 2017

Working with Rasters

Module 9 demonstrates the many capabilities that rasters have in the ArcGIS environment.  This was the most difficult module for me thus far and I have determined I will not be doing this in the "real world," from technical difficulties with the remote desktop to the complexity of the area of study I recognize I am not cut out to do this on a daily basis.

The results don't appear to show this but I did learn a good bit throughout the exercise and lab assignment this week.  The function to "Describe" rasters is quite useful.  One can determine properties such as: base name, file type and extension; this could be useful when examining metadata. Displaying raster resolution is slightly more involved but still useful; however, inputs must include mean cell width and height.  In dealing with multi band rasters, the individual bands must be specified.

When using rasters in geoprocessing, the spatial analyst extension must be enabled and license available.  These tools return raster objects which are a variable that points to a raster dataset. The module contains functions to perform map algebra and the module allows the calling of different geoprocessing tools in a simpler manner thereby reducing error risk.  Having a background in mathematics, the slope function was most intuitive for me and I found it useful how variable inputs can be entered into the code and easily return a result.  Reclassifying rasters can also be performed within this context and the end result of this assignment was to be a raster.  I have been experiencing technical issues with my remote desktop, particularly with reclassifying rasters in other courses.  I am unsure whether those problems also contributed here but am working to rectify any glitches that may exist.  Nonetheless, the resulting raster in ArcMap should have shown the landcover.  Despite problems I understand the overall goal of the assignment and the implications of skills learned.

Participation #2

The article I chose for this assignment is as follows:

Integrated Flood hazard Assessment Based on Spatial Ordered Weighted Averaging Method 
Considering Spatial Heterogeneity of Risk Preference

This article looks at China and areas that are at high risk for flood disaster and the implements that could be put in place in order to improve outcomes.  The areas being studied in with this publication are Hanyang, Caidian and Hannan of Wuhan, China.  Several of these locations plagued by frequent and severe flooding events.  The author points out that many times the worst effects occur in areas of high population making it even more imperative that solutions be derived from GIS analysis of flood zones.  The primary analysis presented here is “the spatial ordered weighted averaging method with spatially variable risk preference was implemented in the GIS environment to integrate the criteria.  The advantage of the proposed method is that it has considered spatial heterogeneity in assigning risk preference in the decision-making process.” (Yangfan, Shanzhen, Zhongqian)  The results of this study sought to mitigate losses of life and property which is a real-world.  This study using GIS principles and applications represents a crucial aspect of our times and the science that must continue in order to preserve life and ways of life into the future.  

Sunday, July 23, 2017

Urban Planning

Module 9 looks at urban planning.  I would have to say that this has been one of my better outcomes. A major feature of this module is learning about Data Driven Pages in ArcMap.  These are quite helpful in that they allow for the presentation of a large amount of visual information within one map document.  The pages act just as one might assume.  A locator map is used to show the relation of a page to the entire context and the pages are easily navigated with the Data Driven Pages option enabled.  A page of my final map is seen below, this is the page containing the parcel that was being examined throughout the lab:

This lab, in particular, showed the many applications of using GIS in a local government/city planning environment.  Urban planning processes also require the use of parcel data.  Though I have had experience with this type of information in the past it was helpful to use it in a more pertinent objective.  Zoning was something I had not encountered and it was eye opening to see the many classifications and to interpret those implications.  Creating the site map and grid index was somewhat involved but the end result is intuitive and makes interpreting the data easier.  I also found creating reports quite useful.  The degree of customization is most helpful and can be used for virtually any data required.  Examples of data extracted from this lab: there were discovering a $6,500 doghouse on a property (don't tell my dogs), 75 parcels in this area are owned by Gulf County and 11 of those are greater than 20 acres.

I am a magnet for technical glitches and this lab was no exception.  It took three days to do something as simple as exporting a map and goes to show how problematic software can be at times; it made me realize I need to practice more patience with GIS!

Participation Assignment

The participation assignment looks at property assessment.  Every location seems to go about the representation of this data differently.  The lack of consistent information is frustrating to say the least.  The following are questions and screenshots from this exercise:

      1.  Washington County, TN property appraiser website directs to Tennessee Comptroller of the Treasury Real Estate Assessment Data page: 
      From here property cards may be accessed and GIS maps viewed. 

2. Cannot locate record of property sales for my area including surrounding counties.  Checked the provided link for Maricopa County, AZ for property sales records, returned over 9,000 results in PDF documents.  Not sorted by date.  A search for local property sales records yields only realtor and home sales sights.  Since I cannot locate the highest value home sold for June 2017, I will include my neighborhood home values for the sake of this exercise.  Sales and descriptive information are found in these screenshots. 

3. Assessed land value: $3,200.  Land value lower than last sale price due to the fact this is a condominium community; however based on land values close by it is higher due to the fact the location is closest to a University. 

4. Additional information: no link to deed provided.  Property is within walking distance to a major University.  As the University has expanded dramatically in recent years the value of this property has also increased.  The surrounding city is also expanding and as a result the land and property values are increasing.  

Final assessment map seen below:

5. In learning more about property assessment I would suggest, from this end result, that the one property in red be evaluated and reviewed.  This is an outlier of sorts in the context of the rest of this development.  The small blue triangle represents a sewage lift station but does not seem to have much negative effect on the values of the parcels immediately surrounding it.  The parcels which are oddly shaped are not suitable for development and worth a review as well for purposes of improvements.  There would also be interest in examining what makes the five parcels in light orange less valuable than the majority of others surrounding them.  These are likely more dated properties or have some other less desirable location or characteristic.  

Part two of this assignment was more enjoyable than the first.  It was informative to use raw data such as these property values and create a document that could have far reaching consequences in terms of decision making and home ownership.