GIS4048 Final Project-Brevard County Solar Project

This Final Project was awesome! This project was a lot of work but it was a great experience. The task was to conduct a Location Decision analysis for a subject of your choice. I was excited to tackle this project and I decided to do my Location Decision analysis for a proposed Solar Center in Brevard County. I was partially influenced to select this subject because I feel strongly that we should aggressively pursue Solar Energy production and the fact that I live in Brevard County.

My "client" was the "Special Project Coordinator for Brevard County, Mr. Estrella Sol (Star Sun, pretty clever, if I do say so myself). Brevard County, through new leadership, wants to become known as the "Solar Coast" as well as the "Space Coast." At least, that is the scenario I invented for this Final Project. In reality, FPLis building new Solar Centers in DeSoto, Charlotte and Manatee Counties, and I am saying that Brevard County wants to be a part of this opportunity.  The criteria for this Solar center is:

                                   #1 The parcel must be owned by Brevard County

                                   #2 The parcel must be within 1 mile of a major road

                                   #3 The parcel must be at least 1000 yards from schools

                                   #4 The parcel must be greater than 100 acres

                                   #5 The parcel should avoid disturbing areas of 

                                        environmentally sensitive lands 

For this project I used, Geoprocessing tools such as Clip, Buffer, Euclidean Distance, ModelBuilder and Weighted Analysis. The data I used was as follows:

 


I was also fortunate to have the Brevard County Appraiser website available for my reference. I was able to view aerials of the Parcels I was considering for this project.

After establishing the environment and setting my projection, I used a couple of Select By Attribute searches to limit the field of possible Parcels for consideration; Brevard County has 287,853 parcels . I selected Parcels owned by Brevard County (Select By Attribute > ONAME = Brevard County; this gave me 1806 parcels) and then Parcels greater than 100 Acres (this left me with only 48 parcels). Then, I used ModelBuilder to run  a process to find the Parcels that are near (within 1 mile of) a Major Road, I-95.

  
The last portion of the Project Analysis was to create a Weighted Analysis model. I used the Feature to Raster tool on three datasets:

Parcels_100Acres to ConvertParcelsBC100

MajorRoads_I95 to ConvertMajorRoads

BC_schools_selection to ConvertSchools

The Weighed Analysis model produced a map that seemed to favor the largest parcels, but it was not as conclusive as I had hoped.  

Finally, I was able to use the Brevard County Appraiser's website to review aerials of several of the Parcels. I found some Parcels that looked like they met the criteria, but the aerial image showed that the parcel was actually underwater; easy to eliminate that parcel from consideration. In the end I was able to find three great parcels that met all the criteria including avoiding sensitive lands.  Here's my final map and a link to my final presentation:

This exercise and the entire course of GIS 4048 Applications in GIS, has been very illuminating. I thoroughly enjoyed studying the different GIS applications such as HomeIand Security, Natural hazards and Urban Planning. Once again, I feel like I could have spent even more time working on this final project and all of the projects throughout the semester. If I had more time on this Final Project, I could have provided a written report that included all the information from the Brevard website and I believe this would have been greatly valuable to my customer, Mr. Estrella Sol.  Also, if I had found data about soil type and slope, that too would have been very useful. We take for granted, living in Florida, that slope is not a factor, however, I know, for instance, that in the Tallahassee area “rolling hills” seem to be the norm. A solar site on the wrong side of a hill would be disastrous (better use hillside shading for this analysis). I know I have learned a lot from this course; now my challenge is to continue to use the skills I have gained. To that end I am doing volunteer work with the Brevard County GIS Department and I hope to find full-time employment in the not-too-distant-future.

Participation Exercise Part 2- Mapping Assessment Values

This is the second part of this week's Participation Exercise. We continue our study of the duties and responsibilities of the Property Appraiser's Office. This time, I am working on determining if there are any anomalies with the appraised values of homes in West Ridge Place, a subdivision in Pensacola, Florida. This is a great assignment and I am happy to have this work.

As they say, "A picture is worth a thousand words." So, I compiled a map that had the data I could use to make a recommendation to the local Property Appraiser. My goal was to display values for the homes in the West Ridge Place subdivision in a manner that allows for easy comparison. I put together a map consisting of Land Values, the shapefile for the subdivision, Parcels, Streets and Easements. I used the command "Join" table and "Select by Location" among others to devise the map below:

The fundamental question to answer when viewing this map is, are there parcels that appear to not conform to the assessed value of properties in this subdivision? As I look at this map I see two properties (accounts) that the answer to this question could be "Yes."  The two properties should be reviewed to see if the assessed values conform to good practices.  There may be good reasons for variance in property value such as improvements on the property to raise the value (such as a $6,500.00 Dog House) or items that detract from the property value. However, in this case, at first glance the property in Yellow, to the left, lower, quadrant (071S312000001001) appears to be under valued compared to the majority of properties in the subdivision. While the property in Red, to the north and slightly off center (071S312000013001) appears to be over valued. Indeed, I believe it would be appropriate to review these two properties.

But since a picture is really worth... a lot of words; allow me to show you what I mean:

The two Parcels in question to be reviewed.

This was a good exercise to experience what our local appraiser's office does on a daily basis. I enjoyed doing the research and compiling the map for this particular type of property investigation. I can't wait to really be involved in this area of GIS work!

Participation Exercise Part 1- Urban Planning

This week in GIS4048 - GIS Applications - besides our Lab on Urban Planning, we are also working on a Participation Exercise. The objective of the Participation Exercise is to explore how a County or municipality, Appraiser's office conducts business relative to assessing parcels for tax purposes. For the exercise we looked up a recent home sale in our area and foraged for the information I will show you below.

 Since I live in Brevard County I selected the Brevard County Appraiser's Web Site to do my research.Dana Blickley, CFA Brevard County Property Appraiser.
It is a very nice web site that is currently being updated- they have a beta site that has a few more features- but generally, this site has all the info you need.
I did run into one substantial challenge: I could not find a single home sale posted to this site for June 2015. So I wrote to the Appraiser's office to see if I was missing an obvious search method that would help me find what I needed; the highest priced home that sold in June 2015. Here's what I got back:

Jim Brandenburg <jim.brandenburg@bcpao.us>	9:19 AM (7 hours ago)
to me

Good morning Mr. Castillo;

Several things come to mind.

1)      Sales often lag behind for a variety of reasons. First, the transfer may not get registered with the Clerk’s office immediately. It may not be processed and made available to the Property Appraiser immediately and we also have certain lag time internally. The net result is that, right now, our most recent sale is from mid-May, 2015.

2)      We also distinguish between “qualified” and “non-qualified” sales… a qualified sale is an unencumbered, single parcel transfer at market price. A non-qualified sale can be just about anything else, from a person transfers a property to a friend or relative for a dollar all the way up to a large commercial sale involving multiple parcels, liens, payments in kind, problems with the legal descriptions… etc.  It seems likely that you would be interested in qualified sales only.

Well, lo and behold, I wasn't off my rocker and I do not lack the skills to do a decent search for current home sales; there just wasn't any data for me to find. So, I elected to use a poperty from June 2014, and here's the information I collected:

First question, Q1:  Does your property appraiser offer a web mapping site? If so, what is the web address? If not, what is the method in which you may obtain the data?
A: Indeed my property appraiser has a great web site, and I posted the link above. But just in case, here it is again:

Dana Blickley, CFA Brevard County Property Appraiser.

Question 2: What was the selling price of this property? What was the previous selling price of this property (if applicable)?   Take a screen shot of the description provided to include with this answer.

A: Let's start with the link to the beautiful property in question: Brevard County Parcel ID27-37-03-02-*-12 and Tax ID 2735118 (To find the parcel, enter the Parcel ID or Tax ID in the QUICK SEARCH block after the web site opens). This fabulous home sold for $1.26M on 06/26/2014. Prior to that the home sold for $1.25 on 08/14/2009. Regarding the description of this home; just in case the link above does not work, here's the image and abbreviated description as well as other pertinent information:

Next question please: What is the assessed land value?  Based on land record data, is the assessed land value higher or lower than the last sale price?  Include a screen shot. 

A: The assessed value is given as "Assessed Value Non-School" and "Assessed Value School". 

The table below shows this, but the assessed values for 2014 are: $828,720 (non-school) and $828,720 (School). Though here they are the same value I did see other homes where the value differed slightly. These values are significantly lower then the June 2014 sale price, but this may be because the assessed value includes a Homestead exemption or two and other variations that decrease the value for tax purposes.

  

The web site had many interesting tidbits of information. I liked that you could select a layer view and choose which layers you wanted to see. Additionally, there were Advance Search techniques and Settings that anyone could manipulate. I copied this link to a Detailed Report that I found interesting. I hope you enjoyed this Participation Exercise; I certainly did!

GIS4048-Urban Planning

This week was very busy. For GIS 4048, we worked on Module 9, Urban Planning. However, there was the matter of a Participation Exercise, that I will discuss in a later post or two. For now, let's discuss this Lab: Urban Planning: GIS for Local Government- Scenario 1 & 2. As you might guess based on the title alone, this looks like a rather long and involved lab. The overall objective was to become familiar with how a local municipality conducts business relative to property appraisals and zoning. This turned out to be more fun than I anticipated. I found this Lab highly interesting because I am currently volunteering with the Brevard County Survey Department located in the Government office complex in Viera (an unincorporated section adjacent to Melbourne, Florida). One of the functions I have observed while volunteering is the request to Vacate certain easement restrictions on various parcels. Usually, it seems, this happens because someone wants to put in a new swimming pool and it may encroach on a neighboring parcel or an easement for access.

For this lab we had to research surrounding parcels for a local developer and provide a report. The customer, Mr. Zuko, wanted to know the type of zoning, and the owners of the surrounding properties to the parcel in question. The best part of this lab was learning how to use Data Driven Pages. Data Driven Pages make it possible to provide much more information in a map book utilizing several pages of maps that can tell a story or convey a great deal of information in a uniform and consistent manner.  Below is one of the pages from my Map Book showing the customer's Parcel:

My entire Map Book for this Module is available for review at:   

Data Driven Pages Report Created by Gil Castillo

The process for creating the Map Book was similar to what I have done in the past to create a complete Map. I did the research on the Marion County Property Appraiser web site; I collected information about this parcel (14580-000-00) and I put together all the details on the above Map Book. The big difference was in using the Data Driven Pages Tool. Using Dynamic Text and Making the Locator that you see in the lower right hand corner of the map was also a very cool experience. Another report I "delivered" to this customer was the written Parcel Report. I created this by using the Create Report feature at: attribute table>Table Options> Reports> Create Report 

Here's the report I created:

The entire report is available at:

Parcel Report Created By Gil Castillo

There were several questions along the way that I had to address. The easiest way for me to present the questions is by listing both the question and my answer for each of the Scenarios:

Scenario 1: Marion County, FL

1. When was the data certified?

A: On the web page that has you “agree to continue” to the “Search engine”, the first sentence states: “Certified (2014) data represents certified assessed values provided to the Tax Collector and used in generating the 2014 tax bill. The 2014 Assessment Rolls were certified to the Tax Collector on October 16, 2014.” The answer is, the data was certified on October 16, 2014.


2. Who is the owner of the parcel and what is the acreage?

A: Once again, exploring this web site and reviewing the portion regarding “Property Information, at the top of the record, the answer is:

HAWKER INVESTMENT TR

C/O JTP FILMS INC

801 N BRAND BLVD # 665

GLENDALE CA 91203

is listed as the owner of this parcel. The acreage for this parcel can also be found at the top of the page to the far right. Acreage is listed as: Acres: 19.46


3. What two types of zoning are listed for this parcel? Include the classification description.

A: On this web site page, a heading for Zoning is found under “Land Data – Warning: Verify Zoning” The zoning listed here for this property is: A1, A1, A1, A3, A3

However, to find the definitions of A1 and A3 Zoning, I had to “hunt” the web site. I began with the "Home" Page and cycled through "Meet the Property Appraiser", Duties of Property Appraiser" "Property Search" (agree to terms , again) "Map It" and finally, "Sales Search" where I found a link to Zoning that opened a “Zoning Codes”, page. Here I found that:

A1 is for General Agriculture and A3 is for RES Agriculture Est. Though I could have just Googled “Zoning definitions”, I am not aware that there is a standard or a universal definition of A1 or A3 zoning. So, I was reluctant to take that shortcut and instead went on the “hunt.”.


4. What is the value of the dog house on this property?

A: Really? The value of a dog house? I found a great drawing of the buildings and the layout on the property. At the very bottom of the page was a section that reads: “Planning and Building, County Permit Search” and there, the second line item from the bottom, is “Dog House.” This must be one fantastic dog house. The permit search area states the Amount as: $6,500, so according to the Permit issued, the value of this dog house is $6,500.00.


5. How many records were selected?

A: I used: Selection> Select By Location > first drop down=select features from and I checked the box next to Parcels_Join. Only show selectable layers in this list, was already checked. I set the Source Layer = Zuko_Parcel, and I selected for Spatial selection method= are within a distance of the source layer feature. Finally, I put .25 and miles for the search distance. The "selection" found 67 out of 643 parcels or features. Therefore, 67 records were selected.


6. List the zoning type(s) with description found in the parcel area.

A: I found mostly A1 or A3 zoning types. A1 is for General Agriculture and A3 is for RES Agriculture Est. However, I did find other types of zoning including: B1, Neighborhood Business, B2, Community Business, B5 which is, Heavy Business, P-MH, Mobile Park, R1, Single family Dwelling and R4, which is for Residential Mixed Use. I made the below table and placed it on my Zoning Map for reference. 

Scenario 2: Gulf County, FL 

7. How many parcels are owned by Gulf County?

A: To get to this point, I started an editing session to annotate the newly created polygon, Object ID number 16911, to show that it too was owned by "Gulf County". Then, I used the Selection by Attribute expression "OWN_NAME" LIKE "GULF COUNTY" as provided in the Lab instructions. The Selection revealed that there are 75 parcels owned by Gulf County.


8. How many land parcels are greater than 20 acres?

A: I manually reviewed the parcels and found only a few that were greater or equal to 20 acres. After running the query, (provided in the Lab instructions: “Use the “Query Builder…” button to create the following expression: Acres >= 20 “) I found 12 parcels that were both Gulf County owned and equal to or greater than 20 acres.

Overall, this was a great Lab and I can't wait to have a job doing this kind of work everyday!

Location Decisions - Where to Live

Almost there....stay on target...we are at the penultimate week for GIS4048. Well, of course, then there's the final project...but we won't discuss that right now.

For this Module we are working on how to use the Weighted Overlay Tool and conduct a thorough analysis for a couple that is moving to Alachua County.  But this is not just any couple; more on this later.

Our goal was clear; Find the perfect location for this couple's new home. So. here is where the challenge comes in. The criteria is:

The new home location must be close to North Florida Regional Medical Center (NFRMC)
The new home location must be close to UF
The new home location must be a neighborhood with a high percentage of people 40 to 49 years old and
The new home location must be a neighborhood with high home values

So, where to begin?

I put together my map beginning with a Base Map of Alachua County. After this I learned how to use the  Euclidean Distance tool and applied it to NFRMC and UF. I had to Reclassify the layers (Reclassify Tool) to make it possible to interpret and compare the results later. I also calculated the Percentage of Population Aged 40 - 49, and Homeownership, since these were also my "clients" criteria. I summarized the data and presented my map to them:

The above map could be used to discuss the four criteria with my "clients", but we are not done with this hypothetical scenario, It seems my "clients" discovered traffic in Alachua County and want to be very close to work to shorten their commute (they should see the traffic in Los Angeles- I learned to drive their). She is a doctor and he is a professor. They are smart and determined. It will be hard to please them, but I am going to try.

So, the next phase of this map creation was to add Weighted Overlays. This was really interesting to me. The Weighted Overlay Tool was very cool. This tool allows you to take layers and give more "influence" to certain data or criteria. I sat down and had a deep discussion with my "clients":

          The couple is very concerned about the commute to work. For Prof. UF, he knows he will have a set schedule that will only vary with the classes he is teaching. In fact, he expressed that when not in class, he could work from home. Mrs. Doctor, may have to go to the hospital at various times of the daydepending on medical emergencies and patient obligations. Therefore, living very close to NFRMC is the most important factor followed by homeownership. The age group was not a concern and in fact, younger or older neighbors made no difference to them by this point. Taking into consideration these factors, my weighting for my final map was:

Reclass_Own=20

reclas_Age=10

reclas_UF=10

reclas_hosp=60

I also used Model Builder to crunch the data with the tool.

In the end, I believe my "clients" will find this map very useful in determining where they will live, work and play.

Homeland Security: Protect and The Boston Marathon

We are wrapping-up our study on MEDS (Minimum Essential Datasets) and the Department of Homeland Security. This week we completed our maps using the Military Template by compiling layers of data on Critical Infrastructure around Boston for the 2012 Marathon. The overall task was to identify Critical Infrastructure, such as Hospitals, School, Dams and Airports and to analyze various Line-of-Sight locations around the finishline where security cameras could be placed. There were quite a few tasks to accomplish for this lab, such as, Analyze Data; add the MEDS data we compiled last week to our scenario map for this week; create a buffer around the event site; create a security buffer around critical infrastructure; identify and secure ingress and egress routes; generate hillshade; create surveillance points; generate viewshed; create line-of-sight graphs and a view in 3D. This last part was very cool and I learned quite a bit doing this so I wold like to list my actions and steps for this last part:

1-       To Create the line-of-sight profile graph, I had to first find where the tool was

a.       I asked myself, “Where is this?  Is this on the Draw toolbar...???” I had to Google ArcGIS Help to confirm where this “Tool” was located.

b.      I selected the Draw Arrow (next to the Drawing dropdown/pulldown window directly under the "Draw" title). I thought, “this can’t be that hard.”

c.       I thought wrong.

2-       Initially, the option was not available for me to select. That is, I could not select the “Profile Graph” on the 3D Analyst toolbar.

a.       Finally, the Create Profile Graph became available for me to select and it was not greyed out.

b.      I think I had to be in the Layout view not Data View.

3-       The Blue handles appeared when I double-clicked on the point. However, I did not need to double click. When I did this a second time for step  7 number 9. I clicked one time and the blue handles appeared and a box was placed around the line.

4-       After making my box around the surveillance point of my choice, the Graph popped up and I was able to select properties and enter a title and subtitle. I did this for several points.

5-       I exported the Graphs for later use and saved what I had before moving on to the next step.

      To create the View in 3D, I had to use ArcScene

a.       The first time I did this I did not notice that the ArcScene icon was on the 3D Analyst toolbar, so I opened ArcScene from my desktop.

7-       I added the layers as instructed and I recall thinking, I vaguely remember doing something with the Base Heights tab a long time ago...

8-      I almost missed the step, “Make sure the Factor to convert layer elevation values to scene units is set to Custom 1.0 and click OK” but I caught it just before exiting.

9-      Then it was back to ArcMap to select, copy and paste the line-of-sight from each surveillance point. This was difficult at first to get to work. However, after I did this a couple of times, all was good.

10-   This was an excellent learning point going back and forth between ArcMap and ArcScene.

a.       I saved my work and tried to export it as a 3D file (finishline_lineosight_gc.wrl). But, this did not seem to be what I wanted

b.   So, I tried again and selected export as 2D and then as a .jpg (finishline_lineosight_gc.jpg)—much better this time.

11-   After this it was time to compile my map.

This was a very involved lab that took two weeks to complete I learned a lot these past weeks and I am sure I will continue to advance in my skills and knowledge.  

Homeland Security - Prepare MEDS

This week we began our study of the Department of Homeland Security (DHS). Our task is to accomplish a Pepare MEDS exercise. MEDS stands for Minimum Essential Datasets and the idea for this was initiated by the DHS to ensure the Nation is prepared for any domestic hazard.

The National Preparedness Goal is a result of Homeland Security Presidential Directive-8 (HSPD-8) and is designed “to achieve and sustain risk-based target levels of capability to prevent, protect against, respond to, and recover from major events, and to minimize their impact on lives, property, and the economy through systematic and prioritized efforts by Federal, State, local and Tribal entities, their private and nongovernmental partners, and the general public.”  This information and more is available at:   National Preparedness Guidelines

The idea is that GIS can be very helpful in the event of a Natural or Man-made disaster and having the right types of information can save lives.  The datasets we are talking about are:

DHS Minimum Essential Data Sets (MEDS)

-Orthoimagery              -Boundaries

-Elevation                       -Structures

-Hydrography               -Land Cover

                -Transportation       -Geographic Names          

DHS is a huge Federal Agency composed of a number of  Agencies:

United States Citizenship and Immigration Services (USCIS)

United States Customs and Border Protection (CBP)

United States Coast Guard (USCG)

Federal Emergency Management Agency (FEMA)

Federal Law Enforcement TrainingCenter (FLETC)

Transportation Security Administration (TSA)

United States Immigration and Customs Enforcement (ICE)

United States Secret Service (USSS)

Directorate for Management

National Protection and Programs Directorate

Science and Technology Directorate

Domestic Nuclear Detection Office

Office of Health Affairs

Office of Intelligence and Analysis

Office of Operations Coordination

Office of Policy

An individual's safety has always depended on how well that person is prepared. It is no different when we are discussing municipalities. As we discuss GIS information, we are concerned about:  

1. The quality, accuracy and currency of all types of data about a particular location; 

2. Efficient and effective methods to optimize data sharing and interoperability between agencies and jurisdictions; 

3. Geospatial analysis to provide situational awareness at all stages of a homeland security operation.  

Therefore, DHS has promulgated guidelines that a comprehensive geospatial database be prepared, ready, available, and accessible to a community’s needs for the prevention, preparation, response, and recovery relating to any catastrophic event.  This is one of the most important components of a successful homeland security operation.

Our task is to compile a MEDS for the Boston area prior to the running of the Marathon - yes, we are traveling back in time. We are tasked to assemble the data to Prepare our map for use in a Homeland Security planning and operations analysis. I collected and re-named the layers indicated above (DHS MEDS) and ensured the projections were consistent. DHS requires that the MEDS data be in the North America Datum of 1983. 

There was a lot going on in this MEDS Prepare exercise, and while I don't want to leave anything out, I'll just hit the highlights. I started the project by preparing my environment and setting the default Geodatabase to my BostonData.gdb. This is a good way to start any project and a habit I am glad to be acquiring. After adding data to my map, I needed to Join a table to my Transportation layer. Working with Tabular data is interesting because I normally think of GIS as strictly images that comprise my map. But the tabular data can be highly useful in describing or grouping data to make the presentation more meaningful.  I took the  Census Feature Class Code (CFCC) table and Joined it to my Transportation layer to better describe the types of roads in the Boston area and then group many of those roads together to streamline my legend. Another "very cool" task here was that I used the Scale Range to hide or not display certain labels at Small Scales so that when you are "zoomed out" the map doesn't appear cluttered. Then, when you "zoom in" or select a much Larger Scale, say Street Level, the labels magically appear. I thought this was brilliant.      

Another interesting task was using the Extract by Mask Tool. This tool is found at: Spatial Analyst Tools > Extraction > Extract by Mask.  Essentially, you use one layer (extent) to extract features from another layer. I also learned that to create a color map, the input raster dataset must be a single band raster with integer values and a pixel depth of 16-bit unsigned or fewer.

One last area that was interesting to me was, converting the schema.ini file that contained all the GNIS information. The Geographic Names Information System (GNIS), was developed by the U.S. Geological Survey in corporation with the U.S. Board on Geographic Names.  GNIS data contains information about physical and cultural geographic features in the U.S. and associated areas, both current and historical (not including roads and highways). The database holds the federally recognized names of each feature and defines the location of the feature by state, county, USGS topographic map and geographic coordinates. The GNIS is the official vehicle for geographic names and it is used by the Federal Government as the source for applying geographic names to Federal maps & other printed and electronic products. The GNIS is also used to provide names data to government agencies and to the public, and provide the Geographic Names data layers to The National Map. In other words, GNIS is a very important system in the GIS world. The problem with the schema.ini file was that the information was not in rows and columns that made sense. When I opened the schema.ini file the first time I could not recognize headings, names, etc. the way it was formatted. So, I had to change the format from CSV Delimited to Delimited and add a parenthetical "pipe." This is the how I made the change in Notepad:  Format=Delimited(|).  The symbol in the parenthesis is a "pipe"; this character is found on the backslash key and to access it you use  "shift" , and then hit the backslash key.      

But that's not all folks. For some reason, after I made the change to the .ini file, my data still wasn't neatly formatted as it should have been. I tried closing and opening the file a few times and finally had to exit my remote session (disconnect from the remote server) and walk away for about 30 minutes. On a positive note, I had time to grab another cup of coffee and stretch my legs. When I returned and re-connected to the remote server, "abracadabra" the file opened in perfect form. This allowed me to use ArcCatalog, to right-click MA_FEATURES_20130404.txt and select the Create Feature Class and From XY Table to create my Geographic Names layer. 

One final note. I also took a look at the  USGS: The National Map  website to get a better idea of what is involved if I had to obtain all the MEDS information (the 7 datasets listed above) completely on my own. Wow! That would indeed be quite a time consuming task. I downloaded some of the data, just for fun and it took me quite a while to get to the data; select the appropriate data; request the data be sent to my email account; then download and extract the files on my computer. My map is not yet complete as we will continue to work on the MEDS process next week. But, here's a look at my MEDS layers as depicted in the Table of Contents (TOC). Remember, this is not yet complete, so please don't judge me.

Homeland Security- DC Crime Mapping

I can't believe we are on week 5! This week, we are looking at how to analyze data using the Kernel Density Tool. The subject of this week's Lab is to analyze DC Crime data by examining various categories of crime ad mapping the proximity of crimes by type and distance from various Police Stations.

I created a graph that shows all the reported crimes in the DC area:

To create this graph, my first step was to summarize the data and create a database file (dbf).
                 - Open the Attribute table, right click the column "Offense" and select Summarize
After I created the graph I experimented with different settings and selections.
                 - I decided to use the “palette” color and named the other items accordingly.
Analyzing this graph was a quick way to see how many of each type of offense was reported.
                 - I could clearly see that the top three Offenses were Theft, Theft from Auto and Burglary.

But this was only one step in the entire process to create the two maps for this week's Lab. Creating the first map, I also had the chance to use the Ring Buffer Tool. I created rings at distances of 0.5 miles, 1.0 miles and 2.0 miles. This told me how many total crimes were reported within these distances. The results were:

                                             0.5 Miles there were 668 crimes reported
                                             1.0 Miles there were 856 crimes reported
                                             2.0 Miles there were 556 crimes reported

I then used the formula:       ([Count_] / 2080) *100

To compute the percentage for each category of crime reported. 

                          At 0.5 miles the percentage of total crimes reported was: 32%

                          At 1.0 miles = 41%

                          At 2.0 miles = 27%

I looked at the data using other tools and finally created the following map:

What I learned from my analysis is that the highest crime rate is at three separate District HQs: 3D with 13% of total crime; 7D with 12% of total crime and 6D with 10%.  In fact, 6 of the top 7 crime rates are at District HQs with the only exception being the Asian Liaison unit that has 8% of the total crime. The data seems to indicate that more crime occurs in the vicinity of HQs and less crime occurs where there are Liaison units or smaller Substations.  However, more important to me is that I gained valuable experience doing this analysis using the tools I have studied in this course.

Compiling the second map was very interesting because I learned to use a knew tool: Kernel Density Tool (ArcToolbox > Spatial Analyst Tools > Density > Kernel Density). I won't try to explain the math that the tool uses; suffice it to say, this is an awesome tool and I had a blast using it. Here's the ArcGIS Help link that explains the Kernel Density Tool much better than I ever could:  

                

                                         The Awesome Kernel Density Tool

And here's my second map for this week's lab:

Natural Hazards: Hurricane Sandy 2012

This week we continued our study of natural hazards by compiling two maps: One that depicts the path of Hurricane Sandy and another that is a Damage Assessment of the same Hurricane. The below excerpt is from, "Tropical Cyclone Report Hurricane Sandy (AL182012) 22-29 October 2012":


"Hurricane Sandy was a classic late-season hurricane in the southwestern Caribbean Sea.  The cyclone made landfall as a category 1 hurricane (on the Saffir-Simpson Hurricane Wind Scale) in Jamaica, and as a 100-kt category 3 hurricane in eastern Cuba before quickly weakening to a category 1 hurricane while moving through the central and northwestern Bahamas...  The system restrengthened into a hurricane while it moved northeastward, parallel to the coast of the southeastern United States, and reached a secondary peak intensity of 85 kt while it turned northwestward toward the mid-Atlantic states.  Sandy weakened somewhat and then made landfall as a post-tropical cyclone near Brigantine, New Jersey with 70-kt maximum sustained winds.  Because of its tremendous size, however, Sandy drove a catastrophic storm surge into the New Jersey and New York coastlines.   Preliminary U.S. damage estimates are near $50 billion, making Sandy the second-costliest cyclone to hit the United States since 1900."

Hurricane Sandy was certainly a major Natural Hazard event in 2012, and it makes sense for us to study this event today. Our objectives for this week's lab were to utilize several tools to create and display the storm path and conduct a damage assessment in the area where the storm made landfall. Some of the tools I used were:

- Select by Attribute
- Add X-Y data
- Points to Line Tool
- Adding Graticules


Using the Points to line tool was interesting. The tool can be found at:

ArcToolbox > Data Management Tools > Features > Points to Line Tool

I took the points provided with the Sandy Track Events file and utilized the Points to Line tool to create the path that Sandy followed up to the New Jersey shore. Then, I symbolized the storm intensity using an appropriate color ramp and then I added the storm symbol to my map. Another interesting thing I did was add Graticules to my map. This was indeed a first for me, and fortunately, a relatively straight forward task to accomplish:

From Data Frame Properties > Grids > New Grid.  Select Graticule: divides map by meridian and parallels and, there you have it. Of course, you must be in the Layout view to see the Graticules (another Lesson Learned).

To create the Damage Assessment map, I used several aerial images to make a Raster Mosaic.

I added the imagery to DamageAssessment.gdb by right-clicking on the GDB > New > Mosaic Dataset. After adding all the layers such as the NJ_Counties, NJ_Municipalities, NJ_State and NJ_Roads, it was time to create some data!

One of the main objectives for this week's lab was to make comparisons of the before and after aerial imagery where Sandy came ashore in New Jersey. The Effects toolbar contains a "Swipe" tool that allows you to peel the selected layer back and see underneath it. Cool! Only, you have to be in Data View to use the tool...I was in Layout view when I started this part and the tool was disabled; another good lesson learned.

I created the Damage Assessment Table after digitizing several homes from the post storm aerial and I did remember to save my edits!  Here's a look at my final two maps.

GeoHazards: Tsunami Evacuation

This week in GIS4048 Applications, we continue our journey through Hazardous terrain. This week we are discussing Tsunami's. Specifically, we were charged to build an evacuation map for the Fukushima II Nulcear Power Plant that was flooded by the Tsunami that hit Japan on March 11, 2011. This Tsunami, that hit the northeastern coastline of Japan, was the product of a 9.0 earthquake.

A Tsunami is an incredibly destructive force that:

- „Causes human death (average death rates are estimated at 50% of the population but have been reported up to 80%.)
„- Leaves people homeless, destroys other property.
„- Psychologically traumatic.
„- Spreads contaminates to water and food sources.

Our objective is to provide an analysis of both the Radiation hazard and the runup evacuation zones caused by this Tsunami. There were many tasks to accomplish. Below I outline two major tasks.

Task#1 Fukushima Radiation Exposure Zones

To create the Fukushima Radiation Exposure Zones, I had to develop my map so that I could look at the distances to determine the possible population totals that might be effected by the nuclear radiation from Fukushima II. To accomplish this I needed several layers of data.  I included the following layers:

a. JpnBndOutline

                                    b. NuclearPwrPlnt

c. JapanCities

d. Roads

e. NEJapanPrefectures

With these layers, I could find Fukushima II by manually selecting from the NuclearPwrPlnt attribute table the plant I was concerned with. From this selection I made a layer with the one point: Fukushima II Nuclear Power Plant.

At this point I needed Population information; I added Japan Cities and selected those Cities that were within 50 miles of my NucPwrPlnt.

Next, I could use the multiple rings tool to place rings at: 3, 7, 15, 30, 40 and 50 miles from the Fukushima II, Nuclear Power Plant.

ArcToolBox>Analysis Tools > Proximity > Multiple Ring Buffer

 After this, I found, by using Select by location the cities that fell within the prescribed distances above 

The last step for me was to ensure I had selected an appropriate symbology for the radiation zones

.

                        - The first attempt I forgot to deselect <all other values>

                        - Subsequently, I reviewed several color ramps before selecting the red to green ramp.

                        - I selected Category= Unique value and then deselected the borders for each color

Here is my result:

Task#2 Model Builder: Develop Tsunami Runup Zones 

This was a very interesting portion of this week's lab. Model Builder is a great tool; you just have to stay organized and save your model when done. To get to the Model Builder you open ArcCatalog then add a ToolBox to your GeoDataBase (right click on the .gdb and select New > Toolbox). Once you have added the Toolbox, you can right click on it and select New > Model  

After I completed and successfully ran my model, I went back to it to do some editing, however, I could not open it. I must not have saved it properly (though I thought I had because it appeared in ArcCatalog). So, I re-accomplished the model, getting two-times the practice on this part of the lab, and then I ran the model and SAVED my work.  

Lesson Learned: Ensure my work is always SAVED.

Natural Hazards: Lahars and Module 2

It has started again. I can feel my pulse trying to jump out of my body. I have not had so much excitement in a while. Module 2 for GIS Applications was an exercise in learning about Natural Disasters, such as Meteor strikes, Hurricanes, Floods, and, my map of the day: Lahars. The lab consisted of using several new tools including:

-  Hydrology toolset.
-  Mosaic to New Raster (Data Management)
-  Fill tool
-  Flow Direction
-  Flow Accumulation
-  Conditional Evaluation of Rasters
-  Raster to Feature
-  Using Raster Math >  Math > Int
- And using  Spatial Analyst Toolbox > Hydrology > Stream to Feature

The objective was to determine where Lahars or streams would flow in the event that Mt Hood erupted. "Lahars, or volcanic debris flows, are water-saturated mixtures of soil and rock fragments that can travel very long distances (over 60 miles) and as fast as 50 miles per hour in steep channels close to a volcano." (Oregon Geology Fact Sheet)

I also had to take two DEMs and combine them to make one mosaic to then compute the flow by changing the cells to integers from floating points. I used the Spatial Analyst Toolbox and executed the Math > Int tool. This converted the floating point raster to an integer raster-- this was way cool!
After this step I could use other tools such as the Con Tool to control the output value for each cell. Ultimately, I wanted to arrive where I could determine the flow or streams the Lahars would follow and what schools, cities and the amount of population that would be at risk. The below map shows that, in the event that Mt Hood erupts, a number of schools and cities would be in danger. Also a large population, 58, 260 people, would also be in the path or near enough the Lahars to be at risk.