final project intermediate gis; project description and analysis outline

8/12/2019 Final Project Intermediate GIS; Project Description and Analysis Outline

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incoming cable XKA-DDISA1312014

initial recipient D. Doolittle

end recipient M. Kulish

datetime of reception 1312014 PST 1731

ATTN M Kulish here is the original communication received, proposal, analytical outline and visualizations

you requested. It is ready to have a final review and to be forwarded on to the necessary parties. The

assignment comes as three separate files in the cable the original communication with an attached

analytical outline, the proposal with an attached analytical outline and appendices, and the visualization.

...Original Communication

A electronic message intercepted between two unknown parties, indicates a country not

allied with the United States is in the preliminary stages of preparing to build 6 data collection

centers in Kitsap County Washington. The message goes on further to say this is a trial run by

these unknown entities to build a centralized monitoring hub of data concerning Washington

states wartime capabilities to respond to a larger scale invasion. The intel then continues with,in Kitsap County these data centers will act as central nodes to collecting analyzing and

dispersing data of the following areas Bangor Naval Subbase, Bremerton Naval Base, Whidbey

Island Naval Station, and Joint Base Lewis McChord. The centers will further be used by the

foreign entities to conduct pre-emptive cyber-warfare if a larger scale invasion occurs. GIS

analysis is needed of the criteria provided in the request for a proposal, to assume the locations

the data centers will be before the developer is scheduled to meet with the governing bodies

representatives later this month. In addition Homeland Security and or the Federal Bureau of

Investigation would like to request a federal warrant approved to conduct surveillance and

domestic electronic monitoring these locations. To do so however factual evidence of where the

developments could occur following the criteria and who is proposed to be responsible is neededto build a strong case. Likely the local development companies who would take on this project

will use www.kitsapgov.com/gisfreely available datasets to provide the uknown party with

suitable sites to begin purchasing then building on the sites. Before development begins this

attempt at espionage by a foreign entity needs to be stopped..The development of these sites will

be a threat to national security and territorial integrity of the United States. The

intelligence indicates the development company in question will be looking for a set of criteria to

present 6 areas to build affordablehousing. The criteria starts with the fact that each

location will have 10 units built onto it.The 10 units are to take on the appearance of two

story apartment buildings. The outer shell of each unit will be a an actual living area, presumably

for the foreign agents or individuals who have lower incomes to act as cover. Inside each outershell will be a inner two story data collection server room and operations center. The inner shell

is also capable of housing and maintaining 5 technicians and 5 security personnel for extended

periods of time. This makes the foreign country in question capable of having 60 foreign agents

in Kitsap County indefinitely. The initial size of the property proposed for purchase has to

be between 1.5 and 4 acres.This comfortably makes the proposed developments manageable

with this size frame as well as allows for some buffer zone between adjacent properties. The

use of which is outlined in the intel as security measures. The unknown party in question also
http://www.google.com/url?q=http%3A%2F%2Fwww.kitsapgov.com%2Fgis&sa=D&sntz=1&usg=AFQjCNFSbQP0jQOCpDbemu-CVPCMrbRbDA


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requests each property be under a sale value of 200,000$ per unit but notes acquisition

prices can not exceed 25% of the target price. each property is targeted to sell at

2,000,000$ total with ten units on each property.In other words the maximum purchase

price for each of the 6 properties can not be over 500,000$ .Variables that would cause the

price to exceed would include demolishing any current standing structures on the property

acquired.If buildings exist on the property the acquisition price extends 25% of theoriginal cost.This means any available properties with buildings can not exceed the

acquisition price of 375,000$.This intelligence indicates the foreign country in question has a

swiss bank account with a account balance for foreign securities development of 50 million

USD. If successfully able to build these data recovery and espionage centers in Kitsap County,

the messages diction mentions expanding operations to other major areas of United States.

Primarily these areas would have high military presences on the western seaboard of the United

States. This can be presumed to include San Francisco, Los Angeles, and San Diego. The

budget for the preliminary run on setting up the facilities is unknown, heavily outlined in the

intelligence are the numbers 1,200,000 and 1,500,000. This presumably is the maximum funds

spent per areas development solely, between 1,200,000$ and 1,500,000$. With this funding notonly 4 of these 6 building centers could be opened up, nearly 33 of these 6 building centers could

be opened in the United States. This strict ranges of maximum cost spent per center also fits

Washington State tax law for it being considered affordable housing. Regulation permits federal

tax subsidies and exemptions for building facilities considered affordable or low income

housing between this range, effectively keeping the proposed facilities out of the eyes of federal

tax infringement monitoring. It also provides a loop-hole for this foreign country to use federal

laws to build low cost sites for foreign security development on U.S. soil through proxy urban

development companies. Due to the sensitive nature to exposure of the true business at

the facilities the deciding authority has also made it a priority the locations are not to be

within geohazard or floodplains, essentially wetland areas of Kitsap County.This furtherlimits the exposure of the facility in the event of severe winter weather in the area causing a

landslide or flood causing damage to premises. These areas also pose a threat to the equipment

under and above ground the foreign technicians will install to monitor data as well as provide

security for the facilities. The foreign client has requested each site have access to a

public road and within 1 mile of healthcare facilities.In the event of one of the inner shells

being discovered by domestic authorities, access to a public road is essential according to the

intelligence provided. The primary reasons cited for the properties being fronted by at least 1

public road are to have multiple options in evacuating facility personnel individually, to not raise

attention to a conjoined group effort. Further attention is made in the recovered intel to burn the

whole program if one of the facilities is in immediate threat of being discovered. Then each

facilities personnel are to proceed separately to the nearest saltwater shorelineto

rendezvous with the other facility personnel first, then commandeer sea transportation until

reaching international waters for extraction. For this purpose the intel alludes to the

importance of each proposed property being within ten minutes time travelled on foot to

from a saltwater shoreline.If an invasion is imminent the leader of this foreign entity will give

an undetermined signal nonchalantly to the mass media during a live interview to signal to the

foreign agents at the facilities. Whatever this signal is, security personnel at the 6 facilities are


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instructed to converge on a medical facility within 1 mileof their facility to procure supplies

needed to defend the facilities from domestic attack until reinforcements will be scheduled to

arrive 18 hours later. Properties also must encompass the ability for the foreign personnel

to conduct clandestine operation coordination meetings for each facility monthly. These

meetings will need to be within a 20 minute walk of the facility holding the meeting.

Meetings will rotate between the six properties, each facility having two meetings a year.Communication from the facilities to the governing entity regarding status updates on

the assemblage of operations will need to be done covertly at public libraries to maintain

anonymity of the data collection operations. Each property is requested to be within a 20

minute walk of a public library.Something is said within the intel about a mom and pop

relationship being the center of the subject of electronic communications from the libraries.

English is to be the only language used and proxy email accounts will be assigned to personnel

on completion of the facilities in preparation for the program. By providing locations of the

nearest parks and libraries in the proposal, it also helps federal agencies to concentrate

monitoring of these areas.

All of these criteria also fit the cover the governing body is trying to portray as affordableand low income housing. Being on a public road generally makes access to public

transportation easier, as the occupants of the outer shell may not have transportation

depending on their individual situations. Having a hospital within 1 mile gives the ability to

promptly use those services in event of an emergency. This also saves money for these families

by cutting down an ambulance bills to a hospital in times of emergency. Firms who typically

invest in affordable housing look for locations where an imminent natural disaster or flood would

not affect the premises to protect their investments. As mentioned before the foreign entity is

unknown. The National Security Administration is working to decrypt the intelligence to the

original language but is so far not having any success as the encryption means are something

they have never seen before. Please proceed cautiously in forming this analysis, localdevelopment companies are not to be contacted about their involvement in this matter. By

formulating this analysis into a model, in ESRIs Arcmap Modelbuilder, location selection can be

made in the areas mentioned following the criteria mentioned above San Francisco, Los

Angeles, and San Diego. It is of critical importance this proposal is finished before the date of

March 13th 2014. The foreign body is set to receive a proposal and exchange of funds from a

local development company March 15th in the Seychelles islands. The Central Intelligence

Agency will represent the local development company at a redirected earlier meeting to reveal

the identity of the governing body responsible for the intelligence recovered. Then the governing

body will be allowed to purchase and begin development until being stonewalled with fabricated

development regulations. This gives the federal intelligence agencies time to monitor other sites

the model will reveal and decimate the efforts of what appears to be an elaborate plan for an

invasion of the western seaboard before it gets underway. This intelligence is reliable but is a

completely unheard of scenario on any level within the intelligence community. Doing all of this

and bringing to light the parties involved all starts with this proposal. The proposal must be

professionally produced for the representing United States assets to use it in the field at the

meeting. The sooner finished the better as it will give the asset more time to review and become

knowledgeable of the information contained before the rearranged meeting time. Along with a


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visual representation no bigger than 18 by 24 the client requests a written analysis for the

proposed premises including the specific information as follows

Parcel ID, Section Township Range

Parcel Address, if available

AreaPrice (value)

Comprehensive Plan Designation

Zoning Designation

Governance districts, utility school port parks fire library city limits

Distance from nearest saltwater shoreline

Distance to nearest commerce area (commercial zoned areas)

Name and distance to nearest 2 community facilities (excluding medical facilities)

Name and distance to nearest public park

Name and distance to nearest fire station

Name and distance to nearest law enforcement facilitySoil type and stability

The proposal is to be addressed to mr opportunity and hand delivered in the matter described

above with all the contents (including any supporting information) at the meeting in the

Seychelles March 15th 2014.


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...Analytical Outline

All datasets were downloaded from the www.kitsapgov.com/giswebsite, unzipped, and

shapefiles were placed into the TECD151_DATA folder. A file geodatabase (gdb) was created

151_FGDB in ArcCatalog and all the shapefiles were imported as feature classes into the new

file database using the import multiple feature classes option. Datatables were imported into151_FGDB using import multiple tables option. Having done all this the following feature classes

were selected to be used in the project cities (city boundaries), community (community facilities

* includes medical facilities), compplan (comprehensive development plan for kitsap county),

firedist (fire districts), firestat (fire stations), geohazard (geo hazard areas), lawenf (law

enforcement stations), parcels (tax parcel lots), parktype (parks), portdist (port districts), roadcl

(road centerlines), schooldist (school districts areas), outline (kitsap county outline), strpoly

(section township range in polygon format), wetlands (wetland areas), zoning (regulated zoning

designations for development). The following geodatabase tables from 151_FGDB were used

buildings (existing structures) and flatats (kitsap tabular data associated with land values, main

tax designations, and other attributes needed for development).Starting ArcMap a new project was created and entitled affordable_development_KC.

Save this file to the TECD151_PROJECT folder. Add to the project all the feature classes and

data tables mentioned in the previous paragraph. Right click on the parcels feature class in the

layer selection. Navigate and click on join tab. Select RP_ACCT_ID (tax ID number) as the field

to join from the parcels layer, buildings as the table to join it with, and RP_ACCT_ID (tax ID #)

as the field from buildings to base the join on, select keep all records. Validate the results and

click ok {94709 parcels containing structures or the property is already developed}. Select the

geoprocessing tab and open the Arcmap Modelbuilder. *The model makes assumptions that

other areas where the criteria will be run include datasets with the same information as these

feature classes and similar formatted files compatible with ESRI ArcCatalog and Map. Move theModelBuilder window to the center of the project to allow ready access to the layers of feature

classes on the left and geoprocessing tool search tab on the right. Save the model into the pre

determined gdb as affordable_development. From the search tab find Add Join (Data

Management) drag the tool into the model builder. Double click the white bubble with the tools

name fill the layer name with Parcels, input join field as RP_ACCT_ID (tax ID number), join table

as flatats (tax information), output join field RP_ACCT_ID (tax ID #). Click ok. Validate this

process by running the model to check results {130002 results joined}. Enter the search tab and

search for Select, drag the result with the exact syntax as the search nineteen times into model

builder. Double click the first white bubble Select enter Parcels(2) for the input feature class,

for the output rename the feature class dev_acre_size_A in the destination file gdb, write in

expression the SQL without parentheses [flatats.ACRES >= 1.5], click ok and validate results

{31944 parcels equal to or above 1.5 acres}. Double click the second white bubble Select

enter dev_acre_size_A for the input feature class, for the output rename the feature class

dev_acre_size_B in the destination file gdb, write in expression the SQL without parentheses

[flatats.ACRES


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500000], click ok and validate the results {15931 parcels available with an acquisition cost 25%

of the total sale of 10 units at 200,000$ a piece, or all values being below 500,000$}. Double

click the Select (4) white bubble enter dev_buymax_A as the input to the tool, changed the

output feature class name to dev_buymax_B, using SQL write the following expression

[flatats_ASSD_VALUE =

375000 AND building_IMPROV_TYP IS NULL]. The results in the attribute table should show no

values of ASSD_value above 375,000$ with any form of IMPROV_TYP ie structures field value

besides .

Entering into the search bar type Union (analysis). Drag the top result into the model

builder three times. Double click the first empty white bubble Union for the layers to unionize

select GeoHazards and Wetlands, rename the output dev_propertyrisks, click ok and run the

model to validate. Double click the Union (2) white bubble input dev_buymax_final anddev_propertyrisks feature classes in the input tab, change the output name to

dev_buyfinal_riskadded, run the model to validate this step and record results {29788 seperate

polygons which contain the properties proposed (15323), or include variables spatially from

Geohazards and Wetlands to make separate polygons (shared space)}. Double click the Select

(6) white bubble for the feature class to select from choose dev_buyfinal_riskadded, in SQL

type [FID_geohazard = 0 AND FID_wetlands = 0], rename the output to dev_buyfinal_norisks,

apply and run the model to validate data {13999 parcels that are within the proposed properties

and do not contain shared space with Geohazard or Wetlands polygons risk areas}. * To

manually check the validity of this data do the following geoprocessing using the intersect tool

inputs dev_buyfinal_norisks and dev_propertyrisks, name this feature class validtest1. results

should number 0 in the new attribute table.

Emergency services are considered hospitals urgent care centers and red cross centers

for the sake of the proposal. The criteria indicates all properties must be within 1 mile of an

emergency services facility. Start by double clicking the empty white bubble Select (7)" icon in

the model window for the input select the community features class, as an output rename the

feature class to dev_emergencyservices, using SQL write the following expression [TYPE =

'HOSPITAL' OR TYPE = 'URGENT CARE CLINIC' OR TYPE = 'RED CROSS'], ok the tool and


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run the model to check validity {11 results}. Open the search tab and type in the exact syntax

Buffer (Analysis) drag the geoprocessing tool into the model eight times then click on it select

the input as dev_emergencyservices, change the output location to the feature class name

dev_emergencyservices_buffer in the 151_FGDB gdb, leave all other options alone, change

the measurement tab from its current value to Miles, type in 1 in the linear unit tab, click okay and

run the model to create a buffer displaying a 1 mile direct radius around each emergencyservices location. In the search tab type Intersect (Analysis) move the geoprocessing tool by

dragging the words into the model seven times. Click the white empty bubble Intersect the

input features should be selected as dev_buyfinal_norisks and

dev_emergencyservices_buffer, the output feature class changed to

dev_buyfinal_norisks_esr (esr meaning emergency services range), then click ok run the

model and validate the results {850 parcels for proposed property development between 1.5 and

4 acres, fitting acquisition for eventual sale criteria, not in indicated risk areas of natural disaster,

within 1 mile of a healthcare facility}.

Click on the white bubble Select (8) set the input feature class to roadcl, in the output

rename the feature class dev_transportservices, write the following SQL expression inexpression tab [HIERARCHY


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be within 1 mile of a library. Select the Select (9) bubble for the input choose community

feature class *not associated with the model already, change the output to

dev_communication, type the SQL [TYPE = 'PUBLIC LIBRARY'], click ok then run this step of

the model. Double click Buffer (3) in the model window select dev_communication as the

input to buffer, change the output feature classes name to dev_communication_buffer, set the

measurement to miles and the linear units to 1, do not change any other selectable options, runthe buffer to create a 1 mile radius around each public library. Click on the Intersect (4) bubble

make the inputted feature classes dev_communication_buffer and dev_buy_esr_tsr_mwr,

rename the output dev_buy_esr_tsr_mwr_cwr (communication walking range), validate by

running the model to this point {155 results from 1.5 to 4 acres, meeting acquisition prices for

sale criteria, does not intersect with risk areas of natural disaster, within 1 mile of a healthcare

facility, within 600 feet of a public main road, within 20 minute walk of a park, also within 20

minutes on foot of a public library}.

Continuing to follow the pace of 1 mile per 20 minutes, supplies shopping must be within

1 mile of commercially zoned shopping areas. According to the metadata attached to the kitsap

county Zoning feature class, the North American Metadata metadata style text says severalzones encompass what can be considered shopping areas. Click the Select (10) empty white

bubble the feature class input should be chosen as Zoning, the output renamed to

dev_shopping, then type the following SQL in the expression tab [ZONE_DESCR = 'Business

Center' OR ZONE_DESCR = 'Business Park' OR ZONE_DESCR = 'Highway/Tourist

Commercial' OR ZONE_DESCR = 'Keyport Village Commercial' OR ZONE_DESCR =

'Manchester Village Commercial' OR ZONE_DESCR = 'Mixed Use' OR ZONE_DESCR =

'Neighborhood Commercial' OR ZONE_DESCR = 'Regional Commercial' OR ZONE_DESCR =

'Rural Commercial' ], click ok and run the model to validate the selection. Double click the empty

white bubble Buffer (5) select dev_shopping feature class as the input to buffer, change the

output name to dev_shopping_buffer, change the measurement to miles and the linear units to1, do not change any other options, run the buffer to create a 1 mile radius around zones

considered shopping areas. Click Intersect (5) input the feature classes dev_shopping_buffer

and dev_buy_esr_tsr_mwr_cwr, rename the output dev_buy_esr_tsr_mwr_cwr_swr

(shopping walking range), run the model to validate the data and record results {90 results of

parcels for proposed property development that are between 1.5 and 4 acres, meet the

acquisition prices for sale criteria, doesnt overlay areas of risk to natural disaster, within 1 mile

of a healthcare facility, within 600 feet of a public main road, within 20 minute walk of a park,

within 20 minutes on foot of a public library, and a 20 minute walk from local shopping areas}.

The area around Kitsap County is surrounded by water on three sides, producing a buffer

around the outline of the county will create a non variable fourth side . For this proposal special

accommodations will be needed to change the model to further fit the criteria for other target

areas of development. But for the purposes of this model using the outline as a source of

saltwater shorelines is a fair assumption. It is also for this reason building the shoreline criteria is

one of the last steps in the model, to be easily edited at a later date. I am allowed to make this

assumption because the area around the land bound side of kitsap county does not fit any of the

other criteria needed for property development. Criteria indicates property must be within a 10

minute walk from the a saltwater shoreline. According to the assumptions made above regarding


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average human walking speeds, this would mean proposed developments would have to be .5

miles or 2640 feet. Begin to select property for the proposal in this range by clicking Buffer (6)

bubble for the input layer to buffer choose Outline, rename the output dev_beachwalk, leave

the measurement unit feet and input 200 into the linear unit tab, change the side value to outside

only, click ok then run the model to produce a small buffer around the outline. Click the Buffer

(7) empty white bubble as the feature class dev_beachwalk should be chosen for the input,change the output name to dev_beachwalk_halfmile, leave measuring in feet and input 2640

into the linear unit number selection, click ok then run the model to produce a 2640 buffer from

the saltwater shoreline of Kitsap County *plus one land bound side. Click on Intersect (6) for

the intersecting feature classes use dev_buy_esr_tsr_mwr_cwr_swr and

dev_beachwalk_halfmile, rename the output feature class to

dev_buy_esr_tsr_mwr_cwr_swr_bwr (beach walk range), click ok and run the model to

validate this step {61 results of parcels for proposed property development that range from 1.5 to

4 acres, do not exceed and meet criteria of acquisition, does not intersect areas of risk to natural

disaster, is within 1 mile of a healthcare facility, 600 feet from a public main road, within 20

minute walk of a park, within 20 minutes on foot of a public library, a 20 minute walk from localshopping areas, and only a 10 minute walk from a saltwater shoreline}

No property in question should be commercially zoned for it to be considered for

development as the development proposed is a residential affordable housing. To remove

proposed development areas that are considered commercial zoned the following procedure

should be enacted. Double click the Select (11) white bubble as the input layer use a non

processed Zoning feature class, change the output name to dev_shopping, type the SQL

expression [ZONE_DESCR = 'Business Center' OR ZONE_DESCR = 'Business Park' OR

ZONE_DESCR = 'Highway/Tourist Commercial' OR ZONE_DESCR = 'Keyport Village

Commercial' OR ZONE_DESCR = 'Manchester Village Commercial' OR ZONE_DESCR =

'Mixed Use' OR ZONE_DESCR = 'Neighborhood Commercial' OR ZONE_DESCR = 'RegionalCommercial' OR ZONE_DESCR = 'Rural Commercial' ], click ok and run this step. Select the

Union (3) empty white bubble for the union inputs select dev_buy_esr_tsr_mwr_cwr_bwr and

dev_shopping (3), change the name of the output feature class to dev_final_A, run this

geoprocess to validate this part of the model. This joins the parcels from dev_buy_esr... and

dev_shopping (commercially zoned areas) to show the parcels that also contain commercially

zoned areas. Double click Select (12) for the input choose dev_final_A, output feature class

rename to dev_final_B, for the SQL expression type [ZONE_DESCR = ''], click ok and run the

step to validate this part of the model {41 parcels for proposed property development that range

1.5 to 4 acres, do not exceed and meet criteria of acquisition, does not intersect areas of risk to

natural disaster, is within 1 mile of a healthcare facility, 600 feet from a public main road, within

20 minute walk of a park, within 20 minutes on foot of a public library, a 20 minute walk from local

shopping areas, 10 minutes walking to a saltwater shoreline, and the area is not commercially

zoned for development}.

Reviewing the results showed some parcels had a value of 0 and also were deemed non

developable for various reasons. To remove these from the proposed properties for development

start by clicking the Select (13) white bubble for the input select the dev_final_B feature

class, create the output to be dev_final_C, type the SQL expression [ASSD_VALUE > 0], ok the


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selection and run the model to validate {34 parcels for proposed property development ranging

1.5 to 4 acres in size, meet the criteria of acquisition prices, within a mile of healthcare facilities,

600 feet from public main roads, a 20 minute walk to a park library shopping areas, 10 minutes

walking distance to shorelines, all zoned as residential development, and parcel data does not

include a 0 value for the assessed value}

Many of the resulting parcels have structures currently built on them. To hastendevelopment of the proposed properties it could be beneficial to remove those parcels from the

proposed properties. To do so begin by clicking on the Select (14) white bubble as the input

feature class select dev_final_C, change the outputs name to dev_final_D, type

IMPROV_TYPE IS NULL into the SQL expression tab, click ok then run the model to validate {13

parcels 1.5 to 4 acres in size, meet the criteria of aquisition prices, within a mile of healthcare

facilities, 600 feet from public main roads, a 20 minute walk to a park library shopping areas, 10

minutes walking distance to shorelines, all zoned as residential development, the parcel data for

proposed properties does not include a 0 value for the assessed value, and the parcel data for

proposed development has no existing standing structures}

To begin to validate the 13 parcels results it is necessary to produce feature classes withsome of the datasets associated with various distances for the proposal. By creating a mile

buffer around the remaining parcels these feature classes can be easily created, measure the

distance from the 13 parcels, then parcels with values of error can be removed (distances above

5280 feet ie 1 mile ie 20 minutes walking distance), and the results can be furthered ratified for

accuracy and the clarity of this proposal. Double click the empty white bubble in the model

Buffer (8) select the input to be buffered as dev_final_D, leave the measurement in feet and

change the linear unit to 5280, change the output feature class name to dev_final_D_1miR (1

mile range), do not change any other selection options, run the buffer to create a 1 mile radius

around each proposed development. Next enter the search tab. Search Select Layer by

Location, drag the result 5 times into the Affordable Housing model. Click select layer bylocation white bubble select firestat as input layer, relationship intersect, selecting feature

from dev_final_D_1miR, click ok and run the model. Click Select (15) input processed

firestat (2), ouput name dev_firestat_1miR, SQL expression [OBJECTID > 0] (selects all).

Click Select Layer by Location (2) input lawenf as feature class layer, relationship intersect,

select features from dev_final_D_1miR, click ok run the step. Click on Select (16) input

processed lawenf (2), output dev_lawenf_1miR, expression tab SQL [OBJECTID > 0]

(selects all). Click Select Layer by Location (3) input parktype as feature class layer,

relationship intersect, select features from dev_final_D_1miR, click ok run the step. Click on

Select (17) input processed parktype (2), select features from dev_parktype_1miR,

expression tab SQL [OBJECTID > 0] (selects all). Click the Select (18) white bubble change

the input to an non geogrocessed community feature class, change the output to

dev_libraries, type the SQL expression [TYPE = LIBRARY], click ok to run the selection.

Double click Select Layer by Location (4) input processed dev_libraries (2), relationship

intersect, select features from dev_final_D_1miR, click ok to run the model. Click on the

Select (18) white bubble for the feature class to select from choose dev_libraries (3), change

the output to dev_libraries_1miR, type the SQL expression [OBJECTID > 0] (select all). Run all

these processes individually to produce feature classes with all point layers associated with


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Model PNG (zoomable in PDF format)

final project intermediate gis; project description and analysis outline

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