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Spatial-Analysis-Real-Estate-Development-Company

Analysis question: Should the development company build a small mixed-use development in the municipality of Gresham?

Introduction

I'm acting as a market analyst for a local development company. The company is currently trying to find out the optimal sites where it can build small mixed-use developments. The local company wants to build in a city that has large amount of land already zoned for mixed-use development, and also the company targets on people in their 20s and 30s for both the retail and the rental purpose.

Ask Questions

In the case study, I'm going to determine key information about the city:

  1. How much area is zoned for mixed-use development?
  2. Where are high rental areas?
  3. Where do high numbers of people between the ages of 22-39 live in high rental areas?

Analyze and Explore data

Step 1: Filter data to limit feature display

The first step is to filter the Gresham Zoning layer to display only the areas zoned for mixed-use development on the map. I used OR logical to find area that meet the filter creteria: Both Office Mix-use Residential (MUC1) and Downtown Mix-use Residential (MUC2) Check the below map, and these areas are symbolized with pink or maroon.

MUC1 and MUC2

Step 2: Examine statistics

In this step, I'm going to answer How much area is zoned for mixed-use development? I used Information in the feature table and found out that slightly over 517 acres meet the criteria in either MUC1 or MUC2.

information

Step 3: Enrich Block Group layer by adding attribute information

I applied Analysis in the Setting toolbar and by adding enrichment variables in the Block Group, I successfully added 2023 Renter Occupied HUs attibute in the layer.

Addting attribute to layer

Step 4: Calculate field

The development company also wants to determine how many young people btween 20s and 30s reside within these block groups. Since the data was seperated in two columns AGE_22_29 and AGE_30_39, I need to sum the number together by adding a new column AGE_22_39 to this attribute table.

addting new column to attribute table

Analyze and Model

Apply labels

In order to make the map more informative, I decided to apply labels to the Enriched Block Group Renters layer. It's now easily to view the population of people between the age of 22-39 for each block group.

AddingLabels

Analysis by Visualization

From information of 2023 Renter Occupied HUs field in attribute table, we've seen that the block groups have an average over 394 number of rental units. Then, I added an expression in Style to get a more effective visualization of rental housing. This graph also explains question that Where do renters live within the city?

You can find that most rentals are found in block groups closer to the city center in Gresham or northwest of the city center.

RENTER_CY > 394

In the Style under the setting tool, I added an expression that display the block group if the number of rental units is over 394 and dislay its percentage of the population between 22-29 years old

Above 394 block group with percentage

The map above shows only the block groups that have an above average number of rental units. It also answers the question: Where do high numbers of people between the ages of 22-39 live in high rental areas? The gardient symbology with darker blue indicates a greater percentage of people aged 22-29 lives in around the city center and in the northwest area of the municipality.

Then, turn on the visibility of Gresham Zoning Layer with existing mixed-use development area.

with mixed used development

The generated maps helps in finalizing the optimal locations for the local development company to constrct small mixed-used developments in Gresham. This is achived by focusing on block group with an above average number of rental properties, a higher percentage of renters aged 22-39, and closer to the existing mixed-use development.

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Should the development company build a small mixed-use development in the municipality of Gresham?

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