G2-Group08 Proposal

Project Motivation

As part of our module, Geographic Information Systems for Urban Planning, we are collaborating with an international food chain to analyse 15 trade areas located in Taiwan's Kaohsiung and Ping Tung region as shown in the image below. The international food chain currently uses manual methods of delineating their trade area which is largely time consuming. Therefore we aim to propose new and faster methods using QGIS to delineate the trade area. We will also be analysing the points of interest (POI) within each trade area to determine the correlation between the POIs and sales revenue. To do so, we will be using simple and multiple linear regression analysis. The results of this project will provide the international food chain with the necessary geographic data analysis to make an informed decision regarding their sales and marketing strategy.

About Kaohsiung and Ping Tung

Kaohsiung is a port city located in Southern Taiwan. It has a population of 2,770,000 people. Sitting between Cijin Island and downtown, Port of Kaohsiung is a world-class port in Taiwan as well as a hub for international trade. The ceaseless ships and containers from around the world represent the energy and vitality of the business in Kaohsiung. Ping Tung county is a county also located in Southern Taiwan. It is the fifth-largest county in Taiwan. It is well known for its top attractions such as Kenting National Park and Ngoluanpi Park. Ping Tung also has some of Taiwan's best natural attractions such as amazing beaches, mountains and farmlands.

Project Objectives

There are two main objectives of this project: 1. To find the most suitable and efficient trade area delineation method 2. To analyse and generate insights into the current trade areas with respect to the selected points of interest and sales revenue

Data

Geospatial Data

Name	Description	Geographic Representation	Data Format	Source	Used in
Taiwan Stores	Contains store locations allocated to each group	Point	Geopackage	Professor Kam, Client	Allocation of Stores, Trade area delineation methods
*Administrative Boundaries*
County MOI	Contains boundaries by county	Polygon	ESRI Shapefile	Client	Trade area Digitisation
Town MOI	Contains boundaries by town	Polygon	ESRI Shapefile	Client	Trade area Digitisation
Village MOI	Contains boundaries by village	Polygon	ESRI Shapefile	Client	Trade area Digitisation
*Points of Interest*
Business	Businesses in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
CommSvc	Community Service Facilities in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
EduInsts	Educational Institutions in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
Entertn	Entertainment places in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
FinInsts	Financial Institutions in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
Hospital	Hospitals in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
MiscCategories	Miscellaneous facilities in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
ParkRec	Parks and Recreational areas in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
Restrnts	Restaurants in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
Shopping	Shopping centres in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
TransHub	Transporation hubs in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
TravDest	Travel Destinations in South Taiwan	Point	ESRI Shapefile	Client	Sales Revenue Analysis
*Store Sales*
Store Sales Data	Revenue from sales by POD Code	NIL	CSV	Client	Sales Revenue Analysis

Location Maps

The location maps were used as a reference when digitising the operational trade area.

Name	Description	Data Format	Source	Used in
CK-20190624寬109cm長130	Location Map for trade area Shih Chuan, Kaohsiung County	Powerpoint	Client	Trade area Digitisation
JK-20190314寬83高72(木)含框	Location Map for trade area Jiangong, Sanmin District, Kaohsiung City	Powerpoint	Client	Trade area Digitisation
KS20190823(外送範圍)	Location Map for Kang Shan Town, Kaohsiung County 820	Powerpoint	Client	Trade area Digitisation
LJ-20171030寬89高120(木)含框	Location Map for Lujhu District, Kaohsiung City	Powerpoint	Client	Trade area Digitisation
NZ地圖.jpg	Location Map for Nan Zi, Kaohsiung	Powerpoint	Client	Trade area Digitisation
NJ-20150902寬100高90(木)	Location Map for Nanzih District, Kaohsiung City	Powerpoint	Client	Trade area Digitisation
PM-20171124寬84高76(鋁)	Location Map for Ming Shan Road, Pintong	Powerpoint	Client	Trade area Digitisation
PZ-20171215寬82高76(鋁)	Location Map for Ping Tung Zhong Zheng	Powerpoint	Client	Trade area Digitisation
QD-20180913寬80高100(木)	Location Map for Qie Ding District, Kaohsiung City	Powerpoint	Client	Trade area Digitisation
RM-20190107寬110高110(木)含框	Location Map for Renwu District, Kaohsiung City	Powerpoint	Client	Trade area Digitisation
RZ-20190314寬90高119.7(木)含框	Location Map for Zuoying District, Kaohsiung City	Powerpoint	Client	Trade area Digitisation
TS-20190624-鋁-寬65高80	Location Map for Tso Ying Delco, Kaohsiung	Powerpoint	Client	Trade area Digitisation
UC-20171226寬70高90(鋁)	Location Map for Yen Cheng District, Kaohsiung City	Powerpoint	Client	Trade area Digitisation
ZH-20190527寬90高88.8(鋁)含框	Location Map for Gushan District, Kaohsiung City	Powerpoint	Client	Trade area Digitisation
ZY	Location Map for Tsoying Zi Yo, Kaohsiung	Powerpoint	Client	Trade area Digitisation

Scope of Work

1. Digitising the existing Trade Area
We would need to digitise the existing hand-drawn trade area by referring to the location maps given

2. Extracting Points of Interest
We would need to extract the points of interest from the shapefiles given.

3. Trade Area Delineation method (Buffer)
We would need to delineate 2.5km, 3km and 3.5km buffers and analyse whether it would be a suitable replacement method.

4. Trade Area Delineation method (Drive Time)
We would need to delineate 15 minutes drive time boundary using QGIS' QNEAT function.

5. Sales revenue analysis
We would need to analyse the sales revenue namely bills, total revenue and average bills to find the correlation between sales and points of interest or other factors such as population.