2010 Fall 406 Final Project Location Suitability Analysispl273965/406/RichL_Poster.pdf · 2010 Fall...
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New Burger stores in San Fernando Valley I. Introduction II. Data IV. Results III. Methods PO CHUN (RICH) LEE 2010.12.06 2010 Fall 406 Final Project Location Suitability Analysis In-N-Out Burger is the most famous burger chain store in South West America. Established in 1948 at Baldwin Park, CA, In-N-Out nowadays has more than 250 stores. Besides, it is still expanding. In Fact, In-N-Out is going to open two more stores in Costa Mesa, CA and Phoenix, AZ in the end of 2010. This project assumed that In-N-Out intends to serve more customers in San Fernando Valley, CA, so the com- pany needs to find a new store location. Since there are too many factors may affect the decision, In-N-Out decided to apply Location Suitability Analysis method in GIS to make sure that their new store could locate in a suitable place. In this project, the following data had been used: 1. Current In-N-Out locations: Download from The official website: www.in-n-out.com 2. San Fernando Valley: ESRI US Street Map (copy form Geography Data Drive) -------(Including Background data, Census data, Highway data) 3. Land use Data: Copy from Geography Data Drive Location suitability analysis is an analysis method that overlaps different data and transfers them into a scale. After sum up those scores from different layers, the places have higher score are considered as better locations. This project picks the following factors to analyze the new location: A. Existing stores: a new location should have certain distance from existing locations that they will not compete with each other. B. Highway: An In-N-Out store is usually close to a highway exit so people could easily pass by. C. Land use type: It is better to build a store in commercial place than park or agricultural land. D. Census (Age) data: this project set those target customers are ages from 18 to 39. Before applying the analysis, all the data have to convert into Raster data with the same cell size. Hence, pre-process all the data is necessary. A. In-N-Out Locations: Buffer all the locations with 0.5 mi radius from 0.5 to 3.5 miles. B. Highway data: Select those highways in the study area (I-5, I-405, I-210, US-101, SR-118, SR-170) C. Land use type: Classify different land use type into 1 to 10 scale. (agriculture and government places are 0~3; residential places are 5; commercial places are 10) D. Census data (Age): Reclassify the population from age 18 to 39 into 10 groups. After pre processing, In-N-Out locations and Highway data need to be calculated with distance. The “Euclidean Distance” tool, hence, is a good method to apply. Since it outputs as a raster format, both Land use type and Census data need to be convert into raster with the same cell size too. After that “Reclassify” tool is applied to convert all the raster data into 1 to 10 scale, so the overlap will be done under the same conditions with each data layers. Due to the different data have different influence, the score is sum up by a weight that Existing location is 40%, Highway is 30%, Age is 20%, and Land use type is 10%. After applying “Weighted Overlay” tool, all the cell with highest score are potential places to be chose. However, since the results are still too much, those places were filtered by “Majority” tool to make sure the places are larg e enough. Besides, only those places that really close to highway (within 0.2 mi) are suggested to In-N-Out company. The final output are three different places located in the east of the study area. Those places are around I-5 and I-210 in SF valley. Due to the less of factors, it is hard to have only one optimal site. However, those three locations are still some good suggestions that In-N-Out burger could start to do some more research about. If there could have more elements added into analysis, the result will be better. The analysis of location suitability is a good method to support the decision maker and it could be applied into a wide range. Those analysis methods could be combined into a “Spatial Decisi on Support System”, in which could help the decision maker to find a better solution that is based on the latest updated geographical information data .
Transcript of 2010 Fall 406 Final Project Location Suitability Analysispl273965/406/RichL_Poster.pdf · 2010 Fall...
New Burger stores in San Fernando Valley
I. Introduction II. Data
IV. Results
III. Methods
PO CHUN (RICH) LEE 2010.12.06
2010 Fall 406 Final Project
Location Suitability Analysis
In-N-Out Burger is the most famous burger chain
store in South West America. Established in 1948 at
Baldwin Park, CA, In-N-Out nowadays has more than 250
stores. Besides, it is still expanding. In Fact, In-N-Out is
going to open two more stores in Costa Mesa, CA and
Phoenix, AZ in the end of 2010.
This project assumed that In-N-Out intends to serve
more customers in San Fernando Valley, CA, so the com-
pany needs to find a new store location. Since there are
too many factors may affect the decision, In-N-Out
decided to apply Location Suitability Analysis method in
GIS to make sure that their new store could locate in a
suitable place.
In this project, the following data had been used:
1. Current In-N-Out locations: Download from The official website: www.in-n-out.com
2. San Fernando Valley: ESRI US Street Map (copy form Geography Data Drive)
-------(Including Background data, Census data, Highway data)
3. Land use Data: Copy from Geography Data Drive
Location suitability analysis is an analysis method that overlaps
different data and transfers them into a scale. After sum up
those scores from different layers, the places have higher score are considered as better locations.
This project picks the following factors to analyze the new location: A. Existing stores: a new location
should have certain distance from existing locations that they will not compete with each other.
B. Highway: An In-N-Out store is usually close to a highway exit so people could easily pass by. C. Land use type: It is better to build a store in commercial place than park or agricultural land.
D. Census (Age) data: this project set those target customers are ages from 18 to 39.
Before applying the analysis, all the data have to convert into Raster data with the same cell size. Hence, pre-process all the data is necessary.
A. In-N-Out Locations: Buffer all the locations with 0.5 mi radius from 0.5 to 3.5 miles. B. Highway data: Select those highways in the study area (I-5, I-405, I-210, US-101, SR-118, SR-170)
C. Land use type: Classify different land use type into 1 to 10 scale. (agriculture and government places are 0~3; residential places are 5; commercial places are 10)
D. Census data (Age): Reclassify the population from age 18 to 39 into 10 groups.
After pre processing, In-N-Out locations and Highway data need to be calculated with distance. The “Euclidean Distance” tool, hence, is a good method to apply. Since it outputs as a
raster format, both Land use type and Census data need to be convert into raster with the same cell size too. After that “Reclassify” tool is applied to convert all the raster data into
1 to 10 scale, so the overlap will be done under the same conditions with each data layers. Due to the different data have different influence, the score is sum up by a weight that
Existing location is 40%, Highway is 30%, Age is 20%, and Land use type is 10%. After applying “Weighted Overlay” tool, all the cell with highest score are potential places to be chose.
However, since the results are still too much, those places were filtered by “Majority” tool to make sure the places are large enough. Besides, only those places that really close to
highway (within 0.2 mi) are suggested to In-N-Out company.
The final output are three different places located in the east of the study area. Those places are around I-5 and I-210 in SF valley.
Due to the less of factors, it is hard to have only one optimal site. However, those three locations are still some good suggestions that In-N-Out burger could start to do
some more research about. If there could have more elements added into analysis, the result will be better. The analysis of location suitability is a good method to support
the decision maker and it could be applied into a wide range. Those analysis methods could be combined into a “Spatial Decision Support System”, in which could help the
decision maker to find a better solution that is based on the latest updated geographical information data .
