Hotel Location Analysis using ArcGIS

Transcription

1 Hotel Location Analysis using ArcGIS Yang Yang Department of Geography University of Florida

2 Outline Introduction Background Data Source Research Methodology Preliminary Result

3 Introduction Location! Location! Location! Especially true for service industry Agglomeration effects are evident in hotel location. Different location preference for hotels in the U.S and China?

4 Outline Introduction Background Data Source Research Methodology Preliminary Result

5 Background We choose two cities for studies. They are famed with distinguished amusement park attractions~ Orange County (Great Orlando area), Florida. (The City Beautiful) Shenzhen City (Great Shenzhen area), Guangdong. (The City of Ambition)

6 Background

7 Research Question How do hotels distribute in the two cities? Does different hotels have different preference for location? What factors contribute to hotel location?

8 Outline Introduction Background Data Source Research Methodology Preliminary Result

9 Data Source Orlando Data: Florida Geographic Data Library (FGDL): road and lodging facility data of Florida Orange County GIS Database: Zipcode area data, Airport data. Orlando City GIS Program: Landmark data Shenzhen Data: Dept. of Geography, Univ. of Nanjing

10 Hotel location in Orange County Legend CONDOMINIUM HOTEL MOTEL Highways Orange County Boundary 0 5,000 10,000 15,000 20,000 Meters Created by Yang Yang Dept. of Geography Univ. of Florida 12/01/2010 Projection: Albers Conical Equal Area

11 Hotel Location Map of Shenzhen type2 hotel type1 hotel type0 hotel Inner_roads Express roads Shenzhen City Created by Yang Yang, 12/04/ Kilometers

12 Outline Introduction Background Data Source Research Methodology Preliminary Result

13 General Projection Skills Geodatabase design Map design Merge feature Distribution description Point density Extraction K-function Eclipse Nearest neighbor analysis Agglomeration analysis Buffer analysis Clip Frequency analysis Regression analysis Spatial join Near Regression analysis Functions Make all layers in the same projection Organize all project data in geodatabase for Orlando and Shenzhen respectively. Create location maps for hotels Union of line features To visualize hotel location Extract the point density (raster data) by mask To quantify the agglomeration of different hotels Compare the spatial distribution (direction and dispersion) Detect the agglomeration of location To measure the proximity of hotels to major roads, parks and airports. To general hotels within the buffering area To get frequency of hotels in different buffers Count number of hotels in different zones Find the nearest distance of hotels to parks Estimate each factor s contribution to hotel location

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15 Research Methodology

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17 Research Methodology Hotel layer Spatial join Park layer Near Zone_reg Airport layer Road layer Near Spatial join Regression analysis Estimated coefficient table

18 Research Methodology

19 Outline Introduction Background Data Source Research Methodology Preliminary Result

20 Point Density of Hotel Location Density for condominums Density for motels Density for all categories 0 12,500 25,000 50,000 75, ,000 Feet FCreated by Yang Yang, Dept. of Geography, UF, 12/02/2010 Density for hotels

21 Point Density of Hotels in Shenzhen Preliminary Result Low-level hotels Middle-level hotels All hotels F Kilometers Created by Yang Yang, 12/04/2010 High-level hotels

22 !! Hotel location in Orange County with Standard Deviational Ellipse MOTEL Legend CONDOMINIUM HOTEL MOTEL Highways Orange County Boundary! Ellipse HOTEL Ellipse CONDOMINIUM Ellipse 0 5,100 10,200 15,300 20,400 Meters Created by Yang Yang Dept. of Geography Univ. of Florida 12/01/2010 Projection: Albers Conical Equal Area

23 Preliminary Result

24 Preliminary Result Orlando Buffer Condominium Hotel Motel 1km 34.82% 33.93% 31.25% 2km 36.05% 37.21% 26.74% 3km 41.60% 34.20% 24.20% 4km 41.86% 33.72% 24.42% 5km 42.00% 33.90% 24.11% Orlando Buffer Condominium Hotel Motel 1km 6.25% 81.25% 12.50% 2km 14.86% 58.11% 27.03% 3km 46.70% 34.62% 18.68% 4km 41.31% 40.85% 17.84% 5km 55.18% 31.93% 12.89% Shenzhen Buffer low-level middle-level high-level 1km 65.71% 23.82% 10.47% 2km 69.08% 20.68% 10.23% 3km 70.69% 19.80% 9.50% 4km 71.37% 19.47% 9.16% 5km 71.43% 19.43% 9.14% Shenzhen Buffer low-level middle-level high-level 1km 50.00% 16.67% 33.33% 2km 64.29% 14.29% 21.43% 3km 62.50% 12.50% 25.00% 4km 60.53% 23.68% 15.79% 5km 64.58% 20.83% 14.58% Major Roads Amusement Park

25 Preliminary Result

26 Thanks you!