Geospatial Analytics enables one to draw attention to the location aspects of the features or attributes in question for the analysis. It provides additional information that enables better decision-making. For our assignment on Geospatial story telling, we have considered the classic case of accommodation hunt for NUS students and performed the Analysis in ArcGIS.
Objective: To find a suitable location for student profiles with all the basic amenities and needs within their reach
The students have been classified into 3 profiles:
i) The Nerd – prefers an affordable living near University and does not commute much
ii) The Explorer – loves to explore the city, prefers to participate in recreational activities and travels a lot
iii) The Nerdy Explorer (Their combination)
i) Students Commuting Data
ii) Singapore Population Data
iii) Singapore Accommodation Pricing Data
iv) Location of Basic Amenities: Library, Hawker Centre, Fire station and Police Station
v) Location of Recreational Amenities: Community Centre, Sky Greenery, Museum, Park
We started with the Singapore topographic map overlayed with MRT Line as our General Purpose Map. NUS location data was added using its Geo Coordinates as we essentially want our profiles to live within close proximity to the University.
The residential areas in Singapore have been identified and a Thematic choropleth map was used to visualize based on population. The outskirts are more crowded and the population size decreased as we move to the center of the city
Similarly the residential areas were visualized by pricing. The pattern here is reversed. The city center is more expensive and the price decrease as we move to the out skirts.
Locational Pricing MapNote: The area in grey are Non- residential zones (either industrial area or office spaces).
The Basic amenities were represented as vector points. It includes Library , Hawker Centre, Fire Station and Police station. Library and Hawker Centre were places of daily visit for students while Fire station ad police station are general safety requirements in any neighbourhood
1km buffer was drawn around them which will later be intersected. The intersection indicates the locations which are at close proximity to all amenities.
Hawker Centre Buffer
Fire Station Buffer
Police Station Buffer
The 1km buffers were then intersected to identify potential locations for students stay.
Basic Amenities Intersection
Similar steps were followed for Recreational Amenities
Recreational Amenities Intersection
Student commuting data was added to the Map to understand the commuting pattern of Students and their spread around Singapore. From the map we gather that most students travel via MRT and we will take into account this information when identifying the ideal accommodation for our profiles.
ArcGIS Tools Used:
i) Spatial Statistics Tools -> Mapping Clusters -> Optimised Hot Spot Analysis
ii) Spatial Statistics Tools -> Measuring Geographic Distance -> Mean Centre
iii) Spatial Statistics Tools -> Measuring Geographic Distance -> Standard Distance
iv) Directional Distribution -> Measuring Geographic Distance -> Directional Distribution
Optimized Hot spot analysis was done to identify hot spots were students are concentrated. Red colored regions indicate regions of hot spot. We note that most students are concentrated around Kent Ridge (which we assume is because students frequent NUS often)
Optimized Hot Spot Analysis
Hot Spot Analysis – Removing Data Points
The geographic Mean of the commuting data was taken to identify the optimal location for stay in terms of distance from all the commuted points. With the mean as centre and one standard deviation as radius the circle (dark purple) was drawn indicating the boundary or maximum limit where we want our profiles to stay. To provide some orientation to the boundary we have also created standard deviational ellipse (Light Purple).
Having identified the geographical limits of our objective we overlayed the Basic Amenities intersection Map with Boundary Map to eliminate the regions that fall outside our boundary (Eg Jurong East and Hougang)
Overlay 1- Boundary Map and Basic Amenities Intersection Map
We then overlay the Recreational Amenities intersection Map with the Boundary Map and eliminate Yio Chu Khang and Hougang for similar reasons
Overlay 2 – Boundary Map and Recreational Amenities Intersection Map
We finally overlay all the intersection and pricing information into a single map. From the Map we observe that Clementi, an affordable living, is an ideal location for the Nerd Profile, Bouna Vista (with many recreational opportunities) for the Explorer and Pasir Panjang for the Nerdy Explorer.
Most of the students searching for accommodation would have probably intuitively considered several of the amenities mentioned in our assignment and the proximity of the amenities to their accommotdation as a major criteria in selecting their accommodation. In this assignment we have utilised an analytic approach using travelling hot spots and standard distances to identify the best location in terms of accommodation for different students based on their interest. The scope of the study can be extended further by including more amenities, student profile and considering optimal travel options for the students
Presentation Link:Click Here
Abhinaya Murugesan [A0163311W]
Allen Geoffrey Raj [A0163398R]
Kavya AK [A0163250R]
Preethi Jennifer R [A0163190L]
Ram Nagarajan [A0163247E]