Project Groups

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Claraview.png IS415 GeoSpatial Analytics and Applications

About

Weekly Session

Take-home Exercises

Geospatial Analytics Project

Course Resources

 



Team Name Project Title Project Description Project Artifacts Members Sponsor or potential users
GeoSpies

Project Title

Abstract (Note: Not more than 350 words)

Group Member: Student001, Student002, Student003
GeoSpies

Project Title

Abstract (Note: Not more than 350 words)

Group Member: Student001, Student002, Student003
GeoSpies

Project Title

Abstract (Note: Not more than 350 words)

Group Member: Student001, Student002, Student003
GeoSpies

Project Title

Abstract (Note: Not more than 350 words)

Group Member: Student001, Student002, Student003
Dangy

Project Title

This project would analyse the various factors which influence the spread of dengue across difference regions of Taiwan. This includes studying the occurrence of dengue cases against factors which encourage breeding of dengue mosquitos: demographic spread, population density, weather and climate and dengue-prone locations such as water protection areas and industrial district.
Through identification of hotspots and studying the transmission of dengue over time, this project will help us better understand patterns and discover strategies on how to curb with epidemics in future & steps to prevent in Taiwan.

Group Member: Ang Kah Eng
Jerry Obadiah Tohvan
Tan Kai Xiang Terence
Elec3city

Project Title

Abstract (Note: Not more than 350 words)

Group Member: Darren Choy, Fu Yu, Silvester Lim
GeoSpies

Project Title

Abstract (Note: Not more than 350 words)

Group Member: Student001, Student002, Student003
WhereYouGeoLogo.png
WhereYouGeo
Visualizing Public Transport Passengers Movement

As more Singaporeans are opting to take public transport for day to day trips, being able to understand the trip patterns of Singaporeans can help to identify interesting insights and these patterns can be used to help improve the environment of Singapore example: building more elderly friendly facilities, more buses services when school is over, etc. Our project aims to provide an application that will help various government sectors like HDB, URA, SLA and LTA to enable better planning and decision making where it will eventually impact Singaporeans in the future.

Group Members:

Chan Huang Suan
Vincent Koh How Han
Yeo Qin Ying Sheryl

GeoSpies

Project Title

Abstract (Note: Not more than 350 words)

Group Member: Student001, Student002, Student003
BURP Logo.png
BURP

Balancing Urban Residential Plannings

In recent years, the Ministry of Education (MOE) has been appointing new mergers between schools and relocating them. These schools include primary schools, secondary schools as well as junior colleges. The merging and relocation of schools would mean lesser schools in each neighbourhoods. This would affect the students' accessibility to certain schools, especially those in primary schools where parents need to send their children to schools. With more upcoming mergers of school by MOE, it is important for the government and schools to know the inconvenience in terms of time and distance travelled caused by the mergers and implement measures to ensure that these areas have better accessibility. Thus, our team aims to identify the HDB residential areas that are affected due to the merger of schools.

Group Member: Brendo Austin, Tan Peng Chong, Goh Li Na Rebecca
GeoSpies

Project Title

Abstract (Note: Not more than 350 words)

Group Member: Student001, Student002, Student003
EzModellogo.png
EzModel

Geographically Weighted Modelling Tool for HDB Resale Prices

In recent decades, modeling housing prices has become a hot topic among economists, planners, and policymakers due to the significant role of properties in household wealth and national economy. In Singapore, public housing accommodates more than 80% of its citizens and citizens either choose to buy a new Housing Development Board (HDB) flat or purchase a HDB resale flat, second-hand flats with less than 99 years left on the lease.

Our project will focus on modelling the HDB resale flat prices which are shaped by market forces. As many previous hedonic pricing models that uses linear regression fails to take into account spatial variations among the observations in the local surroundings, our project will be building a modeling tool based on the geographically weighted regression (GWR) model to analyse the effects of spatial variation on housing prices. Our application will provide users with the option of using a mixed geographically weighted model to account for both local and global variables. At the same time, users can also choose to upload a geo-coded data set if they wish to include new spatial attributes into the GWR model. We hope that this modelling tool will help users more accurately investigate the impact of variables on HDB resale flat prices in Singapore.

Group Members:

Lim Yan Hong, Patrick
Shi Jianrong
Daniel Chin Wen Kai

Team Members
Renting Inequality Shubham Periwal Yunying Kaelyn Raynie Moo - - -
BURP Tan Peng Chong Brendo Austin Goh Li Na Rebecca - - -
Elec3city Darren Choy Fu Yu Silvester Lim - - -
WhereYouGeo Chan Huang Suan Sheryl Yeo Vincent Koh - - -
Signal Ang Jia Ying Sheryl Chong Man Er Tan Yan Lin - - -
Neighbourhood WatchDocs Debbie Lee Shan Ying Goh Chun Ming Tan Guan Ze - - -
GeoEstate Cerulean Koh Shiliang Daniel Ang Tang Hui Xin - - -
Business Mafia Chloe Fu Wei Yu Cheng Xin Yuan Lim Jia Khee - - -
EzSell Lim Yan Hong, Patrick Shi Jianrong Daniel Chin Wen Kai - - -
Dangy Ang Kah Eng Jerry Obadiah Tohvan Tan Kai Xiang, Terence - - -
FLATearthers Benjamin Ng Wei Xian Yong Yong Qing Goh Mi Shan, Brittany - - -