Difference between revisions of "Project Groups"
| Line 215: | Line 215: | ||
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. | 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 | + | 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. |
|| | || | ||
* [[EzModel_Proposal|Project Details]] | * [[EzModel_Proposal|Project Details]] | ||
Revision as of 22:47, 25 February 2019
IS415 GeoSpatial Analytics and Applications
|
|
|
|
|
|
| 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 |
||
| GeoSpies |
Project Title |
Abstract (Note: Not more than 350 words) |
Group Member: Student001, Student002, Student003 |
||
| 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 |
||
 |
|
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: | ||
| 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 |
||
 |
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: |
| 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 | - | - | - | ||||||||||||
