Difference between revisions of "Issho-ni Research Paper"

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<div id="mw-content-text" lang="en-GB" dir="ltr" class="mw-content-ltr"><div style="background: #D2B48C; padding: 10px; font-weight: bold; line-height: 1em; text-indent: 15px; text-align: center; font-size: 30px"><font color="FFFFFF">Project Report</font>
 
<div id="mw-content-text" lang="en-GB" dir="ltr" class="mw-content-ltr"><div style="background: #D2B48C; padding: 10px; font-weight: bold; line-height: 1em; text-indent: 15px; text-align: center; font-size: 30px"><font color="FFFFFF">Project Report</font>
 
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[[File:FCKyOUJIN.PNG|400px|center|link=https://pdfhost.io/v/x8yW1LXR_GIS_Project_Report_G1_Group_4convertedpdf.pdf]]
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==<div style="background: #367a57; padding: 10px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #BEB9B5 solid 32px; font-size: 20px"><font color="white">Yishun Land Change Detection (2008 & 2014) </font></div>==
 
==<div style="background: #367a57; padding: 10px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #BEB9B5 solid 32px; font-size: 20px"><font color="white">Yishun Land Change Detection (2008 & 2014) </font></div>==
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==<div style="background:#367a57; padding: 10px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #BEB9B5 solid 32px; font-size: 20px"><font color="white">Population Proportion of Targeted Age Groups </font></div>==
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==<div style="background:#367a57; padding: 10px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #BEB9B5 solid 32px; font-size: 20px"><font color="white">Demographics of Yishun (Population) </font></div>==
 
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=== Population Change for the Segments ===
 
=== Population Change for the Segments ===
We have obtained the census/household data from SingStat to analyse the population change between 2008 and 2014 for each target segment identified above. Due to unavailability of the desired information (data for 2008 and 2014), we have used the Basic Demographic Characteristics data for year 2010 and 2015 respectively, which closely follows the timeframe in study.
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We have obtained the census/household data from SingStat to analyse the population change between 2008 and 2014 for each target segment identified above.
  
From the downloaded Excel sheets, we have extracted information relevant to our analysis (i.e. Yishun's population) and cleaned up the data necessarily before saving into separate CSV files ready to be used in QGIS as attribute tables. For instance, the data from 2010 did not include Nee Soon as part of the subzones of Yishun's population data unlike the one from 2015. Upon further scrutiny, we realised it was SingStat's decision to omit planning areas/subzones with small number of persons, and that Nee Soon did exist at the year of 2010. Hence, we added in Nee Soon in our 2010 CSV file but with 0's imputed for the population.
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From the downloaded Excel sheet, we have extracted information relevant to our analysis (i.e. Yishun's population) and cleaned up the data necessarily before saving into separate CSV files ready to be used in QGIS as attribute tables. Specifically, we have used the yearly data and leveraged on Excel's filter tool to retrieve the desired information, of which we imported to our CSV files in our desired format (transpose pasting, etc). For null values, we have replaced/imputed them with 0s with anticipation of calculation later on.
  
Further preprocessing and data manipulation is then conducted in another CSV file, where we combined information from both 2010 and 2015 to study the population change. First, we created three new columns to store the aggregated population for each group, once for each year. Subsequently, the change (headcount) can be calculated by computing the difference between 2015 and 2010. The percentage change is then obtained by dividing the change in headcount with 2010's base population, also in headcount.
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Further preprocessing and data manipulation is then conducted in another CSV file, where we combined information from both 2008 and 2014 to study the population change. First, we created three new columns to store the aggregated population for each group, once for each year. Subsequently, the change (headcount) can be calculated by computing the difference between the two years. The percentage change is then obtained by dividing the change in headcount with 2008's base population, also in the form of headcount.
  
 
For each map view below, the number of classes/bins have been carefully selected to include the minimum and maximum value (i.e. range). Similarly, the intervals are chosen to be equal with careful choice of split so that the patterns can be evidently shown to map readers in a clear manner.
 
For each map view below, the number of classes/bins have been carefully selected to include the minimum and maximum value (i.e. range). Similarly, the intervals are chosen to be equal with careful choice of split so that the patterns can be evidently shown to map readers in a clear manner.
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==<div style="background: #367a57; padding: 10px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #BEB9B5 solid 32px; font-size: 20px"><font color="white">Conclusion & Analysis</font></div>==
 
==<div style="background: #367a57; padding: 10px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #BEB9B5 solid 32px; font-size: 20px"><font color="white">Conclusion & Analysis</font></div>==
 
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the ideal elderly service ..
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We proposed recommendation based on the understanding and knowledge we obtained from the data set gathered and analyzed in the precious sections. Below are the three recommendation we proposed for each age group. Detailed steps and explanation can be found in our full report document(link is at the top)
  
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[[File:Economic Activeyoujin.png|800px|left]]
 
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[[File:YoungSchool yiujin.png|800px|left]]
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Latest revision as of 00:37, 25 November 2019

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Project Report
FCKyOUJIN.PNG



Yishun Land Change Detection (2008 & 2014)

Yishun Boundary Change

Yishun Boundary Change.png

From the map view above, we can see that Yishun's boundary has diminished a little, where the land has receded from the northeast direction. The subzones affected are namely Northland, Yishun East and Lower Seletar.

Yishun 2008 & 2014 Land Use

LandUse 08 Yishun.png
LandUse 14 Yishun.png

Besides the land reduction leading to Yishun's differing boundary, the land use in the planning area has also changed. Here, we will highlight the major changes observed.

  • The area to the left of Lower Seletar Reservoir (Yishun's prominent waterbody) has became a reserve site from previous use for sports & recreation
  • Southwest of Yishun, there is a road extension that joins two existing roads
  • Further down the aforementioned road, a portion of land that used to be reserved is now accommodating for commercial and residential usage

GIF Animation Depicting Land Use Changes

LandUse GIF.gif

Demographics of Yishun (Population)

Demographic Segmentation

The population is divided into 3 groups:

  • Young (0 - 24 years old)
  • Economic Active (25 - 64 years old)
  • Aged (65 and above)

Population Change for the Segments

We have obtained the census/household data from SingStat to analyse the population change between 2008 and 2014 for each target segment identified above.

From the downloaded Excel sheet, we have extracted information relevant to our analysis (i.e. Yishun's population) and cleaned up the data necessarily before saving into separate CSV files ready to be used in QGIS as attribute tables. Specifically, we have used the yearly data and leveraged on Excel's filter tool to retrieve the desired information, of which we imported to our CSV files in our desired format (transpose pasting, etc). For null values, we have replaced/imputed them with 0s with anticipation of calculation later on.

Further preprocessing and data manipulation is then conducted in another CSV file, where we combined information from both 2008 and 2014 to study the population change. First, we created three new columns to store the aggregated population for each group, once for each year. Subsequently, the change (headcount) can be calculated by computing the difference between the two years. The percentage change is then obtained by dividing the change in headcount with 2008's base population, also in the form of headcount.

For each map view below, the number of classes/bins have been carefully selected to include the minimum and maximum value (i.e. range). Similarly, the intervals are chosen to be equal with careful choice of split so that the patterns can be evidently shown to map readers in a clear manner.

Population Change (Young)

Yishun Population Change (Young, Percentage).png

Population Change (Economic Active)

Yishun Population Change (Econ, Percentage).png

Population Change (Aged)

Yishun Population Change (Aged, Percentage).png

Land Suitability Modelling

Data Name Graphic Representation Format Source
Landuse
Planning Area Polygon Shapefile https://data.gov.sg/dataset/master-plan-2014-planning-area-boundary-no-sea
Master Plan 2008 Land Use Polygon Shapefile https://data.gov.sg/dataset/master-plan-2014-land-use?resource_id=0d1a6cda-7cad-4b17-b9a8-9e173afebbc1
Master Plan 2014 Land Use Polygon Shapefile https://data.gov.sg/dataset/master-plan-2014-land-use?resource_id=0d1a6cda-7cad-4b17-b9a8-9e173afebbc1
Master Plan 2014 Buildings Polygon Shapefile https://data.gov.sg/dataset/master-plan-2014-building?resource_id=c0ff19d3-5c25-4b7d-8034-e8f6dc65d75f
Road Section Line Polyline Shapefile https://www.mytransport.sg/content/dam/datamall/datasets/Geospatial/RoadSectionLine.zip
Housing
HDB Property Point CSV https://data.gov.sg/dataset/hdb-property-information
SLA Dwelling Info Point Keyhole Markup Language (KML) https://data.gov.sg/dataset/sla-dwelling-information
Landed Housing Area Polygon Shapefile https://data.gov.sg/dataset/sdcp-landed-housing-area
Transport
Bus Stop Location Point Shapefile https://www.mytransport.sg/content/dam/datamall/datasets/Geospatial/BusStopLocation.zip
Train Station Point Shapefile https://www.mytransport.sg/content/dam/datamall/datasets/Geospatial/TrainStation.zip
Demographics
Singapore Residents by Subzone, Age Group and Sex Polygon Keyhole Markup Language (KML) https://data.gov.sg/dataset/singapore-residents-by-subzone-age-group-and-sex-june-2016-gender
Educational Institutions
Pre-Schools Point Keyhole Markup Language (KML) https://data.gov.sg/dataset/pre-schools-location
Primary Schools, Secondary Schools and Junior Colleges Point CSV Dataset from Hands-On Ex 4
Private Education Institutions Point Shapefile https://data.gov.sg/dataset/private-education-institutions
Amenities
Supermarkets Point CSV https://data.gov.sg/dataset/list-of-supermarket-licences
Eldercare Services Point Shapefile https://data.gov.sg/dataset/eldercare-services
CHAS Clinics Point Keyhole Markup Language (KML) https://data.gov.sg/dataset/chas-clinics


Conclusion & Analysis

We proposed recommendation based on the understanding and knowledge we obtained from the data set gathered and analyzed in the precious sections. Below are the three recommendation we proposed for each age group. Detailed steps and explanation can be found in our full report document(link is at the top)

Economic Activeyoujin.png
YoungSchool yiujin.png
Eldercare youjin.png