Recent posts

Calibrating Hedonic Pricing Model for Private Highrise Property with GWR Method
Geographically weighted regression (GWR) is a spatial statistical technique that takes non-stationary variables into consideration (e.g., climate; demographic factors; physical environment characteristics) and models the local relationships between these independent variables and an outcome of interest (also known as dependent variable). In this hands-on exercise, you will learn how to build hedonic pricing models by using GWR methods. The dependent variable is the resale prices of condominium in 2015. The independent variables are divided into either structural and locational.
geospatial
sf
spdep
tmap
clustering
Ong Zhi Rong Jordan
December 10, 2022

Regionalisation of Multivariate Water Point Attributes with Non-spatially Constrained and Spatially Constrained Clustering Methods
Understanding the difference between traditional clustering algorithm and spatially constrained clustering algorithm.
geospatial
sf
spdep
tmap
clustering
Ong Zhi Rong Jordan
December 7, 2022

Introduction to Geographic Segmentation with Spatially Constrained Cluster Analysis
Spatially constrained methods has a hard requirement that spatial objects in the same cluster are also geographically linked.
geospatial
sf
spdep
clustering
tmap
Ong Zhi Rong Jordan
December 3, 2022

Geospatial Analytics for Social Good - Understanding Nigeria Water functional and non-functional water point rate
Geospatial analytics hold tremendous potential to address complex problems facing society. In this study, you are tasked to apply appropriate global and local measures of spatial Association techniques to reveals the spatial patterns of Not Functional water points. For the purpose of this study, Nigeria will be used as the study country.
geospatial
sf
spdep
tmap
Ong Zhi Rong Jordan
November 30, 2022

Introduction to Global and Local Measures of Spatial Autocorrelation
Describing the presence of systematic spatial variation in a variable. “The first law of geography Everything is related to everything else, but near things are more related than distant things.” Waldo R. Tobler (Tobler, Waldo R. 1970)
geospatial
sf
spdep
tmap
Ong Zhi Rong Jordan
November 24, 2022

Introduction to Spatial Weights and Application
Computation of spatial weights using R. Understanding the spatial relationships that exist among the features in the dataset.
geospatial
sf
spdep
tmap
Ong Zhi Rong Jordan
November 24, 2022

Introduction to Choropleth Mapping
Utilising the different libraries such as ggplot, tmap and leaflet to visualise geographical data.
geospatial
sf
ggplot
tmap
leaflet
Ong Zhi Rong Jordan
November 23, 2022

Data Wrangling of Geospatial Data
Utilising the sf and tidyverse packages to tidy geospatial data.
geospatial
sf
Ong Zhi Rong Jordan
November 19, 2022

RFM Model
Leveraging on simple data wrangling techniques to create a RFM model. Subsequently, leveraging on unsupervised classification to conduct customer segmentation for targeted marketing.
tibble
clustering
unsupervised
Ong Zhi Rong Jordan
June 25, 2022

SIS Visual Representation
Using Static, Interactive and Statistical (SIS) Graphs to reveal the demographics and relationships of a city.
tibble
ggstatsplot
Ong Zhi Rong Jordan
June 8, 2022
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Posts of my own works

Posts from Geospatial Analytics

Calibrating Hedonic Pricing Model for Private Highrise Property with GWR Method

Geographically weighted regression (GWR) is a spatial statistical technique that takes non-stationary variables into consideration (e.g., climate; demographic factors; physical environment characteristics) and models the local relationships between these independent variables and an outcome of interest (also known as dependent variable). In this hands-on exercise, you will learn how to build hedonic pricing models by using GWR methods. The dependent variable is the resale prices of condominium in 2015. The independent variables are divided into either structural and locational.
geospatial
sf
spdep
tmap
clustering
December 10, 2022
Ong Zhi Rong Jordan

Regionalisation of Multivariate Water Point Attributes with Non-spatially Constrained and Spatially Constrained Clustering Methods

Understanding the difference between traditional clustering algorithm and spatially constrained clustering algorithm.
geospatial
sf
spdep
tmap
clustering
December 7, 2022
Ong Zhi Rong Jordan

Introduction to Geographic Segmentation with Spatially Constrained Cluster Analysis

Spatially constrained methods has a hard requirement that spatial objects in the same cluster are also geographically linked.
geospatial
sf
spdep
clustering
tmap
December 3, 2022
Ong Zhi Rong Jordan

Geospatial Analytics for Social Good - Understanding Nigeria Water functional and non-functional water point rate

Geospatial analytics hold tremendous potential to address complex problems facing society. In this study, you are tasked to apply appropriate global and local measures of spatial Association techniques to reveals the spatial patterns of Not Functional water points. For the purpose of this study, Nigeria will be used as the study country.
geospatial
sf
spdep
tmap
November 30, 2022
Ong Zhi Rong Jordan

Introduction to Global and Local Measures of Spatial Autocorrelation

Describing the presence of systematic spatial variation in a variable. “The first law of geography Everything is related to everything else, but near things are more related than distant things.” Waldo R. Tobler (Tobler, Waldo R. 1970)
geospatial
sf
spdep
tmap
November 24, 2022
Ong Zhi Rong Jordan

Introduction to Spatial Weights and Application

Computation of spatial weights using R. Understanding the spatial relationships that exist among the features in the dataset.
geospatial
sf
spdep
tmap
November 24, 2022
Ong Zhi Rong Jordan

Introduction to Choropleth Mapping

Utilising the different libraries such as ggplot, tmap and leaflet to visualise geographical data.
geospatial
sf
ggplot
tmap
leaflet
November 23, 2022
Ong Zhi Rong Jordan

Data Wrangling of Geospatial Data

Utilising the sf and tidyverse packages to tidy geospatial data.
geospatial
sf
November 19, 2022
Ong Zhi Rong Jordan
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Posts from Visual Analytics

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