Seminar Review: The Provision of and (Just) Access to Housing: Insights from Malaysia and Indonesia
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Housing has been an undeniable primary aspect of human life. Without a proper shelter, a person cannot fulfill his/her basic need in life. This need has given more pressure when we know that there is only a limited amount of land that can be utilized for it. On other side, the competition to obtain a proper housing is getting more intense overtime due to urbanization (more people are coming to urban area to settle in). That is the exact reason why the price for this resource is skyrocketed to the point of no return.
After learning about Google Earth Engine (GEE) from CASA0025: Building Spatial Applications with Big Data in 2024 from CASA, I was impressed by the vast potential of this tool. Not only does it provide access to extensive planetary data, but it also includes essential tools for in-depth analysis and prediction, which can be dynamically visualized and presented through its spatial application. It’s a truly full-stack process!
I was wondering if I could add one more variable to my previous bivariate map, and here they are: triangulating 1) Population Density (represented by point size); 2) Kilometers traveled per year by people who travel to work by Car or Van (gold color); and 3) Total carbon footprint per person in kgCO2e (blue color) into a trivariate map!
During my investigation of carbon footprint data for a personal research project, I became intrigued by its correlation with population proportions. To explore this connection, I initiated the process by plotting both variables (carbon footprint vs population density) on bivariate maps.
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In certain cases, significant movements such as startup development can create disruptions. This has happened with Airbnb, where in some areas, the development of Airbnb-oriented properties has triggered externalities such as the increase in permanent housing prices and gentrification. Due to this issue, the growth of Airbnb should be appropriately monitored. That is what ‘Inside Airbnb’ has been doing for years. Inside Airbnb publishes a large dataset about the location of Airbnb properties along with their characteristics for FREE!