This dataset includes the listing prices for the sale of properties (mostly houses) in Ontario. They are obtained for a short period of time in July 2016 and include the following fields: - Price in dollars - Address of the property - Latitude and Longitude of the address obtained by using Google Geocoding service - Area Name of the property obtained by using Google Geocoding service

This dataset will provide a good starting point for analyzing the inflated housing market in Canada although it does not include time related information. Initially, it is intended to draw an enhanced interactive heatmap of the house prices for different neighborhoods (areas)

However, if there is enough interest, there will be more information added as newer versions to this dataset. Some of those information will include more details on the property as well as time related information on the price (changes).

This is a somehow related articles about the real estate prices in Ontario: http://www.canadianbusiness.com/blogs-and-comment/check-out-this-heat-map-of-toronto-real-estate-prices/

I am also inspired by this dataset which was provided for King County https://www.kaggle.com/harlfoxem/housesalesprediction

This dataset includes the listing prices for the sale of properties (mostly houses) in Ontario. They are obtained for a short period of time in July 2016 and include the following fields: Price in dollars Address of the property Latitude and Longitude of the address obtained by using Google Geocoding service Area Name of the property obtained by using Google Geocoding service This dataset will provide a good starting point for analyzing the inflated housing market in Canada although it does not include time related information. Initially, it is intended to draw an enhanced interactive heatmap of the house prices for different neighborhoods (areas) However, if there is enough interest, there will be more information added as newer versions to this dataset. Some of those information will include more details on the property as well as time related information on the price (changes). This is a somehow related articles about the real estate prices in Ontario: http://www.canadianbusiness.com/blogs-and-comment/check-out-this-heat-map-of-toronto-real-estate-prices/ I am also inspired by this dataset which was provided for King County https://www.kaggle.com/harlfoxem/housesalesprediction

The heat demand is an amalgamation of a number of different spatial datasets that have associated heat demand values. The map has been developed on the principle of applying data with increasing levels of certainty and overlaying and replacing individual property heat demand values.

The heat demand layer is made up of a number of rasters which depict this demand in different ways. The heat demand rasters present a visualisation of the heat demand density by showing total demand within grid squares. These are shown at various grid sizes (50x50, 250x250, 500x500 and 1000x1000).

The Scotland Heat Map is supported by a number of documents including users guidance which is available at http://www.scotland.gov.uk/heatmap

2.1 Methodology report 2.2 Manual 2.3 Metadata 2.4 Local knowledge validation & improvement process 2.5 Data management 2.6 Limitations and protections for data use and analysis 2.7 Scotland heat map – interactive and local web

These basic maps contain information about flooding, heat and biodiversity for every building in the Province of Zuid-Holland. They are used to feed citizen portals for climate adaptation developed by Atelier GroenBlauw.

The sources for the category values per property are:

Heat: Heat stress map climate atlas South Holland Flooding: Vulnerability of buildings in the event of extreme precipitation climate atlas South Holland Biodiversity (Green): Atlas of Natural Capital