Real Estate Data Scraping and Analysis for Specific Uses
Budget: $750 – $1,500 USD
I'm looking for help in scraping and analyzing data related to real estate given parcel index numbers (PINs). I need to collect specific data, such as location (latitude and longitude of geographic center, and corners), county, township, dimensions, shape, legal type, legal description, assessed value, annual property taxes, sales price history, owners adjacent owner of properties, and areal photography of land parcels. The specific area I am looking at is various counties within Illinois. The data will be scraped from various public GIS websites, or other similar data repositories which may have restrictions on the number of queries from a given IP address in a given time frame.
I will use the scraped and analyzed data for investment decisions, including the following:
(1) Determine if the parcel is appropriate for a cellular tower. The data from above will need to be combined along with scraped data from other public databases to determine the local strength of radio signals and cellular coverage, and how cellular coverage would change given a tower placed on the parcel. Ordinances from local governments will need to be scraped to determine if a tower can be legally placed on the parcel.
(2) Determine if the parcel is appropriate to be sold to an adjacent parcel owner. Data from above will need to be combined with data scraped about adjacent parcels to identify if the addition of the subject parcel improves the value of the adjacent parcel.
(3) Determine if the parcel is appropriate to be used for farm equipment storage. Data from the above will need to be combined with other public information about local roads and average distances to farmland.
(4) Determine if the parcel is appropriate for billboards or other signage. Data from the above will need to be combined with traffic data from local roads to determine if a billboard at that location has significant visibility.
(5) Determine if the parcel is appropriate for building a "Habitat for Humanity" home. Data from above will need to be combined with data sources of prior "Habitat for Humanity" construction projects, along with distances to business districts, schools, and local municipal support such as fire and police.
(6) Determine use of similar parcels, if different than the existing use.
I will use the scraped and analyzed data for investment decisions, including the following:
(1) Determine if the parcel is appropriate for a cellular tower. The data from above will need to be combined along with scraped data from other public databases to determine the local strength of radio signals and cellular coverage, and how cellular coverage would change given a tower placed on the parcel. Ordinances from local governments will need to be scraped to determine if a tower can be legally placed on the parcel.
(2) Determine if the parcel is appropriate to be sold to an adjacent parcel owner. Data from above will need to be combined with data scraped about adjacent parcels to identify if the addition of the subject parcel improves the value of the adjacent parcel.
(3) Determine if the parcel is appropriate to be used for farm equipment storage. Data from the above will need to be combined with other public information about local roads and average distances to farmland.
(4) Determine if the parcel is appropriate for billboards or other signage. Data from the above will need to be combined with traffic data from local roads to determine if a billboard at that location has significant visibility.
(5) Determine if the parcel is appropriate for building a "Habitat for Humanity" home. Data from above will need to be combined with data sources of prior "Habitat for Humanity" construction projects, along with distances to business districts, schools, and local municipal support such as fire and police.
(6) Determine use of similar parcels, if different than the existing use.