Key takeaways
- You can perform spatial analysis using GIS or spatial statistics, databases, and modeling.
- Spatial data is available from online platforms, your own research and observations, public agencies, or private companies.
- Standard mapping approaches include choropleth, thematic, cluster, and dot-density mapping.
- Market heatmaps allow investors to identify areas of decreasing supply and increasing demand.
- Investors use spatial autocorrelation, interpolation, regression, optimization, and interaction to analyze data.
The value of the real estate technology market is expected to reach $17.22 billion by 2029, and GIS mapping software will make a significant contribution to that number. In 2020, the geographic information system (GIS) software market was worth $6.3 billion globally. At the time, it was predicted the value would more than triple by 2030, hitting $25.5 billion.
The GIS software market was worth $8.35 billion in 2022. According to the latest expert forecasts, it will reach $29.6 billion by 2031, coming to an annual increase of 15.1% from 2023 to 2031.
According to the US Census Bureau, there are 19.3 million rental properties in the US. Just under 86% contain a single-family unit, for a total of 49.5 million rental units.
A property can contain multiple units sharing common areas like gardens or driveways, located on the same block. It can also be a standalone structure on its own block of land (a house).
In 2024, builders plan to add more than half a million (518,108) new apartment units to the rental market.
Benefits of mapping software for real estate investors
Mapping software provides a graphic presentation of real estate data. It helps property investors identify trends and patterns in a given market. It reveals metrics such as home prices, rental prices, vacancy rates, and others. Heatmaps are color-coded, with red showing high property demand and blue indicating low to no demand for properties in a given area.
You can perform spatial analysis using GIS and spatial statistics, databases, and modeling. The first step in this analysis is gathering and organizing the spatial data you need for a given project. You can obtain spatial data from online platforms, your own research and observations, public agencies, or private companies such as Maptive. Maptive GIS mapping software features numerous reliable techniques to visualize and explore spatial data.
Types of mapping
Apart from heat mapping, effective and commonly applied mapping approaches include choropleth, thematic, cluster, and dot density mapping. They can all assist property investors in making the best decisions. Thematic mapping reveals the spatial variation of a single variable or attribute, such as property price. Choropleth mapping shows a proportion or ratio’s spatial variation. A relevant ratio could be that between the number of occupants and the number of units available in a given area.
Cluster mapping shows the concentration or grouping of features, and dot density mapping indicates a frequency or count’s spatial density, like the turnover: how often a property type is bought and sold.
Market heatmaps allow investors to identify areas of decreasing supply and increasing demand for real estate. They also make it possible to see which neighborhoods are best avoided. Sales heatmaps show investors and real estate agents the most active markets. They reveal how many property sales are occurring in a given area. Different colors represent the different number of homes sold in each area. Investors can use heatmap generators to identify the cities and areas with the highest appreciation potential.
Analyzing and modeling spatial data: Summary
Investors use spatial autocorrelation, interpolation, regression, optimization, and interaction to model and analyze data. Spatial autocorrelation measures whether neighboring features are similar or different. Spatial interpolation assesses the values of a variable in unknown areas based on known ones. Regression estimates explanatory variables’ effect on a dependent variable while accounting for spatial dependence, and optimization determines the best allocation or location of resources depending on concrete goals or limitations. Finally, spatial interaction measures the movement or flow of information or people between locations.