Three reasons the Real Estate industry can’t live without GIS

Geraldine Yeh
6 min readDec 29, 2021
Orchestrating Real Estate Development using GIS. (Image by ESRI)
Orchestrating Real Estate Development using GIS. (Image by ESRI)

Only three things matter in real estate: “location, location, location”. Traditionally, real rate estate firms make their decision based on a combination of intuition and retrospective data. Today, the rise of big data is aiding thousands of decision makers in the real estate industry. Technology — in this case GIS (Geographical Information Systems), is a powerful “disruptor” and enables firms to differentiate themselves, a differentiation that will only grow exponentially in importance. Ultimately, individuals who emerge as winners in the highly competitive field of real estate will be those who are unafraid in the face of change and harness this technology to reap cost savings and achieve better operational efficiencies.

Valued at USD 59.5 billion in 2021, the geospatial analytics market is projected to grow to USD 107.8 in 2026, with a Compound Annual Growth rate of 12.6%. Driven by major factors such as the increasing number of AI and ML GIS based solutions, the development of smart cities and urbanisation, GIS is marked to be a formidable force.

From looking for homes for the ordinary Joe, to franchising a multi-million dollar business, GIS enables its users to utilise technology to analyse location. For instance, The Shopping Center Group (TSCG) — a leading retail-only real estate company, strategically collapsed both psychographic and spatial data to accurately predict the highest possible return on site selection and saw a 30% increase in revenue over three years.

Here are three ways GIS can improve your bottom line:

  1. Site selection

What’s the best place to build a mixed-use development? This is a complex question with layers of factors coming into play. Among others information on demographics, income level, age, nearby competitors and accessibility are critical elements when it comes to identifying the best site for a development. Furthermore, as cities are living, breathing and dynamic, such information may change everyday, hence the importance of dynamic big data.

GIS empowered users to harness location intelligence for real estate site selection decisions. (Image by ESRI)
GIS empowered users to harness location intelligence for real estate site selection decisions. (Image by ESRI)

GIS ties all these data and elements together while presenting them in a meaningful way to aid decision. Culver’s — a popular family restaurant in the US, for instance, has nearly 400 restaurants and has been using GIS to help franchise candidates identify potential new sites.

2. Predictive modelling

Business Insider (2019) reported more than 9,000 store closures in 2019 alone, with major brands such as JCPenny and GAP on the list. With the growing popularity of online shopping, physical stores are facing additional pressure. With the help of GIS, store owners can tap into spatial data analytics to optimise and improve performance.

Prediction of retail revenue -potential top performing stores are located in Los Angelas as seen by the biggest dot. (Image by Dongjie Fan)
Prediction of retail revenue —potential top performing stores are located in Los Angelas as seen by the biggest dot. (Image by Dongjie Fan)

GIS can predict the revenue of a retail store based on a huge array of relevant data points such as the US Census, Consumer spending habits and sales revenue from other stores within the company.

GIS can also aid in the development of an Automated Valuation model, which enables investors to scour a huge number of property deals, analyse them based on location factors and find the best investments that can beat the market using a rental gross yield estimation.

Hone in on market-beating investment opportunities using real estate data science & GIS. (Image by Juan Carlos Alonso — PropertyQuants Course participant)
Hone in on market-beating investment opportunities using real estate data science & GIS. (Image by Juan Carlos Alonso — PropertyQuants Course participant)

Combining machine learning models with GIS helps to identify the factors that drive real estate asset appreciation. Methods like SHapley Additive exPlanations (SHAP) contribute to this. For instance, SHAP is able to show how various variables can contribute to the model output for a specific store.

3. Unlocking the power of spatial data

Big data has unlocked critical information around the world. Whilst information is accessible, they remain fragmented. Aggregating and visualising location based data produced actionable insights rather than mere tables of dry numbers. GIS is the key to moving from pure data to interactive maps, giving a business edge.

GIS enables us to visualise demographic data to make smarter real estate investment decisions. (Image by VIsualCapitalist)
GIS enables us to visualise demographic data to make smarter real estate investment decisions. (Image by VIsualCapitalist)

GIS is able to weave information from multiple sources such as census, economic and most importantly, spatial data to form an overarching pictorial representation.

On a micro level, GIS makes it simple to understand zoning and airspace rights, enabling real estate developers to utilise underdeveloped properties.

To simplify decision making, PropTech companies such as Ratio City and Knogeo visualises city blocks in 3D while reflecting air rights of individual land parcels, which helps to identify land to develop.

Visualising building mass to model identify underdeveloped properties. (Image by Ratio City)
Visualising building mass to model identify underdeveloped properties. (Image by Ratio City)

Other PropTechs such as LocateAlpha and MapYourProperty (are able to analyse properties in a comprehensive manner; thoroughly pairing relevant data such as crime rates, rental friendliness and critical investment metrics (i.e.high returns and lower risks) to its respective property.

Use multiple layers of spatial data to filter and find investments matching ideal criteria. (Image by LocateAlpha)
Use multiple layers of spatial data to filter and find investments matching ideal criteria. (Image by LocateAlpha)

If sourcing for data is a stumbling block for your team, it should no longer remains a hindrance as data providers specialising in real estate data sets such as Placer who specialises in mobile phone data, Urban Intelligence and House Canary make it easy to weave in layers of information in a digestible manner. For those working with data in Asia, Bridge5Asia is able to provide a comprehensive database of real estate data in China.

Now that you understand how GIS can make significant changes to your bottom line, here’s how you can have this helpful tool in your arsenal.

Where you can learn to use GIS for Real Estate:

For starters, an option would be to enrol in a full-time course such as the one offered by PennState University which presents a customisable curriculum based on your specific interest. However, do note that it is a full time course across five 10-weeks terms.

Other general GIS courses that are less time intensive include an introductory course offered online by the University of Alaska — Professional Certificate in Geographical Information Systems Essentials Online: Essential Workflows. Though it is not specifically tailored towards the real estate industry, participants will have the opportunity to learn more about 3D geoprocessing.

Lastly, PropertyQuants offers a course in applying data science and machine learning to real estate, including a module specifically about using GIS to solve complex real estate problems such as using location data for site selection and using spatial data to find market-beating investments. Participants will get to work on a capstone project to explore their topic of interest, producing real world analysis methods taught during the course. Classes are supplemented by one-to-one consultations and graded assignments to ensure that participants are fully equipped with the course materials. This is perhaps the only course today that specifically focuses on the application of data science and GIS to the real estate industry.

To learn more, visit their website https://propertyquants.com/training.

Conclusion

GIS is becoming a recurring theme in the real estate industry. Coupled with the advent of big data, companies that have seen exponential growth are those that have harnessed the power of technology and applied it successfully in the field.

Unfortunately, there is a dire lack of talent who have both the skill sets in the geospatial tech world. According to a recent government commission, there exists a lack in skills to unlock geospatial data, with 60% of the local authorities reporting the lack of skills to be a critical barrier to maximising the value of geospatial data. It suffice to say that those with relevant geospatial skills will unlock the future of real estate.

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