When most people think about data, they think about spreadsheets and data files containing row after row of information in text and numerical values.
And that was the case for most of the 20th century.
Then along came digitized geospatial data. This created the framework for an entirely different kind of data research -- one that looked at information in the context of its physical relationship to other information.
In other words, geospatial data research is a level up from linear time series data science.
Now data scientists can look at information in terms of how an event at Location A and Time X related to subsequent events at Location B and Time Y and at Location C and Time Z.
The difference in data research is leading advances in many sectors. Heard the phrase 'digital twin'? Digital twins are the virtual representation of the real world in highly detailed, extraordinarily accurate data models. Digital twins allow for geospatial data science based upon the closest thing we can do to experimenting 'in the real'.
In this blog I will share results of Geospatial Data Science research that I have done here at Pactriglo, as well as other insightful ways that geospatial data is being used to take a new look at old theories and develop new theories about the future.
Pactriglo focuses on urban infill analysis and market opportunities in major cities in the United States. Pactriglo integrates geospatial and tabular data into customized relational databases and interactive web map apps that provide competitive edge to real estate developers, real estate investors, brokers, and builders. Pactriglo is a market leader in identifying where one county tax parcel contains more than one historic municipal lot for 'lot splitting'. Pactriglo's research and development is in spatial finance and correlations in predictive timeseries analytics as applied to residual land values. To discuss your business intelligence needs, contact us to execute a mutual NDA and schedule an initial consultation.