3.1 GIS & Geospatial Analysis

One of the main objectives in this course is to enable you to:

1. Design, develop, and critique geospatial analysis workflows to perform tasks, answer questions, and solve location-based business problems.
2. To successfully accomplish this, you must be grounded in geospatial data science, be comfortable working with new geospatial software packages, use critical and analytical thinking.
3. Evaluate and manage location data; enriching, analyzing, storing, and visualizing.

Segmenting Markets and Customers for business objectives causes a corresponding reorganization of geospatial data. Recognizing this connection expands one's ability to identify key factors, perform geospatial analysis, and design models of the business problem. Often the goal is to discover customer behaviors and trends to predict future opportunities and identify how location impacts the business strategies. Current analysis techniques include digital transformation of the organization's data, connected sensors, and the Internet of Things (IoT).

In Geography: why it matters, Murphy repeatedly emphasizes how people develop attachments to places and regions. Consider the human factor in geography and geospatial studies to understand why people live there or how a town formed at the confluence of a major river, convenient rail and road transportation routes, with arable land and space for large manufacturing operations. The base or foundation of a successful geospatial analysis examining a business problem begins with understanding the context of the market, demographics, consumer needs, history of that business and a connection to its location, and possibly unique factors that impede or support the organization's success.

People do not simply occupy or visit places; they develop attachments to them that influence what they do, how they think about the world, and even how they construct their own identities.

It follows that grasping the nature of places requires consideration not just of their overt characteristics, but also of the way people think about and experience them. In an influential 1976 study entitled Place and Placelessness, University of Toronto geographer Edward Relph looked at the proliferation of look-alike commercial strips in and around North American cities. Terming these "placeless landscapes" (because they are ubiquitous and ignore the individual characteristics of the places where they sprang up), Relph invited us to think about what happens when landscapes reflecting people's geographical and historical sensibilities are replaced with cookie-cutter urban developments that can be found anywhere. (Murphy, 2018, pp.75-76)

Geospatial Data Sourcing

A business directly and indirectly collects significant volumes of data on its market, customers, products, operations, and operating environment. Analysts are apt to find the data is both structured and semi-structured, requiring capabilities to store, process, and analyze non-conforming and dissimilar data formats. In order to perform a valid analyis of the data and form hypotheses or models of the business problem, additional information is typically required to connect location-based relationships, relate context to differences in quarterly sales reports, and discern anomalies from random observations. The additional information might include geospatial reference data, imagery, consumer marketing, social media, demographics, and typological physical and human geography features.

Advanced data sourcing provide opportunities to improve location intelligence and leverage the volume and velocity of geospatial data collected by IoT sensors, enterprise computer networks, and data mining techniques.

• Human geography and social networking - studying human behavior with operational technologies to recognize, categorize, and interpret relationships of individuals, groups, and organizations.

• Forecasting - process from operations research to anticipate events, trends or trendlines, or expected future results.

• Crowdsourcing - operationalized process where individuals gather, share, and analyze geospatial information in a connected or online network. Access is provided for others to view or use the raw information and results of developed assessments.

Budgets often impact a department's access to business and geospatial data. Some businesses have large cash reserves or cash flow to purchase the volume and detailed data they require to effectively and profitably make decisions. Others must decide between purchasing data or operating the business. The timing of reports and subsequent analysis can provide an advantage to an organization that invests in current and well-organized third-party data. Savvy analysts seek alternative sources of geospatial data to return value to the organization, e.g. Cloud-based data services included in software licenses, crowdsourced information, and trade organization data.

Collecting relevant and accurate data starts the geospatial analysis process. What is related to the business question, is data available, and who determines access? What data formats meet your analysis department’s IT system and schema? Typically, a business does not have all the georeferenced information available to fully develop location intelligence. What information is required to develop the next fiscal year's retail distribution strategy, to array an optimal bank branch distribution to reach consumers, or site planning for the healthcare industry?

Data enrichment adds geospatial, imagery, consumer marketing, social media, demographics, physical and human geography information to examine factors of the business problem. The geospatial professional designs, stores, and accesses a GIS that meets the needs of the business and geospatial analysis.

Data enrichment process that enhances, refines, or otherwise augments existing data, typically with imported datasets. Geospatial analysts geocode inconsistent data, augment routing information, enrich point data with Areas of Influence Analysis (isolines of relative information), and often incorporate demographic measures to get a better picture of the customer or target audience. (Murray, 2017)

O’Sullivan and Unwin describe geographic information analysis as investigating patterns found in spatial processes that may be operating in the space of points, lines, and fields. (O’Sullivan & Unwin, 2003:3) There are many methods of geospatial analysis; it's important to understand the functions of each analysis and match your choice to the factors of the business problem. What questions must be answered to reach a solution for that problem? Recognize how important the concepts of space and time have in analysis. Spatial analytics merge GIS with other types of data and analysis; at times requiring specialized geospatial software to dependably preserve network relationships. Spatial-temporal patterns indicate physical activiites and social behavior which relate to the business problem or modeling.

Geo-Awareness

In your research, seek the most relevant, useful geospatial data sources or collections. Determine how the geospatial data meet your needs for metadata, scale, currency or timeliness. Location intelligence structured and unstructured data sources may be found in business systems, social media, embedded sensors (e.g., vehicle telematics), company portals, mobile apps, open source, third-party geospatial information, and complimentary information (e.g., insurance FIC scores, building repair costs, business formation data).

Today there is more geo-awareness - and those who are both aware of and using geospatial technologies enjoy a significant advantage - the geo-advantage. Geo-advantage comes from not only being aware of the technologies, but also of the data or information available, having access to that information, and knowing how the information can be used to provide a competitive advantage in the GeoEconomy. Together these can collectively be referred to as the geospatial infrastructure. (Ryerson, 2010, p.39-40)