Preface

Geographic information systems (GIS) were seen as a panacea for quite a long time. The misfortune is that they have become more like service-oriented architecture solutions. Indeed, we previously stored our files on either a PC or a server. However, currently files are no longer allocated; instead, we use several network services such as a Web Map Service (WMS) or Web Feature Service (WFS), which distribute network services. We have definitely moved from a web supported by documents to a web supported by databases, crowdsourced data (e.g., volunteered geographic information—VGI), and social networks, twisted by community behavior, giving access to both collaboration tools and environments, and allowing location analytics.

We have reached a point where anybody may gather spatial-referenced data using, for instance, a mobile device, create some reasonable maps, and put them online. VGI is effectively replacing official data sources, letting us perform a more complex and dynamic analysis than the one allowed by traditional census data. This we can call neogeography, a new kind of geography accessible to everyone. Neogeography offers new life to maps, thriving in a society where each individual is a potential cartographer. Now maps are able to display individual perceptions because they are centered on the mapmaker, representing reality from a bottom-up perspective rather than from a bottom-down one. This new generation of maps can be created in real time and be tailor-made, representing detailed singularities never seen before, e.g., graffiti on a wall or birds in a tree.

It is clear that data-driven geography is re-emerging due to substantial spatial data flow from people and sensors. Geography has shifted from a data-scarce to a datarich environment. This—big data—revolution is not about data volume; instead, it is about data variety and at what velocity we can collect and store it. Big data has an enormous potential to feed both spatial analysis and geographic knowledgediscovery but at the same time raise friction among idiographic and nomothetic methodologies. Nonetheless, the belief that location matters is inherent to geography and functions as a robust incentive to develop sophisticated procedures on spatial statistics, time-geography, and geographic information science (GISc).

GISc can be understood as a subdivision of information science that deals with geographic data, or as a set of vital interrogations upraised by geographical information and the technologies used to gather, handle, and communicate it, i.e., information and communication technologies (ICTs). Geographic data can disclose fascinating patterns that, in specific cases, point toward causal mechanisms.

GIS have evolved from a research project to a very profitable industry. As new, quicker, more powerful, and less expensive technologies become accessible, this tendency will carry on. The new generations of mobile phones have capabilities to perform GIS tasks, augment the reality recognized by the handler by getting into databases, and have the capacity to capture and upload photos. Furthermore, the VGI invisible economy greatly increases the value of the visible economy, because people are interested in becoming neogeographers. GIS can be extremely seductive, tempting people to experience an intrinsic love for maps.

**II**

**Section 4**

*by Junghoon Ki*

**Section 5**

GIS and Big Data Visualization

Service Sector Employment

*by Duanshun Li, Ming Lu and Rod Wales*

Big Data and Augmented Reality **117**

**Chapter 7 119**

**Chapter 8 133**

Volunteered Geographic Information **155**

**Chapter 9 157**

*Google Earth* Augmented for Earthwork Construction Planning

Volunteered Geographic Information System and Its Contribution in

*by Nuggehalli Narayanachar Ramaprasad and Priya Narayanan*

Certain key issues are sure to endure in the nearby future. The spatial heterogeneity principle makes sure that most probably local and universal will be struggling with each other, claiming to harmonize standards and improve software and data interoperability. Data interoperability and Web services are ever more crucial, forcing, to some extent, the replacement of the GIS concept with spatial data infrastructures. The spatial dependence standard guarantees that efforts to apply orthodox techniques of inferential statistics to geographic phenomena will always be troubled and the spatial heterogeneity principle will always contradict nomothetic knowledge.

GIS are becoming network-oriented services. In these services, only organized internal resources become worldwide network-shared services. However, network services and smartphones, to name just a few, will soon claim interoperability, openness, and flexibility. Several GIS functions will persist for a long time. Network intelligence is being added, e.g., WMS, WFS, and CityGML; a completely new revolution is on the move. So, obviously, GISc will carry on, but rapidly change and evolve as well. The main GISc challenge is to find useful and efficient ways to catch and map the complexity of geographic systems in the limited digital binary space of a computer. In addition, we face the challenge of depicting the remainder and evaluating its influence on GIS operation results. This generates a question of critical spatial thinking, i.e., the critical process that any user of these technologies must have.

Undeniably, recent developments in ICTs have increased the multimedia narratives about the geographical representation of places, with significant repercussions on geographic research directions. Geographers incorporating big data with current scientific paradigms have changed and supported the study of geographic systems and, in between, settled for new concepts of space. This is a break for new research agendas in both qualitative and quantitative contexts. Big data and data analytics improve our understanding of the use of space, evaluating physical (fixed) and digital (fluid) spaces, and while both overlap and coexist, each one is shaped by the other and its users.

So, one may conclude that over the last few years, GISc has established itself as a collaborative information-processing system that is increasing in popularity. Yet, this interdisciplinary field is still somewhat misunderstood. This book talks about some of the GISc domains encompassing students, researchers, and common users. Chapters focus on important aspects of GISc, keeping in mind the processing capability of GIS along with the mathematics and formulae involved in arriving at each solution. The book has nine chapters divided into five sections. The first section is more general and focuses on what GISc is and its relation to GIS and Geography, the second is on location analytics and modeling, the third on remote sensing data analysis, the fourth on big data and augmented reality, and finally, the fifth is focused on VGI.

> **Jorge Rocha and Patrícia Abrantes** Institute of Geography and Spatial Planning, University of Lisbon, Lisbon, Portugal

> > **1**

Section 1

Geographic Information

Systems and Science
