Abstract
Looking back at the last four decades, the technologies that have been developed for Earth observation and mapping can shed a light on the technologies that are trending today and on their challenges. Forty years ago, the first digital pictures decided the fate of remote sensing, photogrammetric engineering, GIS, or, for short: of geomatics. This sudden wave of volumes of data triggered the research in fields that Big Data is plowing today: this paper will examine this transition. First, a rapid survey of the technology through the succession of selected terms, will help identify two main periods in the last four decades. Spatial information appears in 1970 with the preparation of Landsat, and Big Data appears in 2010. The method for exploring geomatics’ contribution to Big Data, is to examine each of the “Vs” that are used today to characterize the latter: volume, velocity, variety, visualization, value, veracity, validity, and variability. Geomatics has been confronted to each of these facets during the period. The discussion compares the answers offered early by geomatics, with the situation in Big Data today. Over a very large range of issues, from signal processing to the semantics of information, geomatics has made contributions to many data models and algorithms. Big Data now enables geographic information to be disseminated much more widely, and to benefit from new information sources, expanding through the Internet of Things towards a future Digital Earth. Some of the lessons learned during the four decades of geomatics can also be lessons for Big Data today, and for the future of geomatics.
Highlights
Besides being a buzzword, Big Data reveals the way technologies spring off, evolve, merge together, replace older ones, or bring new life to forgotten ones
Can we say that geomatics was dealing with Big Data before the term was coined? Let us try to sum up the hurdles that geomatics has had to overcome over four decades, and let us revisit them through the prism of the seven Vs that are invoked to characterize Big Data
Some lessons learned by geomatics may still be useful for Big Data today
Summary
Big Data reveals the way technologies spring off, evolve, merge together, replace older ones, or bring new life to forgotten ones. It enlightens the new context in which these modifications are emerging. This paper reviews the principal issues that the geo-information science (all ±1990), we preferably use the latter.) has confronted since its early stages This retrospective is conducted under the light shed by the Big Data vocabulary: we invoke the popular three Vs (volume, velocity and variety) and additional Vs often suggested (value, validity, veracity, variability, and, occasionally, vulnerability and visualization). Four Decades of Geomatics Revisited through the Vs of Big Data
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
