We live in the era of ‘Big Data’. In particular, Geospatial data, whether captured through remote sensors (e.g., satellite imagery) or generated from large-scale simulations (e.g., climate change models) have always been significantly large in size. Over the last decade however, advances in instrumentation and computation has seen the volume, variety, velocity, and veracity of this data increase exponentially. Of the 2.5 quintillion (1018) bytes of data that are generated on a daily basis across the globe, a large portion (arguably as much as 80%) is found to be geo-referenced. Therefore, this special issue is dedicated to the innovative theories, methods, analytics, and applications of geospatial big data
Without geospatial data management, today´s challenges in big data applications such as earth observ...
In lieu of an abstract, this is an excerpt from the first page. The exponential growth in the vol...
Advances in machine learning research are pushing the limits of geographical information sciences (G...
We live in the era of ‘Big Data’. In particular, Geospatial data, whether captured through remote se...
The convergence of big data and geospatial computing has brought challenges and opportunities to GIS...
The convergence of big data and geospatial computing has brought forth challenges and opportunities ...
Very large data sets are the common rule in automated mapping, GIS, remote sensing, and what we can ...
Most data sets and streams have a geospatial component. Some people even claim that about 80% of all...
Geospatial big data present a new set of challenges and opportunities for cartographic researchers i...
As stated in literature by several authors, there has been literally big-bang explosion in data acqu...
Technological advances have enabled the emerge of ‘Big Data’ through the production, processing, ana...
In this paper GeoAI is introduced as an emergent spatial analytical framework for data-intensive GIS...
Thinking Big Data in Geography offers a practical state-of-the-field overview of big data as both a ...
Open and persistent access to past, present, and future scientific data is fundamental for transpare...
Looking back at the last four decades, the technologies that have been developed for Earth observati...
Without geospatial data management, today´s challenges in big data applications such as earth observ...
In lieu of an abstract, this is an excerpt from the first page. The exponential growth in the vol...
Advances in machine learning research are pushing the limits of geographical information sciences (G...
We live in the era of ‘Big Data’. In particular, Geospatial data, whether captured through remote se...
The convergence of big data and geospatial computing has brought challenges and opportunities to GIS...
The convergence of big data and geospatial computing has brought forth challenges and opportunities ...
Very large data sets are the common rule in automated mapping, GIS, remote sensing, and what we can ...
Most data sets and streams have a geospatial component. Some people even claim that about 80% of all...
Geospatial big data present a new set of challenges and opportunities for cartographic researchers i...
As stated in literature by several authors, there has been literally big-bang explosion in data acqu...
Technological advances have enabled the emerge of ‘Big Data’ through the production, processing, ana...
In this paper GeoAI is introduced as an emergent spatial analytical framework for data-intensive GIS...
Thinking Big Data in Geography offers a practical state-of-the-field overview of big data as both a ...
Open and persistent access to past, present, and future scientific data is fundamental for transpare...
Looking back at the last four decades, the technologies that have been developed for Earth observati...
Without geospatial data management, today´s challenges in big data applications such as earth observ...
In lieu of an abstract, this is an excerpt from the first page. The exponential growth in the vol...
Advances in machine learning research are pushing the limits of geographical information sciences (G...