URBAN GEO BIG DATA

Geo-Spatial Big Data Analysis: An Overview

Advance increasing interest in large-scale, highresolution, real-time geographic information system (GIS) applications and spatial big data processing, traditional GIS are not efficient enough to handle due to limited computational capabilities. Geospatial analytics in big data needed new approaches that are flexible, non-parametric and should be able for dynamic modeling with non-linear proces...

Geo-spatial Big Data Mining Techniques

As stated in literature by several authors, there has been literally big-bang explosion in data acquired in recent times. This is especially so about the geographical or geospatial data. The huge volume of data acquired in different formats, structured, unstructured ways, having large complexity and non-stop generation of these data have posed an insurmountable challenge in scientific and busin...

Data Mining Approaches for Geo-Spatial Big Data: Uncertainty Issues

The availability of a vast amount of heterogeneous information from a variety of sources ranging from satellite imagery to the Internet has been termed as the problem of Big Data. Currently there is a great emphasis on the huge amount of geophysical data that has a spatial basis or spatial aspects. To effectively utilize such volumes of data, data mining techniques are needed to manage discover...

Constructing gazetteers from volunteered Big Geo-Data based on Hadoop

Traditional gazetteers are built and maintained by authoritative mapping agencies. In the age of Big Data, it is possible to construct gazetteers in a data-driven approach by mining rich volunteered geographic information (VGI) from the Web. In this research, we build a scalable distributed platform and a high-performance geoprocessing workflow based on the Hadoop ecosystem to harvest crowd-sou...

User-Generated Big Data and Urban Morphology