Big Earth data are produced from satellite observations, Internet-of-Things, model
simulations, and other sources. The data embed unprecedented insights and spatiotemporal …

Finding geospatial data has been a big challenge regarding the data size and heterogeneity
across various domains. Previous work has explored using machine learning to improve …

Discovering and accessing geospatial data presents a significant challenge for the Earth
sciences community as massive amounts of data are being produced on a daily basis. In this …

Massive spatiotemporal data scheduling in a cloud environment play a significant role in
real-time visualization. Existing methods focus on preloading, prefetching, multithread …

Cloud computing has become a prime approach for providing reliable and scalable
computing infrastructure for a variety of geographical information applications. This paper …

With the advent of the era of big data, research and application of big data analysis and
mining is more and more attention, in order to face huge amounts of data collection statistics …

Urban system, as a sub-component of the Earth system, is complex and dynamic being
composed of numerous interactions among natural, human-built, and social entities (Jing et …

Finding Earth science data has been a challenging problem given both the quantity of data
available and the heterogeneity of the data across a wide variety of domains. Current search …