Related papers: Challenges and Solutions for Utilizing Earth Obser…
In the era of big data astronomy, next generation telescopes and large sky surveys produce data sets at the TB or even PB level. Due to their large data volumes, these astronomical data sets are extremely difficult to transfer and analyze…
The development of analytical software for big Earth observation data faces several challenges. Designers need to balance between conflicting factors. Solutions that are efficient for specific hardware architectures can not be used in other…
Data exploration and visualization systems are of great importance in the Big Data era. Exploring and visualizing very large datasets has become a major research challenge, of which scalability is a vital requirement. In this survey, we…
Recent developments and research in modern machine learning have led to substantial improvements in the geospatial field. Although numerous deep learning architectures and models have been proposed, the majority of them have been solely…
This paper presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2 million global time series samples from NASA's Harmonized Landsat and Sentinel-2…
Due to the surge of spatio-temporal data volume, the popularity of location-based services and applications, and the importance of extracted knowledge from spatio-temporal data to solve a wide range of real-world problems, a plethora of…
The U.S. Virtual Astronomical Observatory was a software infrastructure and development project designed both to begin the establishment of an operational Virtual Observatory (VO) and to provide the U.S. coordination with the international…
We review some of the scientific opportunities and technical challenges posed by the exploration of the large digital sky surveys, in the context of a Virtual Observatory (VO). The VO paradigm will profoundly change the way observational…
Understanding the earth's climate system and how it might be changing is a preeminent scientific challenge. Global climate models are used to simulate past, present, and future climates, and experiments are executed continuously on an array…
The integration of data science into Geographic Information Systems (GIS) has facilitated the evolution of these tools into complete spatial analysis platforms. The adoption of machine learning and big data techniques has equipped these…
The modern era is characterised as an era of information or Big Data. This has motivated a huge literature on new methods for extracting information and insights from these data. A natural question is how these approaches differ from those…
This paper reviews the most important information fusion data-driven algorithms based on Machine Learning (ML) techniques for problems in Earth observation. Nowadays we observe and model the Earth with a wealth of observations, from a…
In the Virtual Observatory era, where we intend to expose scientists (or software agents on their behalf) to a stream of observations from all existing facilities, the ability to access and to further interpret the origin, relationships,…
Recent advances in data collection and computational statistics coupled with increases in computer processing power, along with the plunging costs of storage are making technologies to effectively analyze large sets of heterogeneous data…
We provide a brief, and inevitably incomplete overview of the use of Machine Learning (ML) and other AI methods in astronomy, astrophysics, and cosmology. Astronomy entered the big data era with the first digital sky surveys in the early…
We live in a world where data generation is omnipresent. Innovations in computer hardware in the last few decades coupled with increasingly reliable connectivity among them have fueled this phenomenon. We are constantly creating and…
Over the past decades and even centuries, the astronomical community has accumulated a signif-icant heritage of recorded observations of a great many astronomical objects. Those records con-tain irreplaceable information about long-term…
With the shifting focus of organizations and governments towards digitization of academic and technical documents, there has been an increasing need to use this reserve of scholarly documents for developing applications that can facilitate…
The immense volume of data generated by Earth observation (EO) satellites presents significant challenges in transmitting it to Earth over rate-limited satellite-to-ground communication links. This paper presents an efficient downlink…
The exponential growth of big data has transformed how large organisations leverage information to drive innovation, optimise processes, and maintain competitive advantages. However, managing and extracting insights from vast, heterogeneous…