相关论文: Microsoft TerraServer: A Spatial Data Warehouse

In this paper we present a preliminary analysis over the largest publicly accessible web dataset: the Common Crawl Corpus. We measure nine web characteristics from two levels of granularity using MapReduce and we comment on the initial…

Despite the growing need for data of more and more sophisticated 3D reconstruction pipelines, we can still observe a scarcity of suitable public datasets. Existing 3D datasets are either low resolution, limited to a small amount of scenes,…

We present GeoRocket, a software for the management of very large geospatial datasets in the cloud. GeoRocket employs a novel way to handle arbitrarily large datasets by splitting them into chunks that are processed individually. The…

Due to the advancement in computer communication and storage technologies, large amount of image data is available on World Wide Web (WWW). In order to locate a particular set of images the available search engines may be used with the help…

Constructing complex queries on data which combines spatial, temporal, and spectral aspects is a challenging and error-prone process. Query interfaces of general-purpose database management systems fall short in providing intuitive support…

Science is becoming very data intensive1. Today's astronomy datasets with tens of millions of galaxies already present substantial challenges for data mining. In less than 10 years the catalogs are expected to grow to billions of objects,…

Worldwide image geolocalization, which aims to predict the GPS coordinates of any image on Earth, remains challenging due to global visual diversity. Recent generative approaches based on Retrieval-Augmented Generation (RAG) and Large…

We introduce OpenEarthMap, a benchmark dataset, for global high-resolution land cover mapping. OpenEarthMap consists of 2.2 million segments of 5000 aerial and satellite images covering 97 regions from 44 countries across 6 continents, with…

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 amount of remote sensing (RS) data has increased at an unexpected scale, due to the rapid progress of earth-observation and the growth of satellite RS and sensor technologies. Traditional relational databases attend their limit to meet…

We present our experiences using cloud computing to support data-intensive analytics on satellite imagery for commercial applications. Drawing from our background in high-performance computing, we draw parallels between the early days of…

We make a case for "planetary computing" -- infrastructure to handle the ingestion, transformation, analysis and publication of global data products for furthering environmental science and enabling better informed policy-making. We draw on…

For more than a decade there has been a push in the planetary science community to support interoperable methods for accessing and working with geospatial data. Common geospatial data products for planetary research include image mosaics,…

This paper describes by example how astronomers can use cloud-computing resources offered by Amazon Web Services (AWS) to create new datasets at scale. We have created from existing surveys an atlas of the Galactic Plane at 16 wavelengths…

Hyperatlas is an open standard intended to facilitate the large-scale federation of image-based data. The subject of hyperatlas is the space of sphere-to-plane projection mappings (the FITS-WCS information), and the standard consists of…

The collection of ecological data in the field is essential to diagnose, monitor and manage ecosystems in a sustainable way. Since acquisition of this information through traditional methods are generally time-consuming, due to the…

Traditional science searched for new objects and phenomena that led to discoveries. Tomorrow's science will combine together the large pool of information in scientific archives and make discoveries. Scienthists are currently keen to…

Data warehouse store and provide access to large volume of historical data supporting the strategic decisions of organisations. Data warehouse is based on a multidimensional model which allow to express user's needs for supporting the…

Increasing quantities of scientific data are becoming readily accessible via online repositories such as those provided by Figshare and Zenodo. Geoscientific simulations in particular generate large quantities of data, with several research…

Astronomy has a long history of acquiring, systematizing, and interpreting large quantities of data. Starting from the earliest sky atlases through the first major photographic sky surveys of the 20th century, this tradition is continuing…