Search results for "Data cube"
showing 7 items of 7 documents
Earth system data cubes unravel global multivariate dynamics
2020
Understanding Earth system dynamics in light of ongoing human intervention and dependency remains a major scientific challenge. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. Today, many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome these hurdles and meet the growing interdisciplinary need for data-intensive research; using data cubes is one promising avenue. Here, we introduce the concept of Earth system data cu…
Nonlinear PCA for Spatio-Temporal Analysis of Earth Observation Data
2020
Remote sensing observations, products, and simulations are fundamental sources of information to monitor our planet and its climate variability. Uncovering the main modes of spatial and temporal variability in Earth data is essential to analyze and understand the underlying physical dynamics and processes driving the Earth System. Dimensionality reduction methods can work with spatio-temporal data sets and decompose the information efficiently. Principal component analysis (PCA), also known as empirical orthogonal functions (EOFs) in geophysics, has been traditionally used to analyze climatic data. However, when nonlinear feature relations are present, PCA/EOF fails. In this article, we pro…
Approximating Empirical Surface Reflectance Data through Emulation: Opportunities for Synthetic Scene Generation
2019
Collection of spectroradiometric measurements with associated biophysical variables is an essential part of the development and validation of optical remote sensing vegetation products. However, their quality can only be assessed in the subsequent analysis, and often there is a need for collecting extra data, e.g., to fill in gaps. To generate empirical-like surface reflectance data of vegetated surfaces, we propose to exploit emulation, i.e., reconstruction of spectral measurements through statistical learning. We evaluated emulation against classical interpolation methods using an empirical field dataset with associated hyperspectral spaceborne CHRIS and airborne HyMap reflectance spectra…
Low-Dimensional Representations of Earth System Processes
2020
In times of global change, we must closely monitor the state of our planet in order to understand gradual or abrupt changes early on. In fact, each of the Earth's subsystems-i.e. the biosphere, atmosphere, hydrosphere, cryosphere, and anthroposphere-can be analyzed from a multitude of data streams. However, since it is very hard to jointly interpret multiple monitoring data streams in parallel, one often aims for some summarizing indicator. Climate indices, for example, summarize the state of atmospheric circulation in a region, e.g. the Multivariate ENSO (El Ñino-Southern Oscillation) Index. Indicator approaches have been used extensively to describe socioeconomic data too, and a range of …
Fragtique: Applying an OO Database Distribution Strategy to Data Warehouse
2001
We propose a strategy for distribution of a relational data warehouse organized according to a star schema. We adapt fragmentation and allocation strategies that were developed for OO databases. We split the most-often-accessed dimension table into fragments by using primary horizontal fragmentation. The derived fragmentation then divides the fact table into fragments. Other dimension tables are not fragmented since they are presumed to be sufficiently small. Allocation of fragments encompasses duplication of non-fragmented dimension tables that we call a closure.
Using OLAP Data Cubes in Business Intelligence
2016
Abstract The purpose of this paper is to demonstrate that it is possible to develop business intelligence projects in big and medium-size organizations, only with Microsoft products, used in accordance with standard OLAP cube technology, and presented possible alternatives, in relation with the requested functions.
Laser illumination designs for snapshot multi-spectral-line imaging
2019
For multi-spectral imaging, both acquisition time of the spectral image set and the spectral bandwidth of each image have to be minimized. Ultimate performance can be achieved if the set of monochromatic (single-wavelength) spectral images is obtained with a single snapshot — a technique provisionally called "snapshot multi-spectral-line imaging" or SMSLI. Using contemporary RGB colour cameras, up to three spectral line images can be extracted from a snapshot image data cube at specific illumination that comprises only three spectral lines, each of them positioned within one of the detection bands (R, G or B) [1]. Techniques able to provide more spectral line images are under development, a…