Big optical Earth observation (EO) data analytics usually start from numerical, sub-symbolic reflectance values that lack inherent semantic information (meaning) and require interpretation. However, interpretation is an ill-posed problem that is diff...
Incremental computing is becoming increasingly important for processing large-scale datasets. In satellite imagery, spatial resolution, temporal depth, and large files pose significant computational challenges, requiring efficient architectures to ma...
In the face of tight natural resources and complex as well as volatile environments, and in order to meet the pressure brought by population growth, we need to overcome a series of challenges. As a new data management paradigm, the Earth Observation...
The amount of data that Sentinel fleet is generating over a territory such as Catalonia makes it virtually impossible to manually download and organize as files. The Open Data Cube (ODC) offers a solution for storing big data products in an efficient...
This study aims at assessing the feasibility of automatically producing analysis-ready radiometrically terrain-corrected (RTC) Synthetic Aperture Radar (SAR) gamma nought backscatter data for ingestion into a data cube for use in a large spatio-tempo...
With the application of big data in Earth observation, satellite imagery data are gradually becoming important means of observation for monitoring changes in vegetation, water bodies, and urbanization. Therefore, new satellite imagery data organizati...
In recent years, the need to protect and conserve biodiversity has become more critical than ever before, as a prerequisite for both sustainable development and the very survival of the human species. This has made it a priority for the scientific co...
The integration of the raster data cube alongside another form of geospatial data (e.g., vector data) raises considerable challenges when it comes to managing and representing it using knowledge graphs. Such integration can play an invaluable role in...
As applications generate massive amounts of data streams, the requirement for ways to analyze and cluster this data has become a critical field of research for knowledge discovery. Data stream clustering’s primary objective and goal are to acqu...
This study investigates decadal trends in vegetation cover in Djibouti from 1990 to 2020, addressing challenges related to its arid climate and limited resources. Using Digital Earth Africa’s Open Data Cube and thirty years of Landsat imagery,...
A research alliance between the Commonwealth Scientific and Industrial Research Organization and Geoscience Australia was established in relation to Digital Earth Australia, to develop a Synthetic Aperture Radar (SAR)-enabled Data Cube capability for...
At present, accessing and processing Earth Observation (EO) data on different cloud platforms requires users to exercise distinct communication strategies as each backend platform is designed differently. The openEO API (Application Programming Inter...
The conflict between environmental conservation and agricultural production highlights the need for precise land use and land cover (LULC) mapping to support agro-environmental-related policies. Satellite image time series from the Moderate Resolutio...
Mountainous regions are particularly vulnerable to climate change, and the impacts are already extensive and observable, the implications of which go far beyond mountain boundaries and the environmental sectors. Monitoring and understanding climate a...
This study introduces a multi-cloud model that combines private and public cloud services for processing and managing satellite images. The multi-cloud service is established by incorporating private clouds within organizations and integrating them w...
Significant amounts of energy are consumed in the commercial building sector, resulting in various adverse environmental issues. To reduce energy consumption and improve energy efficiency in commercial buildings, it is necessary to develop effective...
The Horn of Africa has sensitive, arid ecosystems, with its vegetation commonly distressed by factors such as climate change, population increase, unstable water resources, and rarely enforced land use management practices. These factors make countri...
A radar echo signal received from a cone-shaped target with precession contains micro-Doppler (m-D) information from different effective scattering centers. By taking full advantage of the m-D information, this paper proposes a parameter estimation a...
Earth observation imagery have traditionally been expensive, difficult to find and access, and required specialized skills and software to transform imagery into actionable information. This has limited adoption by the broader science community. Chan...
Cloud-based Earth observation platforms, such as data cubes, enable reproducible analyses of long-term satellite time series for climate and urban studies. In parallel, Essential Climate Variables (ECVs) provide a standardised framework for monitorin...
A decision support system (DSS) is a software application designed to determine suitable actions for specific organizational situations. Its main component is a data repository analyzed to produce decisions. This paper describes the data organization...
Recently, remote sensing image time series analysis has being widely used to investigate the dynamics of environments over time. Many studies have combined image time series analysis with machine learning methods to improve land use and cover change...
In Spain, inbound European tourism exhibits marked territorial imbalances whose evolution is difficult to characterize using aggregate indicators. This study analyzes its spatiotemporal patterns at the municipal level between July 2019 and December 2...
Earth observation data cubes are increasingly used as a data structure to make large collections of satellite images easily accessible to scientists. They hide complexities in the data such that data users can concentrate on the analysis rather than...
Floodplain wetlands are globally important ecosystems, yet altered hydrological regimes increasingly disrupt the balance between woody and non-woody vegetation. In Australia’s regulated Murray–Darling Basin, it remains unclear whether woo...
Earth Observation Data Cubes (EODC) have emerged as a promising solution to efficiently and effectively handle Big Earth Observation (EO) Data generated by satellites and made freely and openly available from different data repositories. The aim of t...
In this study, we used the DeepESDL framework to exploit multivariate data cubes for the identification and characterization of frontal zones in the Alboran Sea throughout the year 2023. By operating directly within a unified data hypercube architect...
Current methods for monitoring deforestation from satellite data at sub-annual scales require pixel time series to have many historical observations in the reference period to model normal forest dynamics before detecting deforestation. However, in s...
The emerging global trend of satellite operators producing analysis-ready data combined with open source tools for managing and exploiting these data are leading to more and more countries using Earth observation data to drive progress against key na...
Earth observations data cubes (EODCs) are a paradigm transforming the way users interact with large spatio-temporal Earth observation (EO) data. It enhances connections between data, applications and users facilitating management, access and use of a...
Coastal and maritime regions and their entities face accelerated degradation due to the combined effects of environmental stressors and anthropogenic activities. Coastal degradation can be identified, visualized and estimated through periodic monitor...
Due to their multiple sources and structures, big spatial data require adapted tools to be efficiently collected, summarized and analyzed. For this purpose, data are archived in data warehouses and explored by spatial online analytical processing (SO...
In recent years, several new technologies have enabled OLAP processing over Big Data sources. Among these technologies, we highlight those that allow data pre-aggregation because of their demonstrated performance in data querying. This is the case of...
Environmental sustainability is nowadays a major global issue that requires efficient and effective responses from governments. Essential variables (EV) have emerged in different scientific communities as a means to characterize and follow environmen...
Environmental issues become an increasing global concern because of the continuous pressure on natural resources. Earth observations (EO), which include both satellite/UAV and in-situ data, can provide robust monitoring for various environmental conc...
Fires are one of the main sources of disturbance in fire-sensitive ecosystems such as the Amazon. Any attempt to characterize their impacts and establish actions aimed at combating these events presupposes the correct identification of the affected a...
Urban function labels in multi-dimensional geo-data cubes (GDCs) assign a single dominant function to each voxel, discarding within-voxel composition. This study extends multi-dimensional grid-point (MDGP) scaling from isotropic two-dimensional raste...
All-to-all broadcasting means to distribute the exclusive message of each node in the network to all other nodes. It can be handled by rings, and a Hamiltonian cycle is a ring that visits each vertex exactly once. Multiple edge-disjoint Hamiltonian c...
In a situation where cities are increasingly being developed vertically and complexly, a novel approach for analyzing vertical urban functional patterns is proposed. For this purpose, a multi-dimensional GDC (Geo Data Cube) consisting of spatial and...
In vitro three-dimensional (3D) culturing is considered essential in many biological fields. However, the imaging of developed 3D formations is often difficult, especially if the size of the sample is relatively large. The z-resolution of fluorescent...
Magnetometers are important sensors with applications in the attitude determination and control systems of satellites. CubeSats have certain limitations related to power, mass, and volume. Due to this, CubeSat magnetometers are not separated from oth...
The calculation of the pressure field on and around solid bodies exposed to external flow is of paramount importance to a number of engineering applications. However, conventional pressure measurement techniques are inherently linked to problems prin...
Modern positioning and sensor technology enable the acquisition of movement positions and attributes on an unprecedented scale. Therefore, a large amount of trajectory data can be used to analyze various movement phenomena. In cartography, a common w...
There is an increasing amount of free and open Earth observation (EO) data, yet more information is not necessarily being generated from them at the same rate despite high information potential. The main challenge in the big EO analysis domain is pro...
The ionosphere is a fundamental component of the Earth’s atmosphere, impacting human activities such as communication transmissions, navigation systems, satellite functions, power network systems, and natural gas pipelines, even endangering hum...
Monitoring and predicting land surface phenology (LSP) are essential for understanding ecosystem dynamics, climate change impacts, and forest and agricultural productivity. Satellite Earth observation (EO) missions have played a crucial role in the a...
The Earth Observation (EO) domain can provide valuable information products that can significantly reduce the cost of mapping flood extent and improve the accuracy of mapping and monitoring systems. In this study, Landsat 5, 7, and 8 were utilized to...
Humans learn from a lot of information sources to make decisions. Once this information is learned in the brain, spatio-temporal associations are made, connecting all these sources (variables) in space and time represented as brain connectivity. In r...
Forests represent important habitats for species and provide multiple ecosystem services for human well-being. Preserving forests and other terrestrial ecosystems has become crucial to halt desertification, land degradation, and biodiversity loss wor...
An important part of Open Data is of a statistical nature and describes economic and social indicators monitoring population size, inflation, trade, and employment. Combining and analyzing Open Data from multiple datasets and sources enable the perfo...
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