Big Data Analytics for Earth Sciences: the EarthServer approach

Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced e-infrastructures. Earth and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and simulations. However, Earth Science data and applications present specificities in terms of relevance of the geospatial information, wide heterogeneity of data models and formats, and complexity of processing. Therefore, Big Earth Data Analytics requires specifically tailored techniques and tools. The EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets, built around a high performance array database technology, and the adoption and enhancement of standards for service interaction (OGC WCS and WCPS). The EarthServer solution, led by the collection of requirements from scientific communities and international initiatives, provides a holistic approach that ranges from query languages and scalability up to mobile access and visualization. The result is demonstrated and validated through the development of lighthouse applications in the Marine, Geology, Atmospheric, Planetary and Cryospheric science domains

Modeling Infrastructure Maintenance Contracts in a Geospatial Database

Automation in every field has introduced various means to increase productivity and efficiency. Recently, the road maintenance industry has adopted automation. However, automated scheduling, pricing, budgeting, reporting and invoicing of work are restricted by the provided format of data. In addition, the available information to depict real state of environment and capabilities of machines is also one of the obstacles to automate the aforementioned processes. This research work addresses these problems by modeling the data in database that will automate the processes. This thesis focuses on studying existing models of road. The information from existing road models is extracted and compared with each other. Afterwards, the necessary data comprising of work requirements along with related machinery is studied, and the useful information is extracted. The road model is then fused with the machine and contract data model. This fusion results to give information of roads, machines and work requirements which are missing in currently available information. The implemented approach is validated with the help of real world contract area. This results in providing the model which will automate the maintenance processes. The resulted model is aligned with the expert view

OPTIMIZING CLIENT-SERVER COMMUNICATION FOR REMOTE SPATIAL DATABASE ACCESS

Technological advances in recent years have opened ways for easier creation of spatial data. Every day, vast amounts of data are collected by both governmental institutions (e.g., USGS, NASA) and commercial entities (e.g., IKONOS). This process is driven by increased popularity and affordability across the whole spectrum of collection methods, ranging from personal GPS units to satellite systems. Many collection methods such as satellite systems produce data in raster format. Often, such raster data is analyzed by the researchers directly, while at other times such data is used to produce the final dataset in vector format. With the rapidly increasing supply of data, more applications for this data are being developed that are of interest to a wider consumer base. The increasing popularity of spatial data viewers and query tools with end users introduces a requirement for methods to allow these basic users to access this data for viewing and querying instantly and without much effort. In our work, we focus on providing remote access to vector-based spatial data, rather than raster data. We explore new ways of allowing visualization of both spatial and non-spatial data stored in a central server database on a simple client connected to this server by possibly a slow and unreliable connection. We considered usage scenarios where transferring the whole database for processing on the client was not feasible. This is due to the large volume of data stored on the server as well as a lack of computing power on the client and a slow link between the two. We focus on finding an optimal way of distributing work between the server, clients, and possibly other entities introduced into the model for query evaluation and data management. We address issues of scalability for clients that have only limited access to system resources (e.g., a Java applet). Methods to allow these clients to provide an interactive user interface, even for databases of arbitrary size, are also examined

Activities of the Remote Sensing Information Sciences Research Group

Topics on the analysis and processing of remotely sensed data in the areas of vegetation analysis and modelling, georeferenced information systems, machine assisted information extraction from image data, and artificial intelligence are investigated. Discussions on support field data and specific applications of the proposed technologies are also included

An intelligent Geographic Information System for design

Recent advances in geographic information systems (GIS) and artificial intelligence (AI) techniques have been summarised, concentrating on the theoretical aspects of their construction and use. Existing projects combining AI and GIS have also been discussed, with attention paid to the interfacing methods used and problems uncovered by the approaches. AI and GIS have been combined in this research to create an intelligent GIS for design. This has been applied to off-shore pipeline route design. The system was tested using data from a real pipeline design project. [Continues.

Modeling, designing and developing a multidisciplinary geodatabase GIS with the physical implementation of RDBMS in conjunction with CAD and different GIS applications for the development of coastal /marine environment

The prime significance of Geographic Information System as a multidisciplinary data integrating, analyzing and visualizing tool depends on the organization of data encompassed within the system. This notion calls for the indispensability of structuring diverse raw data with the intention to establish a functional and robust Geodatabase model that safeguard the consistency and integrities of spatial information management.This research work deals with the process of Georelational GIS data modeling, designing andimplementation of a wide spectrum coastal-marine measurement data.To let the research task set in motion; raw coastal related issues have been discussed under the perspective of Coastal Zone Environment. GIS building block entities were selected. Their conceptual interrelationships have been diagrammatically illustrated. SQL’s DDL applied to execute the physical creation, determine dimension, storage and constraints of the entities in an ODBC compliant RDBMS. Likewise, GIS geographic elements were produced applying spatial programs and their integration with attribute database led to the hatching of the object relational GIS.Topologic operations pertaining to gap detection, segmentation, removal of redundant geographicelements was performed using topology clean up spatial and editing tools. Georefrencing of the coastal maps have been performed using a provided ellipsoid and datum (PSAD56) of a case study area (Guayaquil estuary, Ecuador).Interoperability tests among variety GIS applications show feature-transfer-related lose of spatial featuresproperties but successful regeneration of spatial pointers. The process shows the possibility of producingor transforming a functional spatial database from a specific GIS application into another one. Generating object-relational and spatio-temporal queries related to the developed GIS objects resulted in disclosing thematically visualisable spatial maps. The output of the spatial analysis enables us to perform possible spatial correlation of multidisciplinary results and perceive effects associated to certain marine events

Acquisition and Declarative Analytical Processing of Spatio-Temporal Observation Data

A generic framework for spatio-temporal observation data acquisition and declarative analytical processing has been designed and implemented in this Thesis. The main contributions of this Thesis may be summarized as follows: 1) generalization of a data acquisition and dissemination server, with great applicability in many scientific and industrial domains, providing flexibility in the incorporation of different technologies for data acquisition, data persistence and data dissemination, 2) definition of a new hybrid logical-functional paradigm to formalize a novel data model for the integrated management of entity and sampled data, 3) definition of a novel spatio-temporal declarative data analysis language for the previous data model, 4) definition of a data warehouse data model supporting observation data semantics, including application of the above language to the declarative definition of observation processes executed during observation data load, and 5) column-oriented parallel and distributed implementation of the spatial analysis declarative language. The huge amount of data to be processed forces the exploitation of current multi-core hardware architectures and multi-node cluster infrastructures

Spatial ontologies for architectural heritage

Informatics and artificial intelligence have generated new requirements for digital archiving, information, and documentation. Semantic interoperability has become fundamental for the management and sharing of information. The constraints to data interpretation enable both database interoperability, for data and schemas sharing and reuse, and information retrieval in large datasets. Another challenging issue is the exploitation of automated reasoning possibilities. The solution is the use of domain ontologies as a reference for data modelling in information systems. The architectural heritage (AH) domain is considered in this thesis. The documentation in this field, particularly complex and multifaceted, is well-known to be critical for the preservation, knowledge, and promotion of the monuments. For these reasons, digital inventories, also exploiting standards and new semantic technologies, are developed by international organisations (Getty Institute, ONU, European Union). Geometric and geographic information is essential part of a monument. It is composed by a number of aspects (spatial, topological, and mereological relations; accuracy; multi-scale representation; time; etc.). Currently, geomatics permits the obtaining of very accurate and dense 3D models (possibly enriched with textures) and derived products, in both raster and vector format. Many standards were published for the geographic field or in the cultural heritage domain. However, the first ones are limited in the foreseen representation scales (the maximum is achieved by OGC CityGML), and the semantic values do not consider the full semantic richness of AH. The second ones (especially the core ontology CIDOC – CRM, the Conceptual Reference Model of the Documentation Commettee of the International Council of Museums) were employed to document museums’ objects. Even if it was recently extended to standing buildings and a spatial extension was included, the integration of complex 3D models has not yet been achieved. In this thesis, the aspects (especially spatial issues) to consider in the documentation of monuments are analysed. In the light of them, the OGC CityGML is extended for the management of AH complexity. An approach ‘from the landscape to the detail’ is used, for considering the monument in a wider system, which is essential for analysis and reasoning about such complex objects. An implementation test is conducted on a case study, preferring open source applications

Information resources management, 1984-1989: A bibliography with indexes

This bibliography contains 768 annotated references to reports and journal articles entered into the NASA scientific and technical information database 1984 to 1989

An information adaptive system study report and development plan

The purpose of the information adaptive system (IAS) study was to determine how some selected Earth resource applications may be processed onboard a spacecraft and to provide a detailed preliminary IAS design for these applications. Detailed investigations of a number of applications were conducted with regard to IAS and three were selected for further analysis. Areas of future research and development include algorithmic specifications, system design specifications, and IAS recommended time lines