Dorian Gorgan

Satellite Image Processing Applications in MedioGRID

This paper presents a high level architectural specification of MedioGRID, a research project aiming at implementing a real-time satellite image processing system for extracting relevant environmental and meteorological parameters on a grid system. The presentation focuses on the key architectural decisions of the GRID-aware satellite image processing system, highlighting the technologies for each of the major components. An essential part of managing a global data grid is a monitoring system that is able to monitor and track all the site facilities, networks, and tasks in progress, all in real time. Considering this issue the paper analyzes the possible grid monitoring approaches, proposes a solution and presents a set of monitoring results for the MedioGRID data management subsystem

MedioGrid: A Grid-based Platform for Satellite Image Processing

Recently a new Grid-based software platform was developed to allow remote sensing image processing for preventing disasters like river floods and forest fires. While several innovative components were presented in research papers in the last year, this paper presents a state-of-the-art of the whole platform and exposes the novelty elements that distinguish it from other similar approaches.

Experiments on ESIP—Environment oriented satellite data processing platform

The paper describes the features and the architectures of the ESIP (Environment oriented Satellite Data Processing) and gProcess platforms, supporting the Grid based satellite imagery processing. Features such as Grid services, interactive components, workflow execution, process monitoring, and service composition provided by gProcess, and satellite image processing operators provided by ESIP are described. The paper exemplifies the workflow based description of the GEMI vegetation index in ESIP. The experiments highlight and evaluate as well the performance of the GEMI workflow execution over the SEE-GRID infrastructure.

Grid based satellite image processing platform for Earth observation application development

Satellite images supply important information on earth surface, weather, clime, geographic areas, vegetation, and natural phenomena. Processing of satellite data requires high computation resources and flexible tools in order to search, discover, and reveal the main information, to experiment new algorithms, and to include them into new Earth Observation applications. This paper describes the features and the architectures of the ESIP and gProcess platforms, supporting the Grid based satellite imagery processing. The development methodology of Earth Observation applications is highlighted as well in order to hide the Grid complexity to the user.

Grid Based Training Environment for Earth Observation

The content of the satellite images supplies information on the earth surface, weather, clime, geographic areas, pollution, and natural phenomena. Unfortunately, the real time supervision and the teaching related techniques require high computation and massive spatial data storage resources. This paper presents the Grid oriented GiSHEO eLearning Environment (eGLE) supporting the training and experimental practice in Earth Observation (EO). eGLE facilitates specific access for the academic and scientific community to on-demand services related to specific EO applications. The teachers have the ability to easily create lessons for different topics, supporting both the knowledge presentation and Grid based processing. The eGLE environment is based on the gProcess platform developed through the MedioGrid national project. The gProcess platform consists of a set of tools supporting the flexible description, instantiation, scheduling and execution of the workflow based Grid processing.

Diagrammatic Description of Satellite Image Processing Workflow

Multiple experiments on grid based satellite imagery classification require flexible descriptions of the processing workflow. The user develops the processing workflow pattern by visual tools in terms of satellite image multi-band spectral data. Each pattern may be stored into a repository and instantiated later for a particular area and time of the satellite image. The specific processing can be scheduled for the right time and data flow. By this flexible approach the user can optimize the processing algorithm for appropriate resource configuration, image type and on-line data feeding.

Grid based architectural components for SWAT model calibration

Different scenarios based on environmental changes and water quality models could be used to assess the sustainability and vulnerability of a particular geographical region. The gSWAT application allows the calibration of SWAT models and the execution of different scenarios based on calibrated SWAT model over the Grid infrastructure. Based on the requirements for the SWAT models, lots of input and output data, the high number of simulations that must be performed in the calibration process, the Grid could offer both the storing and execution solutions. This paper presents the gSWAT system highlighting the architectural components and presenting some test cases to assess the system performances.

Grid based environment application development methodology

The satellite image oriented processing in the Grid based environment applications needs flexible tools, process description and execution in order to reveal significant information The main processing consists of imagery classification which is actually a search of information through combinations of multispectral bands of satellite data The Grid based application development process should assist the developer to implement required functionality, but making transparent to the user the Grid complexity and the mapping of the conceptual application over the physical Grid resources The paper exemplifies the gProcess based Grid application development methodology throughout the development phases of the GreenView environment application, and analyzes the efficiency of such an approach The primary aim of the GreenView application is the refinement of surface and vegetation parameters in SEE and CE regions based on satellite images The GreenView application is based on ESIP platform, which lies on the gProcess toolset specific satellite image processing operators and services.

Comparative parallel execution of SWAT hydrological model on multicore and grid architectures

The paper presents a comparative analysis made on the calibration of a large-scale model, executed both on grid and multicore architectures. The goal is to highlight the advantages brought by the grid infrastructure over the multicore architecture, especially for large-scale applications, which require large amounts of data and a large number of executions. The large-scale application used as a case study for this research work is the calibration of a large-scale SWAT hydrological model, covering the Danube River Basin.

Grid Computing Usability Heuristics in Practice

Grid Computing is a relatively new, distributed computing technology, based on sharing different types of computational resources, located in various geographic locations. Usability evaluation for Grid Computing applications brings new challenges. There is a need for new usability evaluation methods or at least for the use of traditional evaluations in novel ways. A set of specific usability heuristics was defined and validated. A usability checklist to be used when applying Grid Computing heuristics is also proposed.