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Results 1-8 of 8 (Search time: 0.038 seconds).
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  • Development of a knowledge driven rule set for classification of submerged aquatic vegetation (SAV) in a clear water stream

    • Authors: Visser, Fleur;  Advisor: -;  Participants: - (2016)

  • A recent attempt at mapping submerged aquatic vegetation (SAV) species composition of a clear water stream in Belgium from ultrahigh resolution, multispectral photographs, using object based image analysis (OBIA), resulted in a low, but consistent overall classification accuracy (53-61%). Since the results were obtained with a single rule set they show promise for the development of an automated tool to map SAV despite the challenges of its submerged environment. This extended abstract investigates to what extent difficulties with species delineation in the validation data may have influenced the results. We compare class boundaries, as drawn by experts along image segmentation outlines, with the results from the expert knowledge driven classification rules. A comparison for ‘pure’ ...
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  • An object-based meta knowledge model for a distributed image interpretation system

    • Authors: Costa, G.A.O.P.;  Advisor: -;  Participants: - (2016)

  • This paper introduces the interpretation meta knowledge model devised for the InterCloud platform. InterCloud is a remote sensing image interpretation platform designed to run on computer clusters or on cloud computing infrastructure. The system is capable of distributing data processing tasks, such as segmentation, feature extraction and classification procedures over the processing elements of a computer grid in a transparent way to the user. Moreover, InterCloud can exploit the potential scalability offered by commercial cloud computing infrastructure services, enabling the interpretation of very large remote sensing datasets in an efficient way. The proposed meta model comprises two types of knowledge: declarative and procedural. The former describes the characteristics of the c...
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  • An object-based image interpretation application on cloud computing infrastructure

    • Authors: Antunes, R.R.;  Advisor: -;  Participants: - (2016)

  • The rapid increase in the number and in the spatial resolution of aerial and orbital Earth observation systems is generating a huge amount of remote sensing data that need to be readily transformed into useful information for policy and decision makers. A possible approach to tackle the demand for image interpretation tools that can deal efficiently with very large volumes of data is to employ data analysis methods based on distributed computing. This paper presents an object-based, remote sensing image interpretation application executed over cloud-computing infrastructure. The application is implemented with InterCloud, a novel image interpretation platform designed to run on computer grids (physical clusters or cloud-computing infrastructure). The application described in this pa...
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  • The Spatial Development Framework for Implementation of National, Urban Policy

    • Authors: Sliuzas, R.V.; Nduwayezu, G;  Advisor: -;  Participants: - (2016)

  • The uncontrolled urban growth is the key characteristics in most cities in less developed countries. However, having a good understanding of the key drivers of the city's growth dynamism has proven to be a key instrument to manage urban growth. This paper investigates the main determinants of Kigali city growth looking at how they changed over time and also how they contributed to the city change through different Logistic Regression models. First, it analyses the spatio-temporal growth of Kigali city through a consistent set of land cover maps of during the period 1987, 1999, 2009 and 2014. Second, after building a Logistic Regression model; the main drivers of Kigali city growth are identified. Third to characterize the future pattern of the city in next 26 years, three scenarios ...
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  • Modeling urban growth in Kigali city Rwanda

    • Authors: Sliuzas, R.V.; Nduwayezu, G;  Advisor: -;  Participants: - (2016)

  • The uncontrolled urban growth is the key characteristics in most cities in less developed countries. However, having a good understanding of the key drivers of the city's growth dynamism has proven to be a key instrument to manage urban growth. This paper investigates the main determinants of Kigali city growth looking at how they changed over time and also how they contributed to the city change through different Logistic Regression models. First, it analyses the spatio-temporal growth of Kigali city through a consistent set of land cover maps of during the period 1987, 1999, 2009 and 2014. Second, after building a Logistic Regression model; the main drivers of Kigali city growth are identified. Third to characterize the future pattern of the city in next 26 years, three scenarios ...
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  • Athena : center of excellence in Cyprus in the field of remote sensing for cultural heritage in the areas of archaeology and cultural heritage

    • Authors: Hadjimitsis, D.G.;  Advisor: -;  Participants: - (2016)

  • In periods of economic instability, national considerations are overruling the process of European integration. Cultural Heritage (CH) is an integral element of a European set of values, and respect for heritage is vital for developing a common European identity. The CH sector has always been facing a number of challenges that have increased with the financial crisis that has hit Europe. To name a few, these include the decrease of public budgets, urbanisation, globalisation, and technological changes. Within this context, CH professionals are seeking to improve currently used methodologies, in order to better understand, protect and valorise the common European past and common identity. The use of satellite and other remote sensing (RS) technologies has progressively been establish...
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  • Interseg : a distributed image segmentation tool

    • Authors: Happ, P.N.;  Advisor: -;  Participants: - (2016)

  • Motivated by the rapidly increase of remote sensing data over the last years, this paper presents a tool designed for distributed image segmentation. InterSeg is able to handle efficiently very large high-resolution images using scalable distributed segmentation methods over computer clusters. Through a graphic user interface, InterSeg hides the distributed processing complexity, allowing the user to easily perform distributed image segmentation on a cloud-computing environment. Experiments carried out with the tool attest its potential scalability and its capability to exploit distributed processing over many cluster nodes. Moreover, as an opensource solution, the software can be extended with different segmentation algorithms and methods.
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  • Satellite based multi-scale methods to support the governance of Brazilian low-carbon agriculture (abc plan)

    • Authors: Simoes, M.;  Advisor: -;  Participants: - (2016)

  • Brazilian Low Carbon Agriculture Plan (ABC Plan) is one the initiatives that places the climate in the agricultural agenda towards a more sustainable and adapted agriculture under global changes. Among the several practices listed and supported by the ABC Plan, zero tillage and integrated crop-livestock-forestry systems including the recovery of degraded pasture are the most relevant ones. Those practices introduced a complexity to agriculture landscape image analyse. The objective of this paper is to present the GeoABC Project and preliminary procedures using OBIA and satellite based multi-scale methods to monitor the introduced scenario of a new agriculture land use dynamics.
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