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F.Z. Fiedrich
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2 records found
1
Bachelor thesis
(2024)
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F.Z. Fiedrich, Dessislava Petrova-Antonova, J.C. van Gemert, K.A. Hildebrandt
The detection of changes in an area over time using remotely sensed data such as images is referred to as change detection. It has a large range of applications. For example, changes in buildings can analysed for urban planning. Many conventional image processing and machine learning-based algorithms have been developed for the purpose of change detection. Conventional non-classification algorithms have advantages in their reduced computational cost. Remotely sensed images vary in their spatial resolution, which is the area a pixel covers on the Earth surface. This work aims to explore how the spatial resolution impacts conventional non-classification pixel-based techniques in the urban change detection context, to provide insight into their performance with regards to detecting urban-related change over different resolutions. A systematic experiment is conducted by considering the LEVIR-CD and OSCD test sets in their initial as well as multiple downsampled resolutions. The change detection algorithms Change Vector Analysis (CVA) and Iteratively Reweighted Multivariate Alteration Detection (IR-MAD) are applied to the data individually. For creating binary change labels on a pixel-level, the Otsu algorithm is applied. A set of performance metrics is calculated, and trends in the metrics values over the resolutions are analysed. The data shows some trends towards improved metric values for lower spatial resolutions. The degree of the trends varies and is dependent on the algorithm and dataset. Overall, further research is necessary to consider influencing factors such as the amount of pixels in images, to refine the processing steps, and to broaden the scope of the experiment.
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The detection of changes in an area over time using remotely sensed data such as images is referred to as change detection. It has a large range of applications. For example, changes in buildings can analysed for urban planning. Many conventional image processing and machine learning-based algorithms have been developed for the purpose of change detection. Conventional non-classification algorithms have advantages in their reduced computational cost. Remotely sensed images vary in their spatial resolution, which is the area a pixel covers on the Earth surface. This work aims to explore how the spatial resolution impacts conventional non-classification pixel-based techniques in the urban change detection context, to provide insight into their performance with regards to detecting urban-related change over different resolutions. A systematic experiment is conducted by considering the LEVIR-CD and OSCD test sets in their initial as well as multiple downsampled resolutions. The change detection algorithms Change Vector Analysis (CVA) and Iteratively Reweighted Multivariate Alteration Detection (IR-MAD) are applied to the data individually. For creating binary change labels on a pixel-level, the Otsu algorithm is applied. A set of performance metrics is calculated, and trends in the metrics values over the resolutions are analysed. The data shows some trends towards improved metric values for lower spatial resolutions. The degree of the trends varies and is dependent on the algorithm and dataset. Overall, further research is necessary to consider influencing factors such as the amount of pixels in images, to refine the processing steps, and to broaden the scope of the experiment.
Space Missions Minor - Engineering Study Case
Venturing into the Heliosphere
Student report
(2024)
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I. Joosten, R. Cotar, F.Z. Fiedrich, Samuel van Erk, F.M. Heijink, I.M. Jagt, H.E. Reitsma, J.H.C. van der Meer, M. van Pelt, Marie van de Sande, I. Akay
In the history of humankind only three spacecraft have ever ventured into interstellar space [2]. How- ever, none of them have been equipped for proper exploration of interstellar space, all of these five spacecraft were equipped for exploring the outer planets and objects of the solar system but not for interstellar space and/or the heliosphere. In part due to this lack of in-situ measurements of the inter- stellar medium and the heliosphere, not a lot is known of these areas. This report aims to provide a detailed overview of the concept of an interstellar heliosphere probe to investigate the heliosphere and the interstellar medium. This report will examine the requirements that are needed for such a spacecraft and explain why these requirements exist. Moreover, a component level description of the various subsystems typically involved in spacecraft manufacturing will be provided. With these subsystems, estimations of the mass, cost, power and data will be given when appropriate in an overview of all the subsystems.
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In the history of humankind only three spacecraft have ever ventured into interstellar space [2]. How- ever, none of them have been equipped for proper exploration of interstellar space, all of these five spacecraft were equipped for exploring the outer planets and objects of the solar system but not for interstellar space and/or the heliosphere. In part due to this lack of in-situ measurements of the inter- stellar medium and the heliosphere, not a lot is known of these areas. This report aims to provide a detailed overview of the concept of an interstellar heliosphere probe to investigate the heliosphere and the interstellar medium. This report will examine the requirements that are needed for such a spacecraft and explain why these requirements exist. Moreover, a component level description of the various subsystems typically involved in spacecraft manufacturing will be provided. With these subsystems, estimations of the mass, cost, power and data will be given when appropriate in an overview of all the subsystems.