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  • GBV  (12)
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  • 1
    Book
    Book
    Evaluation, analysis and optimization of direct-push sensor systems (2012)
    Ilmenau : Wiss.-Verl. Thüringen
    Details
    UID:
    (DE-627)727385798
    Format: XX, 109 S. , Ill., graph. Darst.
    ISBN: 9783936404593
    Series Statement: Forschungsberichte aus dem Institut für Informationstechnik / Technische Universität Ilmenau 14
    Content: Globale ökologische Fragestellungen bezüglich der Böden und des Grundwassers stellen für die Menschheit eine große Herausforderung dar. Die Erkundung des oberflächennahen Erdkörpers liefert dabei einen wesentlichen Beitrag zur Beantwortung, Bewertung und zum Ableiten von Lösungen wesentlicher Umweltfragstellungen. Zu dessen Erkundung werden moderne Direct-Push Sensorsysteme eingesetzt, die eine schnelle und effiziente in-situ Messung in einem vertikalen Profil erlauben. Für die zukünftige Entwicklung dieser Erkundungstechnologie wird in der vorliegenden Arbeit eine systematische Klassifikation und Beschreibung herausgearbeitet. Zur Bewertung und Optimierung bestehender Sensorsysteme wird ein methodischer Ansatz vorgestellt, welcher auf der Analyse mittels Experimenten auf Labor- und Feldskala und deren mathematischen Modellierung basiert. Diese Methode zur Analyse von Direct-Push Sensorsystemen ist geeignet, um sie in deduktiver Form bei synthetischen Entwicklungen und Implementierungen von physikalischen, chemischen oder biologischen Sensorsystemen anzuwenden. Eine wesentliche Anwendung von Direct-Push Sensorsystemen ist die Erkundung von Kontaminationen in Böden und Grundwasser. Eines dieser Sensorsysteme stellt das Membrane Interface Probe (MIP) Verfahren dar, welches sich bei der Anwendung als nicht zuverlässig herausgestellt hat. Zur Bewertung, Analyse und Optimierung dieses Sensorsystems werden in der vorliegenden Arbeit mit dem methodischen Ansatz zur Analyse die wesentlichsten Einflussparameter und Übertragungsfunktionen dieses Systems ermittelt. Zur Optimierung der Messmethode wird die Kopplung eines mobilen Massenspektrometers als online Detektor vorgeschlagen, um die Interpretation von gemessenen Daten wesentlich zu verbessern.
    Note: Zugl.: Ilmenau, Techn. Univ., Diss., 2011
    Language: English
    Keywords: Sondierung ; Umweltprobe ; Probenahme ; Messsystem ; Bohrlochsonde ; Sensorsystem ; Messsystem ; Sensorsystem ; Membranverfahren ; Bodenverschmutzung ; Grundwasserverschmutzung ; Hochschulschrift
    URL: Kurzbeschreibung
    URL: Inhaltsverzeichnis
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  • 2
    Online Resource
    Online Resource
    Monitoring vegetation- and geodiversity with remote sensing and traits (2024)
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    UID:
    (DE-627)1880603675
    Format: 20 , Illustrationen
    ISSN: 1471-2962
    Content: Geodiversity has shaped and structured the Earth's surface at all spatio-temporal scales, not only through long-term processes but also through medium- and short-term processes. Geodiversity is, therefore, a key control and regulating variable in the overall development of landscapes and biodiversity. However, climate change and land use intensity are leading to major changes and disturbances in bio- and geodiversity. For sustainable ecosystem management, temporal, economically viable and standardized monitoring is needed to monitor and model the effects and changes in vegetation- and geodiversity. RS approaches have been used for this purpose for decades. However, to understand in detail how RS approaches capture vegetation- and geodiversity, the aim of this paper is to describe how five features of vegetation- and geodiversity are captured using RS technologies, namely: (i) trait diversity, (ii) phylogenetic/genese diversity, (iii) structural diversity, (iv) taxonomic diversity and (v) functional diversity. Trait diversity is essential for establishing the other four. Traits provide a crucial interface between in situ, close-range, aerial and space-based RS monitoring approaches. The trait approach allows complex data of different types and formats to be linked using the latest semantic data integration techniques, which will enable ecosystem integrity monitoring and modelling in the future.
    In: Philosophical transactions of the Royal Society. A, Mathematical, physical and engineering sciences, London : Royal Society, 1996, 382(2024), 2269, 1471-2962
    In: volume:382
    In: year:2024
    In: number:2269
    In: extent:20
    Language: English
    DOI: 10.1098/rsta.2023.0058
    DOI: 10.25673/115621
    URL: https://doi.org/10.1098/rsta.2023.0058
    URL: kostenfrei
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  • 3
    Article
    Article
    City of the Future: Urban Monitoring based on Smart Sensors and Open Technologies (2019)
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    Details
    UID:
    (DE-627)1743457596
    ISBN: 9789897583551
    In: SENSORNETS (8. : 2019 : Prag), SENSORNETS 2019, [Setúbal, Portugal] : SCITEPRESS - Science and Technology Publications, Lda., 2019, (2019), Seite 116-120, 9789897583551
    In: year:2019
    In: pages:116-120
    Language: English
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  • 4
    Online Resource
    Online Resource
    Spatial retrieval of broadband dielectric spectra (2018)
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    UID:
    (DE-627)1040093205
    Format: 22
    ISSN: 1424-8220
    Content: A broadband soil dielectric spectra retrieval approach (1 MHz - 2 GHz) has been implemented for a layered half space. The inversion kernel consists of a two-port transmission line forward model in the frequency domain and a constitutive material equation based on a power law soil mixture rule (Complex Refractive Index Model - CRIM). The spatially-distributed retrieval of broadband dielectric spectra was achieved with a global optimization approach based on a Shuffled Complex Evolution (SCE) algorithm using the full set of the scattering parameters. For each layer, the broadband dielectric spectra were retrieved with the corresponding parameters thickness, porosity, water saturation and electrical conductivity of the aqueous pore solution. For the validation of the approach, a coaxial transmission line cell measured with a network analyzer was used. The possibilities and limitations of the inverse parameter estimation were numerically analyzed in four scenarios. Expected and retrieved layer thicknesses, soil properties and broadband dielectric spectra in each scenario were in reasonable agreement. Hence, the model is suitable for an estimation of in-homogeneous material parameter distributions. Moreover, the proposed frequency domain approach allows an automatic adaptation of layer number and thickness or regular grids in time and/or space.
    In: Sensors, Basel : MDPI, 2001, 18(2018), 9, Artikel-ID 2780, 1424-8220
    In: volume:18
    In: year:2018
    In: number:9
    In: elocationid:2780
    In: extent:22
    Language: English
    DOI: 10.3390/s18092780
    URL: Volltext  (kostenfrei)
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    GBV
  • 5
    Online Resource
    Online Resource
    Automated Workflow for High-Resolution 4D Vegetation Monitoring Using Stereo Vision (2024)
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    UID:
    (DE-627)1879644983
    ISSN: 2072-4292
    Content: Precision agriculture relies on understanding crop growth dynamics and plant responses to short-term changes in abiotic factors. In this technical note, we present and discuss a technical approach for cost-effective, non-invasive, time-lapse crop monitoring that automates the process of deriving further plant parameters, such as biomass, from 3D object information obtained via stereo images in the red, green, and blue (RGB) color space. The novelty of our approach lies in the automated workflow, which includes a reliable automated data pipeline for 3D point cloud reconstruction from dynamic scenes of RGB images with high spatio-temporal resolution. The setup is based on a permanent rigid and calibrated stereo camera installation and was tested over an entire growing season of winter barley at the Global Change Experimental Facility (GCEF) in Bad Lauchstädt, Germany. For this study, radiometrically aligned image pairs were captured several times per day from 3 November 2021 to 28 June 2022. We performed image preselection using a random forest (RF) classifier with a prediction accuracy of 94.2% to eliminate unsuitable, e.g., shadowed, images in advance and obtained 3D object information for 86 records of the time series using the 4D processing option of the Agisoft Metashape software package, achieving mean standard deviations (STDs) of 17.3–30.4 mm. Finally, we determined vegetation heights by calculating cloud-to-cloud (C2C) distances between a reference point cloud, computed at the beginning of the time-lapse observation, and the respective point clouds measured in succession with an absolute error of 24.9–35.6 mm in depth direction. The calculated growth rates derived from RGB stereo images match the corresponding reference measurements, demonstrating the adequacy of our method in monitoring geometric plant traits, such as vegetation heights and growth spurts during the stand development using automated workflows.
    In: Remote sensing, Basel : MDPI, 2009, 16(2024), 3, Artikel-ID 541, 2072-4292
    In: volume:16
    In: year:2024
    In: number:3
    In: elocationid:541
    Language: English
    DOI: 10.3390/rs16030541
    URL: https://doi.org/10.3390/rs16030541
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  • 6
    Online Resource
    Online Resource
    Dielectric spectra reconstruction of layered multi-phase soil (2018)
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    Details
    UID:
    (DE-627)1029985200
    Format: 4
    ISBN: 9781538645932
    In: International Conference on Electromagnetic Wave Interaction with Water and Moist Substances (12. : 2018 : Lublin), 2018 12th International Conference on Electromagnetic Wave Interaction with Water and Moist Substances (ISEMA), [Piscataway, NJ] : IEEE, 2018, (2018), 9781538645932
    In: year:2018
    In: extent:4
    Language: English
    DOI: 10.1109/ISEMA.2018.8442324
    URL: Volltext
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  • 7
    Article
    Article
    Spatial retrieval of broadband dielectric spectra (2017)
    Show associated volumes
    Details
    UID:
    (DE-627)1009428101
    Content: A broadband frequency domain forward model including dispersion, dielectric and electrical losses of the materials has been implemented. Tue spatially distributed retrieval of the broadband dielectric spectra was achieved with an inverse modeling scheme based on a shuffled complex evolution algorithm. Tue possibilities and limitations of the inverse parameter estimation were analyzed without any prior information about the constitutive material properties of the material.
    In: International Symposium on Theoretical Electrical Engineering (19. : 2017 : Ilmenau), XIX International Symposium on Theoretical Electrical Engineering, Ilmenau (Thür.) : Technische Universität, 2017, (2017), Seite 55
    In: year:2017
    In: pages:55
    Language: English
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  • 8
    Online Resource
    Online Resource
    Ecosystem Integrity Remote Sensing : Modelling and Service Tool—ESIS/Imalys (2024)
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    Details
    UID:
    (DE-627)1884339514
    Format: 25
    ISSN: 2072-4292
    Content: One of the greatest challenges of our time is monitoring the rapid environmental changes taking place worldwide at both local and global scales. This requires easy-to-use and ready-to-implement tools and services to monitor and quantify aspects of bio- and geodiversity change and the impact of land use intensification using freely available and global remotely sensed data, and to derive remotely sensed indicators. Currently, there are no services for quantifying both raster- and vector-based indicators in a “compact tool”. Therefore, the main innovation of ESIS/Imalys is having a remote sensing (RS) tool that allows for RS data processing, data management, and continuous and discrete quantification and derivation of RS indicators in one tool. With the ESIS/Imalys project (Ecosystem Integrity Remote Sensing—Modelling and Service Tool), we try to present environmental indicators on a clearly defined and reproducible basis. The Imalys software library generates the RS indicators and remote sensing products defined for ESIS. This paper provides an overview of the functionality of the Imalys software library. An overview of the technical background of the implementation of the Imalys library, data formats and the user interfaces is given. Examples of RS-based indicators derived using the Imalys tool at pixel level and at zone level (vector level) are presented. Furthermore, the advantages and disadvantages of the Imalys tool are discussed in detail in order to better assess the value of Imalys for users and developers. The applicability of the indicators will be demonstrated through three ecological applications, namely: (1) monitoring landscape diversity, (2) monitoring landscape structure and landscape fragmentation, and (3) monitoring land use intensity and its impact on ecosystem functions. Despite the integration of large amounts of data, Imalys can run on any PC, as the processing and derivation of indicators has been greatly optimised. The Imalys source code is freely available and is hosted and maintained under an open source license. Complete documentation of all methods, functions and derived indicators can be found in the freely available Imalys manual. The user-friendliness of Imalys, despite the integration of a large amount of RS data, makes it another important tool for ecological research, modelling and application for the monitoring and derivation of ecosystem indicators from local to global scale.
    In: Remote sensing, Basel : MDPI, 2009, 16(2024), 7, Artikel-ID 1139, 2072-4292
    In: volume:16
    In: year:2024
    In: number:7
    In: elocationid:1139
    In: extent:25
    Language: English
    DOI: 10.3390/rs16071139
    URL: https://doi.org/10.3390/rs16071139
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  • 9
    Online Resource
    Online Resource
    In situ/remote sensing integration to assess forest health-a review (2016)
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    UID:
    (DE-627)1823187641
    Format: Diagramme, Illustrationen
    ISSN: 2072-4292
    Content: For mapping, quantifying and monitoring regional and global forest health, satellite remote sensing provides fundamental data for the observation of spatial and temporal forest patterns and processes. While new remote-sensing technologies are able to detect forest data in high quality and large quantity, operational applications are still limited by deficits of in situ verification. In situ sampling data as input is required in order to add value to physical imaging remote sensing observations and possibilities to interlink the forest health assessment with biotic and abiotic factors. Numerous methods on how to link remote sensing and in situ data have been presented in the scientific literature using e.g. empirical and physical-based models. In situ data differs in type, quality and quantity between case studies. The irregular subsets of in situ data availability limit the exploitation of available satellite remote sensing data. To achieve a broad implementation of satellite remote sensing data in forest monitoring and management, a standardization of in situ data, workflows and products is essential and necessary for user acceptance. The key focus of the review is a discussion of concept and is designed to bridge gaps of understanding between forestry and remote sensing science community. Methodological approaches for in situ/remote-sensing implementation are organized and evaluated with respect to qualifying for forest monitoring. Research gaps and recommendations for standardization of remote-sensing based products are discussed. Concluding the importance of outstanding organizational work to provide a legally accepted framework for new information products in forestry are highlighted.
    In: Remote sensing, Basel : MDPI, 2009, 8(2016), 6, Artikel-ID 471, 2072-4292
    In: volume:8
    In: year:2016
    In: number:6
    In: elocationid:471
    Language: English
    DOI: 10.3390/rs8060471
    URL: kostenfrei
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  • 10
    Online Resource
    Online Resource
    Remote Sensing of Geomorphodiversity Linked to Biodiversity - Part III : Traits, Processes and Remote Sensing Characteristics (2022)
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    UID:
    (DE-627)1823165397
    Format: Illustrationen
    ISSN: 2072-4292
    Content: Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring of traits and trait variations of geomorphology and its processes, from the local to the continental scale. To implement and better understand RS techniques and the spectral indicators derived from them in the monitoring of geomorphology, this paper presents a new perspective for the definition and recording of five characteristics of geomorphodiversity with RS, namely: geomorphic genesis diversity, geomorphic trait diversity, geomorphic structural diversity, geomorphic taxonomic diversity, and geomorphic functional diversity. In this respect, geomorphic trait diversity is the cornerstone and is essential for recording the other four characteristics using RS technologies. All five characteristics are discussed in detail in this paper and reinforced with numerous examples from various RS technologies. Methods for classifying the five characteristics of geomorphodiversity using RS, as well as the constraints of monitoring the diversity of geomorphology using RS, are discussed. RS-aided techniques that can be used for monitoring geomorphodiversity in regimes with changing land-use intensity are presented. Further, new approaches of geomorphic traits that enable the monitoring of geomorphodiversity through the valorisation of RS data from multiple missions are discussed as well as the ecosystem integrity approach. Likewise, the approach of monitoring the five characteristics of geomorphodiversity recording with RS is discussed, as are existing approaches for recording spectral geomorhic traits/ trait variation approach and indicators, along with approaches for assessing geomorphodiversity. It is shown that there is no comparable approach with which to define and record the five characteristics of geomorphodiversity using only RS data in the literature. Finally, the importance of the digitization process and the use of data science for research in the field of geomorphology in the 21st century is elucidated and discussed.
    In: Remote sensing, Basel : MDPI, 2009, 14(2022), 9, Artikel-ID 2279, 2072-4292
    In: volume:14
    In: year:2022
    In: number:9
    In: elocationid:2279
    Language: English
    DOI: 10.3390/rs14092279
    URL: kostenfrei
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