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  • 1
    Online Resource
    Online Resource
    Remote Sensing of Regional Soil Moisture (2022)
    Basel : MDPI - Multidisciplinary Digital Publishing Institute
    Details
    UID:
    gbv_1794541179
    Format: 1 Online-Ressource (426 p.)
    ISBN: 9783036529578 , 9783036529561
    Content: Requests for regional soil moisture observations are increasing to parameterize complex hydrological models, to assess the impact of land-use changes, and to develop climate adaption strategies in the agricultural sector. Spatial land-use patterns have an impact on the soil water balance and groundwater recharge. Soil moisture is therefore a key parameter for the long-term monitoring and development of sustainable land-management and landscape design strategies that mitigate regional water scarcity and droughts. For example, the spatial organization of hedges or tree rows related to open land and wind direction avoids soil erosion, limits local evaporation, and increases local soil water storage. Since the early 1980s, satellite missions have been designed to monitor proxies for soil moisture, mainly at the national and global scale, with a relatively coarse pixel resolution and low accuracy. The local effects of weather and climate are very dynamic in space and time. Thus, a strong need exists for more accurate, regional-scale remote sensing products for soil moisture. The transfer of existing, proof-of-concept algorithms to region-specific monitoring frameworks is urgent. This Special Issue provides an overview of current developments on remote sensing-based soil moisture observations that are applicable at a regional scale. The compendium of research papers demonstrates the benefits of concurrently utilizing multi-source remote sensing data and in situ measurements through: - Using additional data and site-specific knowledge; - Combining empirical and physical approaches; - Developing concepts to deal with mixed pixels
    Note: English
    Language: English
    URL: kostenfrei
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    Online Resource
    Stabi Berlin
    UB Potsdam
  • 2
    Book
    Book
    Soil parameter retrieval under vegetation cover using SAR polarimetry (2012)
    Potsdam
    Details
    UID:
    gbv_727868594
    Format: XXVIII, 236 S. , Ill., graph. Darst.
    Content: Soil conditions under vegetation cover and their spatial and temporal variations from point to catchment scale are crucial for understanding hydrological processes within the vadose zone, for managing irrigation and consequently maximizing yield by precision farming. Soil moisture and soil roughness are the key parameters that characterize the soil status. In order to monitor their spatial and temporal variability on large scales, remote sensing techniques are required. Therefore the determination of soil parameters under vegetation cover was approached in this thesis by means of (multi-angular) polarimetric SAR acquisitions at a longer wavelength (L-band, lambda=23cm). In this thesis, the penetration capabilities of L-band are combined with newly developed (multi-angular) polarimetric decomposition techniques to separate the different scattering contributions, which are occurring in vegetation and on ground. Subsequently the ground components are inverted to estimate the soil characteristics. The novel (multi-angular) polarimetric decomposition techniques for soil parameter retrieval are physically-based, computationally inexpensive and can be solved analytically without any a priori knowledge. Therefore they can be applied without test site calibration directly to agricultural areas. The developed algorithms are validated with fully polarimetric SAR data acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR) for three different study areas in Germany. The achieved results reveal inversion rates up to 99% for the soil moisture and soil roughness retrieval in agricultural areas. However, in forested areas the inversion rate drops significantly for most of the algorithms, because the inversion in forests is invalid for the applied scattering models at L-band. The validation against simultaneously acquired field measurements indicates an estimation accuracy (root mean square error) of 5-10vol.% for the soil moisture (range of in situ values: 1-46vol.%) and of 0.37-0.45cm for the soil roughness (range of in situ values: 0.5-4.0cm) within the catchment. Hence, a continuous monitoring of soil parameters with the obtained precision, excluding frozen and snow covered conditions, is possible. Especially future, fully polarimetric, space-borne, long wavelength SAR missions can profit distinctively from the developed polarimetric decomposition techniques for separation of ground and volume contributions as well as for soil parameter retrieval on large spatial scales.
    Note: Potsdam, Univ., Diss., 2012
    Additional Edition: Online-Ausg. Jagdhuber, Thomas Soil parameter retrieval under vegetation cover using SAR polarimetry Potsdam, 2012
    Language: English
    Keywords: Hochschulschrift
    Library Location Call Number Volume/Issue/Year Availability
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    UB Potsdam get availability status
  • 3
    Book
    Book
    Soil parameter retrieval under vegetation cover using SAR polarimetry : 21 Tabellen (2012)
    Köln : DLR, Bibliotheks- und Informationswesen
    Details
    UID:
    b3kat_BV040744230
    Format: XXVIII, 236 S. , IIl., graph. Darst., Kt.
    Edition: Als Ms. gedr.
    Series Statement: Forschungsbericht / Deutsches Zentrum für Luft- und Raumfahrt 2012,24
    Note: Zugl.: Potsdam, Univ., Diss., 2012 (Nicht für den Austausch)
    Additional Edition: Erscheint auch als Online-Ausgabe Jagdhuber, Thomas Soil parameter retrieval under vegetation cover using SAR polarimetry
    Language: English
    Subjects: Engineering
    RVK:
    ZI 9560
    Keywords: Bodenfeuchte ; Bodenbedeckung ; Radar ; Synthetische Apertur ; Hochschulschrift
    URL: Inhaltsverzeichnis
    Author information: Jagdhuber, Thomas 1979-
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    TU Berlin get availability status
  • 4
    Online Resource
    Online Resource
    Soil parameter retrieval under vegetation cover using SAR polarimetry (2012)
    Potsdam
    Details
    UID:
    gbv_729554805
    Format: Online-Ressource (PDF-Datei: XXVIII, 236 S., 29.539 kB) , Ill., graph. Darst.
    Content: Soil conditions under vegetation cover and their spatial and temporal variations from point to catchment scale are crucial for understanding hydrological processes within the vadose zone, for managing irrigation and consequently maximizing yield by precision farming. Soil moisture and soil roughness are the key parameters that characterize the soil status. In order to monitor their spatial and temporal variability on large scales, remote sensing techniques are required. Therefore the determination of soil parameters under vegetation cover was approached in this thesis by means of (multi-angular) polarimetric SAR acquisitions at a longer wavelength (L-band, lambda=23cm). In this thesis, the penetration capabilities of L-band are combined with newly developed (multi-angular) polarimetric decomposition techniques to separate the different scattering contributions, which are occurring in vegetation and on ground. Subsequently the ground components are inverted to estimate the soil characteristics. The novel (multi-angular) polarimetric decomposition techniques for soil parameter retrieval are physically-based, computationally inexpensive and can be solved analytically without any a priori knowledge. Therefore they can be applied without test site calibration directly to agricultural areas. The developed algorithms are validated with fully polarimetric SAR data acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR) for three different study areas in Germany. The achieved results reveal inversion rates up to 99% for the soil moisture and soil roughness retrieval in agricultural areas. However, in forested areas the inversion rate drops significantly for most of the algorithms, because the inversion in forests is invalid for the applied scattering models at L-band. The validation against simultaneously acquired field measurements indicates an estimation accuracy (root mean square error) of 5-10vol.% for the soil moisture (range of in situ values: 1-46vol.%) and of 0.37-0.45cm for the soil roughness (range of in situ values: 0.5-4.0cm) within the catchment. Hence, a continuous monitoring of soil parameters with the obtained precision, excluding frozen and snow covered conditions, is possible. Especially future, fully polarimetric, space-borne, long wavelength SAR missions can profit distinctively from the developed polarimetric decomposition techniques for separation of ground and volume contributions as well as for soil parameter retrieval on large spatial scales.
    Note: Potsdam, Univ., Diss., 2012
    Additional Edition: Druck-Ausg. Jagdhuber, Thomas Soil parameter retrieval under vegetation cover using SAR polarimetry Potsdam, 2012
    Language: English
    Keywords: Hochschulschrift
    URN: urn:nbn:de:kobv:517-opus-60519
    URL: kostenfrei
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    Online Resource
    UB Potsdam
  • 5
    Online Resource
    Online Resource
    Remote Sensing of Regional Soil Moisture (2022)
    Basel : MDPI
    Details
    UID:
    b3kat_BV047903158
    Format: 1 Online-Ressource
    ISBN: 9783036529578
    Content: Requests for regional soil moisture observations are increasing to parameterize complex hydrological models, to assess the impact of land-use changes, and to develop climate adaption strategies in the agricultural sector. Spatial land-use patterns have an impact on the soil water balance and groundwater recharge. Soil moisture is therefore a key parameter for the long-term monitoring and development of sustainable land-management and landscape design strategies that mitigate regional water scarcity and droughts. For example, the spatial organization of hedges or tree rows related to open land and wind direction avoids soil erosion, limits local evaporation, and increases local soil water storage. Since the early 1980s, satellite missions have been designed to monitor proxies for soil moisture, mainly at the national and global scale, with a relatively coarse pixel resolution and low accuracy. The local effects of weather and climate are very dynamic in space and time. Thus, a strong need exists for more accurate, regional-scale remote sensing products for soil moisture. The transfer of existing, proof-of-concept algorithms to region-specific monitoring frameworks is urgent. This Special Issue provides an overview of current developments on remote sensing-based soil moisture observations that are applicable at a regional scale. The compendium of research papers demonstrates the benefits of concurrently utilizing multi-source remote sensing data and in situ measurements through: - Using additional data and site-specific knowledge; - Combining empirical and physical approaches; - Developing concepts to deal with mixed pixels.
    Additional Edition: Erscheint auch als Druck-Ausgabe, Hardcover ISBN 978-3-0365-2956-1
    Language: English
    DOI: 10.3390/books978-3-0365-2957-8
    URL: Volltext  (kostenfrei)
    Author information: Schulz, Karsten 1964-
    Author information: Pause, Marion 1979-
    Author information: Jagdhuber, Thomas 1979-
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    Online Resource
    Fulltext
    EUV Frankfurt
  • 6
    Online Resource
    Online Resource
    Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics (2019)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_23311
    Format: 1 Online-Ressource (51 Seiten)
    Content: In the face of rapid global change it is imperative to preserve geodiversity for the overallconservation of biodiversity. Geodiversity is important for understanding complex biogeochemicaland physical processes and is directly and indirectly linked to biodiversity on all scales of ecosystemorganization. Despite the great importance of geodiversity, there is a lack of suitable monitoringmethods. Compared to conventional in-situ techniques, remote sensing (RS) techniques providea pathway towards cost-effective, increasingly more available, comprehensive, and repeatable, aswell as standardized monitoring of continuous geodiversity on the local to global scale. This papergives an overview of the state-of-the-art approaches for monitoring soil characteristics and soilmoisture with unmanned aerial vehicles (UAV) and air- and spaceborne remote sensing techniques.Initially, the definitions for geodiversity along with its five essential characteristics are provided,with an explanation for the latter. Then, the approaches of spectral traits (ST) and spectral traitvariations (STV) to record geodiversity using RS are defined. LiDAR (light detection and ranging),thermal and microwave sensors, multispectral, and hyperspectral RS technologies to monitor soilcharacteristics and soil moisture are also presented. Furthermore, the paper discusses current andfuture satellite-borne sensors and missions as well as existing data products. Due to the prospectsand limitations of the characteristics of different RS sensors, only specific geotraits and geodiversitycharacteristics can be recorded. The paper provides an overview of those geotraits.
    Content: Peer Reviewed
    In: Basel : MDPI, 11,20
    Language: English
    DOI: 10.3390/rs11202356
    DOI: 10.18452/22703
    URN: urn:nbn:de:kobv:11-110-18452/23311-5
    URL: Volltext  (kostenfrei)
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    Online Resource
    Fulltext
    HU Berlin
  • 7
    Online Resource
    Online Resource
    Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces (2020)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_25777
    Format: 1 Online-Ressource (61 Seiten)
    Content: The status, changes, and disturbances in geomorphological regimes can be regarded as controlling and regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, and global scales is not only necessary to conserve geodiversity, but also to preserve biodiversity, as well as to improve biodiversity conservation and ecosystem management. Numerous remote sensing (RS) approaches and platforms have been used in the past to enable a cost-effective, increasingly freely available, comprehensive, repetitive, standardized, and objective monitoring of geomorphological characteristics and their traits. This contribution provides a state-of-the-art review for the RS-based monitoring of these characteristics and traits, by presenting examples of aeolian, fluvial, and coastal landforms. Different examples for monitoring geomorphology as a crucial discipline of geodiversity using RS are provided, discussing the implementation of RS technologies such as LiDAR, RADAR, as well as multi-spectral and hyperspectral sensor technologies. Furthermore, data products and RS technologies that could be used in the future for monitoring geomorphology are introduced. The use of spectral traits (ST) and spectral trait variation (STV) approaches with RS enable the status, changes, and disturbances of geomorphic diversity to be monitored. We focus on the requirements for future geomorphology monitoring specifically aimed at overcoming some key limitations of ecological modeling, namely: the implementation and linking of in-situ, close-range, air- and spaceborne RS technologies, geomorphic traits, and data science approaches as crucial components for a better understanding of the geomorphic impacts on complex ecosystems. This paper aims to impart multidimensional geomorphic information obtained by RS for improved utilization in biodiversity monitoring.
    Content: Peer Reviewed
    In: Basel : MDPI, 12,22
    Language: English
    DOI: 10.3390/rs12223690
    DOI: 10.18452/25097
    URN: urn:nbn:de:kobv:11-110-18452/25777-8
    URL: Volltext  (kostenfrei)
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    Online Resource
    Fulltext
    HU Berlin
  • 8
    Online Resource
    Online Resource
    Remote Sensing of Geomorphodiversity Linked to Biodiversity—Part III: Traits, Processes and Remote Sensing Characteristics (2022)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_27133
    Format: 1 Online-Ressource (48 Seiten)
    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.
    Content: Peer Reviewed
    In: Basel : MDPI, 14,9
    Language: English
    DOI: 10.3390/rs14092279
    DOI: 10.18452/26454
    URN: urn:nbn:de:kobv:11-110-18452/27133-9
    URL: Volltext  (kostenfrei)
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    Online Resource
    Fulltext
    HU Berlin
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