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  • BSZ  (18)
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  • 1
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    Online Resource
    Advancing learning assignments in remote sensing of the environment through simulation games (2020)
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    UID:
    (DE-627)1823175864
    Format: Diagramme
    ISSN: 2072-4292
    Content: Environmental remote sensing has faced increasing satellite data availability, advanced algorithms for thematic analysis, and novel concepts of ground truth. For that reason, contents and concepts of learning and teaching remote sensing are constantly evolving. This eventually leads to the intuition of methodologically linking academic learning assignments with case-related scopes of application. In order to render case-related learning possible, smart teaching and interactive learning contexts are appreciated and required for remote sensing. That is due to the fact that those contexts are considered promising to trigger and gradually foster students' comprehensive interdisciplinary thinking. To this end, the following contribution introduces the case-related concept of applying simulation games as a promising didactic format in teaching/learning assignments of remote sensing. As to methodology, participating students have been invited to take on individual roles bound to technology-related profiles (e.g., satellite-mission planning, irrigation, etc.) Based on the scenario, stakeholder teams have been requested to elaborate, analyze and negotiate viable solutions for soil moisture monitoring in a defined context. Collaboration has been encouraged by providing the protected, specifically designed remoSSoil-incubator environment. This letter-type paper aims to introduce the simulation game technique in the context of remote sensing as a type of scholarly teaching; it evaluates learning outcomes by adopting certain techniques of scholarship of teaching and learning (SoTL); and it provides food for thought of replicating, adapting and enhancing simulation games as an innovative, disruptive next-generation learning environment in remote sensing.
    In: Remote sensing, Basel : MDPI, 2009, 12(2020), 4, Artikel-ID 735, 2072-4292
    In: volume:12
    In: year:2020
    In: number:4
    In: elocationid:735
    Language: English
    DOI: 10.3390/rs12040735
    URL: kostenfrei
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  • 2
    Online Resource
    Online Resource
    Verbesserung der Informationslage zur Flächennutzung mittels aktueller und zukünftiger Fernerkundungsdaten (2020)
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    UID:
    (DE-627)1823249205
    Format: Illustrationen
    ISBN: 9783944101781
    Content: Die Umweltfernerkundung hat in den vergangenen zwei Jahrzehnten enorme Fortschritte erzielt und bietet Potenzial zur Erweiterung behördlicher Geodatenbestände und vielfältiger Anwendung. Insbesondere abbildende Hyperspektraldaten und Thermaldaten bieten die Möglichkeit für die Bereitstellung neuer thematische Informationen (GIS-Layer). Ein zentrales Einsatzgebiet ist die Analyse, Visualisierung und Bereitstellung von Informationen zu den Wirkungsketten grüner und blauer Infrastruktur in Landschaften und Siedlungen. Der Beitrag vermittelt einen Überblick zu Anwendungen, Aspekten und Anforderungen an die Akquise von Hyperspektraldaten und Thermaldaten.
    In: Dresdner Flächennutzungssymposium (12. : 2020 : Dresden), Flächennutzungsmonitoring XII, Berlin : Rhombos-Verlag, 2020, (2020), Seite 241-250, 9783944101781
    In: year:2020
    In: pages:241-250
    Language: German
    DOI: 10.26084/12dfns-p024
    URL: kostenfrei
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  • 3
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    Online Resource
    Linking Earth Observation and taxonomic, structural and functional biodiversity : Local to ecosystem perspectives (2016)
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    UID:
    (DE-627)1823178545
    Format: Diagramme, Illustrationen
    ISSN: 1872-7034
    Content: Impacts of human civilization on ecosystems threaten global biodiversity. In a changing environment, traditional in situ approaches to biodiversity monitoring have made significant steps forward to quantify and evaluate BD at many scales but still, these methods are limited to comparatively small areas. Earth observation (EO) techniques may provide a solution to overcome this shortcoming by measuring entities of interest at different spatial and temporal scales. This paper provides a comprehensive overview of the role of EO to detect, describe, explain, predict and assess biodiversity. Here, we focus on three main aspects related to biodiversity − taxonomic diversity, functional diversity and structural diversity, which integrate different levels of organization − molecular, genetic, individual, species, populations, communities, biomes, ecosystems and landscapes. In particular, we discuss the recording of taxonomic elements of biodiversity through the identification of animal and plant species. We highlight the importance of the spectral traits (ST) and spectral trait variations (STV) concept for EO-based biodiversity research. Furthermore we provide examples of spectral traits/spectral trait variations used in EO applications for quantifying taxonomic diversity, functional diversity and structural diversity. We discuss the use of EO to monitor biodiversity and habitat quality using different remote-sensing techniques. Finally, we suggest specifically important steps for a better integration of EO in biodiversity research. EO methods represent an affordable, repeatable and comparable method for measuring, describing, explaining and modelling taxonomic, functional and structural diversity. Upcoming sensor developments will provide opportunities to quantify spectral traits, currently not detectable with EO, and will surely help to describe biodiversity in more detail. Therefore, new concepts are needed to tightly integrate EO sensor networks with the identification of biodiversity. This will mean taking completely new directions in the future to link complex, large data, different approaches and models.
    In: Ecological indicators, Amsterdam [u.a.] : Elsevier Science, 2001, 70(2016), Seite 317-339, 1872-7034
    In: volume:70
    In: year:2016
    In: pages:317-339
    Language: English
    DOI: 10.1016/j.ecolind.2016.06.022
    URL: kostenfrei
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  • 4
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    Online Resource
    Regionalization of Coarse Scale Soil Moisture Products Using Fine-Scale Vegetation Indices : Prospects and case study (2020)
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    UID:
    (DE-627)1823176364
    Format: Diagramme, Illustrationen
    ISSN: 2072-4292
    Content: Surface soil moisture (SSM) plays a critical role in many hydrological, biological and biogeochemical processes. It is relevant to farmers, scientists, and policymakers for making effective land management decisions. However, coarse spatial resolution and complex interactions of microwave radiation with surface roughness and vegetation structure present limitations within active remote sensing products to directly monitor soil moisture variations with sufficient detail. This paper discusses a strategy to use vegetation indices (VI) such as greenness, water stress, coverage, vigor, and growth dynamics, derived from Earth Observation (EO) data for an indirect characterization of SSM conditions. In this regional-scale study of a wetland environment, correlations between the coarse Advanced SCATterometer-Soil Water Index (ASCAT-SWI or SWI) product and statistical measurements of four vegetation indices from higher resolution Sentinel-2 data were analyzed. The results indicate that the mean value of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) correlates most strongly to the SWI and that the wet season vegetation traits show stronger linear relation to the SWI than during the dry season. The correlation between VIs and SWI was found to be independent of the underlying dominant vegetation classes which are not derived in real-time. Therefore, fine-scale vegetation information from optical satellite data convey the spatial heterogeneity missed by coarse synthetic aperture radar (SAR)-derived SSM products and is linked to the SSM condition underneath for regionalization purposes.
    In: Remote sensing, Basel : MDPI, 2009, 12(2020), 3, Artikel-ID 551, 2072-4292
    In: volume:12
    In: year:2020
    In: number:3
    In: elocationid:551
    Language: English
    DOI: 10.3390/rs12030551
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  • 5
    Online Resource
    Online Resource
    Monitoring glyphosate-based herbicide treatment using Sentinel-2 time series-A proof-of-principle (2019)
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    UID:
    (DE-627)1823176984
    Format: Diagramme, Illustrationen
    ISSN: 2072-4292
    Content: In this paper we aim to show a proof-of-principle approach to detect and monitor weed management using glyphosate-based herbicides in agricultural practices. In a case study in Germany, we demonstrate the application of Sentinel-2 multispectral time-series data. Spectral broadband vegetation indices were analysed to observe vegetation traits and weed damage arising from herbicide-based management. The approach has been validated with stakeholder information about herbicide treatment using commercial products. As a result, broadband NDVI calculated from Sentinel-2 data showed explicit feedback after the glyphosate-based herbicide treatment. Vegetation damage could be detected after just two days following of glyphosate-based herbicide treatment. This trend was observed in three different application scenarios, i.e., during growing stage, before harvest and after harvest. The findings of the study demonstrate the feasibility of satellite based broadband NDVI data for the detection of glyphosate-based herbicide treatment and, e.g., the monitoring of latency to harvesting. The presented results can be used to implement monitoring concepts to provide the necessary transparency about weed treatment in agricultural practices and to support environmental monitoring.
    In: Remote sensing, Basel : MDPI, 2009, 11(2019), 21, Artikel-ID 2541, 2072-4292
    In: volume:11
    In: year:2019
    In: number:21
    In: elocationid:2541
    Language: English
    DOI: 10.3390/rs11212541
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  • 6
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    Linking remote sensing and geodiversity and their traits relevant to biodiversity - Part I : Soil characteristics (2019)
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    UID:
    (DE-627)1823177514
    Format: Diagramme, Illustrationen
    ISSN: 2072-4292
    Content: In the face of rapid global change it is imperative to preserve geodiversity for the overall conservation of biodiversity. Geodiversity is important for understanding complex biogeochemical and physical processes and is directly and indirectly linked to biodiversity on all scales of ecosystem organization. Despite the great importance of geodiversity, there is a lack of suitable monitoring methods. Compared to conventional in-situ techniques, remote sensing (RS) techniques provide a pathway towards cost-effective, increasingly more available, comprehensive, and repeatable, as well as standardized monitoring of continuous geodiversity on the local to global scale. This paper gives an overview of the state-of-the-art approaches for monitoring soil characteristics and soil moisture 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 trait variations (STV) to record geodiversity using RS are defined. LiDAR (light detection and ranging), thermal and microwave sensors, multispectral, and hyperspectral RS technologies to monitor soil characteristics and soil moisture are also presented. Furthermore, the paper discusses current and future satellite-borne sensors and missions as well as existing data products. Due to the prospects and limitations of the characteristics of different RS sensors, only specific geotraits and geodiversity characteristics can be recorded. The paper provides an overview of those geotraits.
    In: Remote sensing, Basel : MDPI, 2009, 11(2019), 20, Artikel-ID 2356, 2072-4292
    In: volume:11
    In: year:2019
    In: number:20
    In: elocationid:2356
    Language: English
    DOI: 10.3390/rs11202356
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  • 7
    Online Resource
    Online Resource
    Remote Sensing of Regional Soil Moisture (2022)
    Basel : MDPI - Multidisciplinary Digital Publishing Institute
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    UID:
    (DE-627)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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    Stabi Berlin
    UB Potsdam
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  • 8
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    Online Resource
    Linking the remote sensing of geodiversity and traits relevant to biodiversity - Part II : Geomorphology, terrain and surfaces (2020)
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    UID:
    (DE-627)1823174914
    Format: Diagramme, Illustrationen
    ISSN: 2072-4292
    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.
    In: Remote sensing, Basel : MDPI, 2009, 12(2020), 22, Artikel-ID 3690, Seite 1-61, 2072-4292
    In: volume:12
    In: year:2020
    In: number:22
    In: elocationid:3690
    In: pages:1-61
    Language: English
    DOI: 10.3390/rs12223690
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  • 9
    Book
    Book
    Fisch Land Fluss : eine Zeitreise durch die Fischereigeschichte am Niederrhein (2020)
    Neuss : Clemens Sels Museum
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    UID:
    (DE-627)173773544X
    Format: 146 Seiten , Illustrationen
    ISBN: 9783936542974
    Note: Publikation anlässlich der Ausstellung "Fisch Land Fluss. Eine Zeitreise durch die Fischereigeschichte am Niederrhein", die vom 27. September 2020 bis zum 31. Januar 2021 im Clemens Sels Museum Neuss zu sehen ist
    Language: German
    Keywords: Niederrhein-Gebiet ; Fischerei ; Geschichte ; Ausstellungskatalog
    URL: Inhaltsverzeichnis
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    Stabi Berlin get availability status
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  • 10
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    Monitoring of spatiotemporal change of green spaces in relation to the land surface temperature : A case study of belgrade, serbia (2021)
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    UID:
    (DE-627)1823173578
    Format: Diagramme, Illustrationen
    ISSN: 2072-4292
    Content: Understanding the relationship between land use and land cover and thermal environment has recently become an emerging issue for urban planners and policy makers. We chose Belgrade, as a case study, to present a cost-and time-effective framework for monitoring spatiotemporal changes of green spaces in relation to the land surface temperature (LST). Time series analysis was performed using Landsat 5 TM and Landsat 8 OLI/TIRS imagery from 1991 to 2019 with an approximate 5-year interval (18 images in total). Spectral vegetation indices and supervised land cover classifications were used to examine changes of green spaces. The results showed a fluctuating trend of the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI). The highest values were recorded in 2019, indicating vegetation recovery in the last decade. A significant positive correlation was determined between the spectral vegetation indices and the amount of precipitation during growing season. The land cover classification showed that the share of vegetated and bare land decreased by 11.74% during the study period. The most intensive conversion of green and bare land into built-up land cover occurred in the first decade (1991–2000). To assess spatiotemporal changes in the LST, Landsat Collection 2 Surface Temperature products were used. We found a negative correlation between change in the spectral vegetation indices and change in the LST. This indicates that the reduction in vegetation was associated with an increase in the LST. The municipalities that were the most affected in each decade were also identified with our framework. The findings of this study are of great relevance for actions targeting an improvement in urban thermal comfort and climate resilience.
    In: Remote sensing, Basel : MDPI, 2009, 13(2021), 19, Artikel-ID 3846, 2072-4292
    In: volume:13
    In: year:2021
    In: number:19
    In: elocationid:3846
    Language: English
    DOI: 10.3390/rs13193846
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