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  • Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten  (26)
  • 1
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    Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten
    Publication Date: 2022-01-14
    Description: Abstract
    Description: At the KlimaCampus (http://www.klimacampus.de), Cluster of Excellence at the University of Hamburg, an Integrated Climate Data Center (ICDC: http://www.icdc.zmaw.de) is established, suitable for data during the scientific project phase as well as storing long-term archive data. ICDC aims to make data out of different internal and external archives easily accessible for the daily work of the KlimaCampus scientists. It extends the existing services by the announcement of data during the scientific project phase, a data portal and collaboration services. Therein, ICDC utilizes the available infrastructure at the WDC Climate by using it for metadata storage and as a long-term archive. The concept of ICDC, its functionality, its implementation status, and future perspectives are presented.
    Description: SeriesInformation
    Description: Proceedings of the Data Management Workshop, 29-30 October 2009, University of Cologne, Germany, Kölner Geographische Arbeiten, 90, pp. 127-135
    Keywords: Earth System Science ; Climate Research ; Data Portal ; Metadata ; Data Management
    Language: English
    Type: Text , Workshop paper
    Format: 1841 Kilobytes
    Format: 9 Pages
    Format: application/pdf
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  • 2
    Publication Date: 2022-01-14
    Description: Abstract
    Description: The multidisciplinary research unit 'Biodiversity and Sustainable Management of a Megadiverse Mountain Ecosystem in South Ecuador' established a central data management system to provide the members with all gathered scientific data. Additionally, to the database functionality of the system the web based layout is capable to present general information on the research unit to the public and support accounting and administration of the project. All parts of the system are implemented using open-source or free software. A major task is the allocation of a sophisticated and detailed metadata scheme. The standardized ecological metadata language (EML) is used as the basis for metadata information stored in a relational database. The describing datatypes are highly modular and can be expanded if necessary. Data input and searching is implemented through a dynamic webinterface with easy to use forms. This is important to increase the acceptance of the system by users. Searching the database is possible by strings for keywords, authors, etc. or by geographic locations. Except for gridded data, all single values of the datasets are stored in relational tables and thus, it is possible to extract only parts of a whole dataset during data download. While the system is already operational, modifications and new features are continuously implemented.
    Description: SeriesInformation
    Description: Proceedings of the Data Management Workshop, 29-30 October 2009, University of Cologne, Germany, Kölner Geographische Arbeiten, 90, pp. 59-64
    Keywords: Metadata ; Ecological Research ; Data Management
    Language: English
    Type: Text , Workshop paper
    Format: 1005 Kilobytes
    Format: 6 Pages
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  • 3
    Publication Date: 2022-01-14
    Description: Abstract
    Description: WDC-RSAT is hosted and operated by the German Remote Sensing Data Center, DFD of the German Aerospace Center (DLR) under the nongovernmental auspices of the International Council for Science (ICSU) and is the most recent data center in the WMO-WDC family, in cooperation with the World Meteorological Organization (WMO). WDC-RSAT cooperates with partners in establishing and making use of modern information technologies (e.g. Grid) in order to promote networking. It is already being implemented as a data publication agent for data related to remote sensing of the atmosphere and is thus authorized to assign so-called Digital Object Identifiers (DOI) to data sets. The German ICSU WDCs (WDC-Climate, WDC-Mare, WDC-Terra, and WDC-RSAT) have formed in 2004 the 'WDC-Cluster on Earth System Research' in order to promote interdisciplinary research related to Earth sciences. Following the recommendations of the Committee of Earth Observation Satellites (CEOS), WDC-RSAT is currently establishing in cooperation with NASA a portal for satellite-based atmospheric composition data (ACC) which ultimately will be integrated in the Global Earth Observation System of Systems (GEOSS).
    Description: SeriesInformation
    Description: Proceedings of the Data Management Workshop, 29-30 October 2009, University of Cologne, Germany, Kölner Geographische Arbeiten, 90, pp. 119-125
    Keywords: Data Management ; Metadata ; Remote Sensing ; Atmosphere
    Language: English
    Type: Text , Workshop paper
    Format: 495 Kilobytes
    Format: 7 Pages
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  • 4
    Publication Date: 2022-01-14
    Description: Abstract
    Description: AMMA program includes in situ measurements at many locations of West Africa and in the Gulf of Guinea, an intensive use of satellite data, diverse modelling studies, as well as human sciences field surveys and value-added products processing. Therefore, AMMA database aims at storing a great amount and a large variety of data, and at providing the data as rapidly and safely as possible to the AMMA research community. In order to stimulate the exchange of information and collaboration between researchers from different disciplines or using different tools, the database provides a detailed description of the products and uses standardized formats. AMMA database and the associated online tools have been fully developed and are managed by two teams in France (IPSL Data Centre, Palaiseau and OMP Data Centre, Toulouse). Datasets are stored in one or the other centre depending on their types, but all of them can be accessed through a single and friendly data request user interface. The complete system has been duplicated at AGHRYMET Regional Centre (CRA) in Niamey, Niger and is operational there since January 2009.
    Description: SeriesInformation
    Description: Proceedings of the Data Management Workshop, 29-30 October 2009, University of Cologne, Germany, Kölner Geographische Arbeiten, 90, pp. 45-51
    Keywords: Multidisciplinarity ; Database ; Data Management
    Language: English
    Type: Text , Workshop paper
    Format: 1119 Kilobytes
    Format: 7 Pages
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  • 5
    Publication Date: 2022-01-14
    Description: Abstract
    Description: Nitrogen (N) is one of the most essential elements in agriculture and ecology due to its direct role in determining crop yield and grain quality, as well as its association with canopy photosynthetic capacity and carbon-nitrogen cycling in the earth ecosystem. Remote sensing provides a useful way to capture canopy nitrogen and biomass with high spatial and temporal resolution. However, seasonal dynamics of plant morphophysiological variation hinder the simultaneous estimation of canopy N concentration (%N) and biomass using a traditional method such as vegetation indices because of the distinct dynamics of canopy biochemical and physical traits. In contrast, multivariate analysis method offers the capability of calibrating a model with multiple dependent variables of interest. Therefore, the main objective of this study was to, simultaneously, estimate canopy %N and biomass of rice using the partial least squares regression (PLSR) model. A field experiment was conducted for paddy rice fertilized with five N rates across five growth stages in 2008, located in the Sanjiang Plain, China. Results showed that the PLS regression model simultaneously explained 84% and 91% of the variation in %N and biomass, respectively, across the five growth stages. Our results also suggest that biomass is the dominant factor that affects the link between canopy dynamical traits and canopy reflectance measures. This study demonstrates that, by incorporating with PLSR for retrieving biophysical and biochemical properties from the full-spectrum analysis, to what extent canopy %N and biomass can be simultaneously estimated from canopy reflectance measurement.
    Keywords: Nitrogen ; Biomass ; Hyperspectral ; Remote Sensing ; Agriculture ; 550 Earth sciences
    Language: English
    Type: Text , Workshop paper
    Format: 5 Pages
    Format: 1130 Kilobytes
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  • 6
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    Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten
    Publication Date: 2022-01-12
    Description: Abstract
    Description: This paper provides an overview of the range of techniques available for integration of heterogeneous data. These range from the wrapper-mediator architecture for integration of structured and semistructured databases: semantic mediation, which involves mapping schema elements and data values to ontologies: to ad hoc, vertical data integration where the user is in the loop of the integration. Every integration technique requires an expert in the loop—at different points in time and at different places in the system, depending on the integration technique employed. Future directions include provision of provenance and social networking information corresponding to the integrated data result.
    Description: SeriesInformation
    Description: Proceedings of the Data Management Workshop, 29-30 October 2009, University of Cologne, Germany, Kölner Geographische Arbeiten, 90, pp. 1-6
    Keywords: Other ; None ; Data Integration ; Data Management ; Heterogeneous ; Data Portal
    Type: Text , Book Section
    Format: 624 Kilobytes
    Format: 6 Pages
    Format: PDF
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  • 7
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    Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten
    Publication Date: 2022-01-12
    Description: Abstract
    Description: The availability and the appropriate use of accurate and widespread observational information are of paramount importance in order to increase the accuracy of weather forecasts. Data assimilation techniques provide a framework to find the best initial state that is consistent with all available information about the state of the system, here considered to be the Earth’s atmosphere. In this paper, a brief introduction to both variational and ensemble based data assimilation is provided, with a focus on the main characteristics of satellite data assimilation and some of its current issues.
    Description: SeriesInformation
    Description: Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 93-99
    Keywords: Other ; None ; Data Assimilation ; Numerical Weather Prediction ; Remote Sensing
    Type: Text , Book Section
    Format: 1906 Kilobytes
    Format: 7 Pages
    Format: PDF
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  • 8
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    Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten
    Publication Date: 2022-01-12
    Description: Abstract
    Description: Measurement errors in orthorectified images are very important when it comes to checking the subsidies claims made by European farmers. The Control with a Remote Sensing (CwRS) Programme, managed by the GeoCAP and CID actions of the Monitoring Agricultural Resources Unit of the EC Joint Research Centre (JRC), requires the establishment of guidelines to be applied by Member States when using remotely sensed images to verify farmers’ claims under the EU Common Agriculture Policy (CAP) subsidies. The area of land parcels used for farming are verified based on very fine spatial resolution (VHR) orthoimages that must meet specific geometric and visual qualities. As such, all VHR orthoimages used within this context must meet or exceed the EU standard as reported in Kapnias et al. (2008), based on external quality control (EQC). EQC is based on the root mean square error (RMSE) between the true geographic position and the image position of the independent check points (ICPs). The ICPs are points not included in the sensor model parameter estimation process and are derived from an independent source, preferably of higher accuracy. This report presents the applied EQC methodology and the geometric quality results recorded for the four samples of the KOMPSAT-2 (K2) radiometrically corrected images (processing level 1R), acquired over the JRC Maussane Test Site. The key issues identified during the testing based on the limited KOMPSAT-2 sample images that were made available to us are as follows: (a) The 1D RMS errors measured on the final K2 orthoimage after the single scene correction applying either the PCI rigorous model, the PCI RPC-based or the ERDAS RPC-based model are not sensitive to the number of GCPs used if they are well-distributed and range between 9 and 15 (provided a DTM with 0.6 m vertical accuracy), and they are sensitive to the overall off-nadir angle and increase with increasing off-nadir angle, (b) The average 1D RMSE are 2.1 m and 4 m, while the maximum 1D RMSE values are 3.2 m and 6.2 m of easting and northing direction respectively, provided that a DTM with 0.6 m vertical accuracy and GCPs with mean RMSE-X (in X direction) and RMSE-Y (in Y direction) values of 0.6 m are used, and (c) The orthorectified KOMPSAT-2 images do not fall within the accuracy criteria of the CwRS 1:10000 scale requirements, i.e. an absolute 1D RMSE not exceeding 2.5 m, except where the images are characterized by an overall off-nadir angle close to zero degrees, and the rigorous model or first order Rational Polynomial sensor model is applied.
    Description: SeriesInformation
    Description: Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 109-115
    Keywords: Other ; None ; Remote Sensing Methods ; Remote Sensing
    Type: Text , Book Section
    Format: 1127 Kilobytes
    Format: 7 Pages
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  • 9
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    Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten
    Publication Date: 2022-01-12
    Description: Abstract
    Description: The study aimed at providing a better understanding for monitoring the status, change and threats to UNESCO world heritage areas that are present in the tropical forest. Three change detection techniques were tested using Landsat images for detecting areas of change in the region of the Rio Platino Biosphere Reserve, a tropical rain forest in Honduras. The change detection techniques considered were image differencing, post-classification analysis using supervised classification and vegetation index differencing (NDVI differencing). Two Landsat scenes recorded in January 1986 and December 2002 were downloaded from USGS. Images were geometrically and radiometrically corrected and the three change detection techniques were tested. Change maps obtained from each technique were visually interpreted. In order to determine the accuracy of each change map, random points were generated using systematic sampling. For each random point, change/no change was separately evaluated by using high resolution data (Google Earth data) and a confusion matrix method. Image differencing for band 2 was found to be the most accurate one, followed by supervised classification and NDVI. Image differencing using band 3 was found to be less accurate than supervised and NDVI differencing. Supervised classification was selected for calculating area statistics inside and outside the UNESCO protected boundary because of the advantage of indicating the nature of changes. The study revealed two important changes in clear-cut areas and in regrowth areas. Clear-cutting has been found to be more frequent outside than inside the protected boundary of the forested UNESCO World Heritage Site.
    Description: SeriesInformation
    Description: Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 71-78
    Keywords: Other ; None ; Landsat ; Classification ; NDVI ; Remote Sensing
    Type: Text , Book Section
    Format: 677 Kilobytes
    Format: 8 Pages
    Format: PDF
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  • 10
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    Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten
    Publication Date: 2022-01-12
    Description: Abstract
    Description: Prehistoric archaeology is an object-oriented discipline. Archaeological objects like stone tools, bone tools or pieces of mobile art embed human behaviour. A central task of prehistoric research is to decode this information in order to reconstruct ancient human behaviour. This premise affords a defined set of tools for analysis and documentation to describe and evaluate particularly the shape of the object and its surface modifications manufactured by humans. Basis for all types of analysis is therefore a precise visual description of the object. This documentation forms part of the scientific process and should follow a generally accepted convention. Only when these rules are respected, a standardised and reproducible recognition of the object becomes possible.
    Description: SeriesInformation
    Description: Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 117-120
    Keywords: Other ; None ; Surface ; Remote Sensing
    Type: Text , Book Section
    Format: 3909 Kilobytes
    Format: 4 Pages
    Format: PDF
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